Rejecting Public Utility Data Monopolies

The threat of monopoly power looms large today. Although not the telecommunications and tobacco monopolies of old, the Goliaths of Big Tech have become today’s target for potential antitrust violations. It is not only their control over the social media infrastructure and digital advertising technologies that give people pause, but their monopolistic collection, use, and sale of customer data. But large technology companies are not the only private companies that have exclusive access to your data; that can crowd out competitors; and that can hold, use, or sell your data with little to no regulation. These other private companies are not data companies, platforms, or even brokers. They are public utilities.

Although termed “public utilities,” these entities are overwhelmingly private, shareholder-owned entities. Like private Big Tech, utilities gather incredible amounts of data from customers and use this data in various ways. And like private Big Tech, these utilities can exercise exclusionary and self-dealing anticompetitive behavior with respect to customer data. But there is one critical difference—unlike Big Tech, utilities enjoy an implied immunity from antitrust laws. This state action immunity has historically applied to utility provision of essential services like electricity and heat. As utilities find themselves in the position of unsuspecting data stewards, however, there is a real and unexplored question about whether their long-enjoyed antitrust immunity should extend to their data practices.

As the first exploration of this question, this Article tests the continuing application and rationale of the state action immunity doctrine to the evolving services that a utility provides as the grid becomes digitized. It demonstrates the importance of staunching the creep of state action immunity over utility data practices. And it recognizes the challenges of developing remedies for such data practices that do not disrupt the state-sanctioned monopoly powers of utilities over the provision of essential services. This Article analyzes both antitrust and regulatory remedies, including a new customer-focused “data duty,” as possible mechanisms to enhance consumer (ratepayer) welfare in this space. Exposing utility data practices to potential antitrust liability may be just the lever that is needed to motivate states, public utility commissions, and utilities to develop a more robust marketplace for energy data.

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Introduction

The threat of monopoly power looms large today. Although not the telecommunications and tobacco monopolies of old, the Goliaths of Big Tech, like Google, Apple, and Facebook, have become today’s target for potential antitrust violations.[1] It is not only their collection, use, and sale of data, but their control over the social media infrastructure and digital advertising technologies that has led to claims of consumer harm.[2] But there are other private companies that have exclusive access to your data; that can crowd out competitors; and that can hold, use, or sell your data with little to no regulation.[3] These private companies are not data companies, platforms, or even brokers. They are public utilities.

Although termed “public utilities,” these entities are overwhelmingly private and shareholder-owned.[4] Like private Big Tech, public utilities gather incredible amounts of data from customers and use this data in various ways that are unknown to the average customer. And like private Big Tech, these utilities can exercise exclusionary and self-dealing anticompetitive behavior with respect to this data. But there is one critical difference—unlike Big Tech, public utilities enjoy an implied immunity from antitrust violations.

This state action immunity has historically applied to utility providers of essential services—telecommunications,[5] heat,[6] and electricity.[7] This immunity was premised on a state-sanctioned grant of monopoly powers over customers in a specific geographic area in exchange for an agreement to provide non-discriminatory access to all customers and be subject to state regulation.[8] With the advent of big data, however, utilities also find themselves in the position of unsuspecting data stewards, collecting, using, and controlling vast amounts of data. Unlike their non-monopoly cousins that find themselves under increasing antitrust scrutiny, however, regulated monopolies have data practices that have been presumed to be protected by antitrust immunity. As such, this special class of private entities has flown largely under the radar of advocates and experts exploring best data practices.[9]

Scholars are increasingly addressing antitrust implications of Big Tech and their platforms,[10] but no one has analyzed whether this long-realized immunity should extend to utility data practices. A few scholars have urged sharing utility data,[11] and one colleague explored the antitrust implications of utility treatment of solar power.[12] But no one has questioned an assumed extension of antitrust immunity to utility data practices, and no one has realized that eliminating this immunity could be the path by which this data is released. Despite the privacy pitfalls that may arise,[13] this analysis joins the growing body of work from scholars who are reluctant to use privacy concerns as a blockade to enhance social welfare.[14]

This Article is the first exploration of this question of how far state action immunity extends, one which tests the continuing application and rationale of the doctrine to the evolving services a utility provides as the grid becomes increasingly digitized. This Article explores this through the lens of the quintessential regulated monopoly: the electric utility. Like their non-monopoly cousins, these regulated monopolies collect data from private individuals. This data is subject to various fates. Sometimes, it just sits in the cloud, never realizing its full potential.[15] Sometimes it becomes commodified and is traded or sold.[16] And sometimes, it realizes its full potential by helping to enhance utility operations or revealing itself to the public to further various public policy goals.[17] This analysis identifies state action immunity as a potential obstacle to this data realizing its full potential.

To that end, this Article provides three important contributions. First, it assesses the market power that utilities are assuming over energy data. Utilities are realizing the present and future value of such data, and already seem to be assuming that their monopoly power and their unique immunity extend to their data practices. Utilities are defaulting to serving as data stewards of massive amounts of previously “invisible” energy data that has become extremely relevant to efforts to decarbonize the grid,[18] enhance equities amongst customers,[19] and reap more profits.[20] Third parties working to enhance the reliability, cost-effectiveness, and environmental and distributional impacts of a transitioning electric grid full of solar panels, electric vehicles, and other customer-side resources find themselves limited by utilities that are clinging tightly to their grid, distribution, and customer data.[21]

Second, this Article demonstrates why state action immunity should not be assumed to extend to a utility’s data practices. It challenges the assumption of state action immunity for all aspects of a utility’s operations, interrogating its viability for utility data practices from both a doctrinal and a normative perspective. It finds anticompetitive utility data practices vulnerable on both counts. Courts have rejected antitrust immunities for a variety of utility practices that do not have express authorization and a clear intent to displace competition, as exists for most utilities today with respect to data.[22] Unlike non-monopoly companies, these regulated monopolies do not have big data analysis as part of their primary regulated function. Ultimate disposition will turn on state-specific analyses, but most utilities would have an uphill battle to cling on to state action immunity for their energy data.

Third, this Article explores potential remedies. It focuses on both non-structural antitrust remedies, as well as regulatory remedies that may be applicable to the data practices of public utilities. Faced with the harsh reality that state action immunity may not extend to their data practices, utilities would be on notice that related anticompetitive behavior could be subject to federal antitrust laws. The threat of such potential liability may be enough to incentivize utilities to engage in more thoughtful data practices. But at the very least, states could be catalyzed to take more intentional steps to optimize energy data use in ways that allow utilities to meet their privacy obligations to shareholders without staunching grid innovation, customer benefits, and environmental goals.

This analysis has practical significance given the crucial role that the electric grid plays in addressing climate change, a role that is enhanced with energy data. But this Article’s insights also have broader theoretical and practical implications. Policymakers and scholars have long tolerated an assumption of state action immunity for utility practices and have largely relied on the hope that utilities will function in a manner consistent with state public policies. But hope is not resulting in sufficient action. This Article challenges these assumptions and provides a forceful antitrust lever to achieve greater energy data access. My conclusions also support more vigorous state involvement in utility data practices. The void in clear state policies regarding the utility data marketplace does no one any good. Instead, states seeking to facilitate decarbonization efforts through grid efficiencies may see value in enhancing a competitive data market in their states.

Part I demonstrates the potential risks of a world where utilities cling tightly to energy data. The primary concerns are twofold: (1) misuse of energy data, and (2) squandered opportunities to use energy data to further efficiencies and social goals such as decarbonization. Part II then explains how antitrust law generally, and the state action immunity doctrine specifically, has served as an obstacle to realizing the highest and best use of this energy data. It demonstrates the doctrinal weaknesses associated with trying to extend state action immunity to a utility’s data practices. And it cautions against deferring to utility monopoly power over their energy data by default, given the risk of related anticompetitive utility behavior.

Part III then explores the paths forward for unshackling utility strangleholds over energy data, both through traditional antitrust doctrine as well as regulatory options. Following the antitrust path leads one to explore the implications of extending the state action immunity to utility data practices, concluding that legal, practical, and ethical analyses generally point toward rejecting such an extension. It then explores non-structural antitrust remedies such as pooling, line of business restrictions, and restructured management options, yet ultimately concludes that traditional antitrust remedies are an uncomfortable fit for a utility that otherwise functions as a state-sanctioned monopoly.

Instead, regulatory tools may provide a more direct remedy. Without the expectation of state action immunity to protect it, a utility may be more inclined to adjust its anticompetitive data behaviors. Accordingly, this Article urges states to provide a more thoughtful and intentional analysis of a utility’s data practices and provide guardrails for data treatment, including a potential new customer-focused “data duty” as a way to enhance ratepayer welfare. Opening utility data practices to potential antitrust liability may be just the lever that is needed to motivate states, public utility commissions (PUCs), and utilities to develop a more robust marketplace for energy data.

I. Assessing Public Utility Data Market Power

For over a century, public utilities have functioned against a backdrop of regulated monopoly power. This allowed states to maintain regulated monopolies across our country for the providers of essential services like water, gas, and electricity.[23] But the utilities now find themselves in the crosshairs of a growing digitalization of the energy sector. With this digitalization comes a deluge of increasingly granular data in a multitude of forms. Some of this data can serve important operational purposes if the utility capitalizes on this newfound resource. But some of this data, when shared beyond the utility, can also serve larger purposes for managing individual, regional, and national grid priorities. Because the data can be quite valuable, however, utilities seem inclined to keep a tight hold on it. With this hold come concerns about anticompetitive utility behaviors. These present themselves in two primary forms. In some instances, utilities can exclude competitors seeking to innovate and facilitate environmental and efficiency policy goals from accessing the data. In other scenarios, utilities engage in data self-dealing that allows them to benefit on the backs of ratepayers. Neither is acceptable nor consistent with the principles historically justifying utility monopolies.

This Part first provides some of the critical background on public utilities and their historic monopoly power. It then assesses a utility’s market power over data, using electric utilities to demonstrate how an evolving electric grid is leading to an explosion of valuable energy data. But the crux of this analysis highlights the danger of monopoly creep from a utility’s traditional function into its data practices, with challenges for competition that can affect efficiencies, consumer protection, and the success of environmental policies.

A.     The Unique Status of a Government-Regulated Utility Monopoly

To understand why an electric utility has exclusive control over electricity data, one must first understand its unique government-regulated monopoly status.[24] In the United States, some of the most common types of regulated monopolies are public utilities.[25] The majority of public utilities are privately owned[26] but distinguish themselves from non-regulated private companies like Amazon and Facebook by the fact that they are providing an essential service to the public. This distinction traces to as early as the 1837 Supreme Court case Charles River Bridge,[27] where the Court acknowledged the state’s need to shield private entrepreneurs engaged in risky infrastructure investments that benefit the public good. Where these private entities were providing an essential public service clothed in the public interest, the government and the private entity agreed to shield the entity from the antitrust laws.[28]

Such regulated monopolies are based on what has historically been called the “regulatory compact” between the state and these utilities. This compact reflects the state laws passed in the nineteenth century that granted these entities—mostly private entities—exclusive territory and a customer base free from competition in exchange for providing non-discriminatory and reliable services to the public, with rates subjected to state regulation.[29] State public utility commissions, charged with striking a fair balance between utility and consumer interests, oversee and regulate utility rates and practices.[30] Such monopoly status provides these entities with a variety of advantages over other private companies, including protection from volatile market fluctuations.[31] While these utilities must obtain approval for their spending from state regulatory bodies, the resulting investments yield a stable rate of return unrivaled in the free marketplace.[32] Without the regulatory compact, we may not have the electric grid we know today.

A shift toward competition in the late 1990s and 2000s led many economists to question the continuing logic of extending this special monopoly status to all aspects of an electric utility.[33] Instead, the continued appropriateness of this monopoly status was dissected concerning the three components of the electric grid: generation, transmission, and distribution.[34] While transmission and distribution remained sensible given the economies of scale associated with wires, the government carved out generation from the monopoly umbrella, thus opening the doors to competition and wholesale markets.[35] As small-scale renewable energies began to enter and compete against incumbent large-scale fossil fuel generators, the rules had to change with them. As a result, Congress passed the Public Utility Regulatory Policy Act of 1978 (PURPA),[36] the Energy Policy Act of 2005 (EPAct),[37] and other laws aimed at unshackling the historic monopoly power of utilities.[38] Today, scholars continue to scrutinize arguments supporting monopoly power over other aspects of the grid, primarily regional transmission siting.[39]

B.     Big Energy Data

This Article builds upon this scrutiny with respect to energy data. Some scholars are already claiming that the current fusion of the biological, physical, and digital worlds reflects the next biggest transformation in society since the steam engine, electricity, and digital revolutions.[40] Coined the “Fourth Industrial Revolution,”[41] this transformation is only possible with massive amounts of data. This data-dependent society infuses those who control this data with immense power.[42] Although it is true that data may have little value without the subsequent analytics to convert the data into useful information, the data still serves as the necessary foundation for all that is derived from it.

Private companies are leading the charge in this data grab, perhaps incentivized by the delta between those who control the data and those who provide it.[43] Some private companies have this data by virtue of their successful capitalistic pursuits.[44] They have succeeded in providing society with such a popular product that many of us are willing to voluntarily relinquish our data as a cost of using the product.[45] For years, this relinquishment occurred with little fanfare, with most users unaware that their use of “free” products actually came at a cost to their privacy.[46] The era of big data has altered the interface that consumers use to interact with the world. Essentially every activity, from changing the temperature of your house on your smart thermostat, to turning on your car, generates data that at least one company collects.[47]

As data has become even more valuable, these companies have come under increasing public scrutiny for their lapses in data collection,[48] retention,[49] and sharing.[50] This has triggered privacy,[51] due process,[52] and even bankruptcy[53] concerns. But as privacy scholars turned their attention to this technological space,[54] and as the EU and at least 19 U.S. states have enacted privacy laws,[55] companies have overwhelmingly adopted consent-based or other disclosure policies.[56] During this same period, the general public has become more sophisticated in its understanding of these products.[57] Nevertheless, these developments have done little to slow individuals from voluntarily sharing data, as most individuals still find that the cost-benefit analysis tips in favor of voluntarily and knowingly allowing access to their private personal data.[58]

Significant concerns still exist, however, about the mosaic effect of aggregating seemingly innocuous data points to develop quite detailed information on an individual.[59] Given the intimate connection between data and power,[60] many scholars have written about the pitfalls of letting such data fall into the hands of both the government[61] and private companies and the challenges of balancing privacy concerns with the benefits of access and use of data.[62] This important work can be grouped into three approaches. Some scholars focus on individual privacy harms to those whose data is shared without their consent or control.[63] Others focus on the commercial harms that can result from the significant barriers to data access and consolidation of power over data in the hands of a few.[64] And a last category of scholars focus not on harms, but on ways to harness the societal benefits that can result from sharing collected data.[65]

This last category is the target of this Part. One of the targeted societal benefits is decarbonization of the electric grid. Spurred by public policies surrounding reducing greenhouse gases from fossil fuels,[66] the grid began to increase its reliance on clean energy sources. In 2010, renewable energy sources like solar and wind comprised only 7.5 percent of U.S. electricity generation.[67] Although hydroelectric and biomass comprised the bulk of historical renewable contributions,[68] public policies like renewable portfolio standards facilitated a steep upward trajectory for rooftop solar, as well as utility-scale solar and wind, which are now making significant contributions.[69] This was facilitated in large part by plummeting costs. The costs of solar electricity have dropped by 85 percent and the costs of both offshore and onshore wind have dropped by about 50 percent since 2010.[70] In 2024 over 70 percent of the new capacity added to the grid came from renewable sources.[71] And renewables in both distributed and utility-scale forms comprised over 21 percent of the nation’s electric grid in 2023.[72] This momentum is likely to continue, with President Biden’s signing of the Inflation Reduction Act, authorizing $369 billion for clean energy and the Bipartisan Infrastructure Act, authorizing $26 million to demonstrate how the electric grid can run reliably with a mix of solar, wind, and energy storage.[73] Such policies to decarbonize the electric grid, facilitated by those regions of the country that opened their generation markets to competition, caused the grid to transform.

The most important transformation for purposes of this analysis is that the grid is becoming increasingly digitized. This change was fueled in part by a 2007 federal law requiring the DOE to research and develop the “smart grid.”[74] The grid has begun to transform from an antiquated, siloed, and one-directional grid[75]—that is dependent on humans to identify problems and maintain continual matching of supply and demand—to a grid that is becoming increasingly modernized, interconnected, two-directional, and automated.[76] In turn, the nature, frequency, and volume of electricity data is growing exponentially.

The sheer amount of data is increasing by virtue of the increasing number of energy generators. The electric grid is evolving from one where large, centralized (often fossil fuel) utilities dominated the landscape to one where small, distributed (often renewable) energy sources (DERs)[77] are starting to provide a more significant amount of an area’s electricity needs. Some localities such as Hawaii are even targeting DERs to provide 50 percent of their electricity needs.[78]

This means that customers are transitioning from being passive receivers of energy to also being active producers of energy,[79] primarily through DERs like rooftop solar, which customers can use to inject their own power into the grid. Such solar installations have grown from 972.5 megawatt capacity to 23,212.9 megawatt capacity over the last ten years.[80] Traditional centralized generators produce steady streams of data, but as distributed sources of energy flourished, they required accompanying technologies to reach their full potential. For instance, enabling customers to share their energy with the grid requires inverters[81] and two-directional smart meters. Smart meters measure and record electricity usage at a minimum of hourly intervals, sometimes at fifteen-minute intervals, and provide the data to both the utility and the utility customer at least once a day.[82] Utilities have already installed about 119 million advanced (smart) metering infrastructure (AMI) installations in 2022.[83] By 2027, 93 percent of U.S. households are projected to have smart meters[84] and the market is expected to grow substantially by 2030.[85] Some customers even more actively contribute to grid management through supply-side initiatives as demand response[86] and energy efficiency programs.[87]

Customers’ transition from internal-combustion engines to electric vehicles (EVs) also provides millions of additional data points. There are nearly 1.7 million EVs in the United States,[88] with 26.4 million EVs projected to be on U.S. roads by 2030.[89] Use of this new fleet of EVs will be facilitated by charging stations, providing even more distributed sources of data.[90] By 2027, EVs are projected to represent 23 percent of new passenger vehicles.[91] Some pilot projects are even testing the feasibility of using customers’ connected EVs to store and inject electricity into the grid as needed (V2G pilots).[92]

Furthermore, even greater digitalization is expected to continue. Key players in the energy industry are calling digitalization a “global imperative.”[93] The International Energy Agency has reported on the importance of increased digitization to “enable utilities to better predict demand and supply imbalances, and to locate and fix faults more quickly.”[94] Products are even being developed to digitize utility rates.[95]

All these changes mean that utilities are now responsible for achieving the same level of performance in a much more complicated and dynamic grid. But it also means that they find themselves inundated with a particular resource—data.

C.    The Value of Big Energy Data

The value of big energy data for utilities is substantial, enabling them to enhance operations, transition to cleaner energy, and achieve cost savings. Data is not a new resource for utilities. In fact, utilities have relied on data analytics for the bulk of their existence[96] from the early days of pioneers like Insull to the present-day strategies of major entities like AEP, an investor-owned utility.[97] Among other data needs, past data analytics allow utilities to plan and forecast for the needs of their customers[98] and current data helps them demonstrate compliance with various regulatory requirements. Electric utilities gather three main types of data collectively known as “energy data”: (1) grid-level data (e.g., real-time information on loads, available assets, locations, aggregated data from smart meters);[99] (2) distribution-level data (e.g., actual energy production levels, performance data, costs, capacity of assets);[100] and (3) customer-level data (e.g., personal identifiable information, energy usage, billing, rates, and individual smart meter data).[101] Energy data empowers utilities to plan for customer needs, ensure regulatory compliance, and optimize their overall performance. However, the landscape is rapidly changing, and utilities must now grapple with big data—datasets that surpass traditional analysis in terms of the “three V’s”: volume, velocity, and variety.[102]

The shift to big data presents new challenges for utilities. Traditional tools like geographic information system used by utilities to analyze and display data specific to a location, may no longer be enough due to the sheer volume, velocity, and variety of data today. “Even in 2022, a typical electric utility geographic information system (GIS) probably contains only a fraction of what is required for managing a smart grid.”[103]

All this collected data is seemingly worthless without rigorous analysis.[104] The data collected and stored must be examined to uncover trends, patterns, and correlations.[105] Data analysis is complicated, and companies employ numerous methods of analysis, including data clustering and data mining.[106] Notably, one of the hidden values found in big data is its ability to enable efficient inferential data analysis.[107] Technological advances have allowed companies to go beyond the raw data to “identify patterns that create answers to questions [they] didn’t even know to ask.”[108] Artificial intelligence and machine learning, in particular, can drastically enhance such predictions.[109] Data analysis expands the dataset of the initial personal data collected,[110] all without the involvement or knowledge of the consumer.[111]

In leveraging data analytics, utilities unlock a wealth of advantages through their exclusive access to energy data. These benefits are twofold: operational enhancements and strategic insights. Operationally, utilities use grid data to monitor voltage, currents, frequency, and flow to balance loads and prevent outages.[112] This data analysis converts raw information into valuable insights, leading to improved operational efficiency and cost reduction.[113] For instance, Public Service Electric and Gas Company (PSE&G), one of the largest combined electric and gas companies in the United States,[114] employs data analytics to evaluate the conditions of its generators.[115] The company looks to multiple factors, such as moisture, dielectric strength, combustible gas rate of change, and cooling performance, to determine the appropriate time to replace transformers.[116] In 2015, the company believed that using this data to proactively replace transformers would help save $100 million over a twenty-five-year period.[117]

Secondly, utilities facilitate the transition to a cleaner energy grid by harnessing this energy data.[118] Energy scholars and think tanks have lauded the benefits that broader access to electricity data can have for the critical grid transformations on the horizon.[119] Other information, such as which customers are connected to which transformers and where rooftop solar panels are located, require other, more granular data inputs.[120] This data can range from distribution data on the utility’s transformers and the substations it uses to manage the delivery of electricity to weather data used to help forecast demand and plan for outages.[121] For example, smart meters allow utilities to realize a number of operational benefits, including eliminating the costs of meter reading, enhanced billing accuracy, and better outage response time.[122] Customer self-generation through rooftop solar allows utilities to defer construction of additional power plants.[123] Even EVs may become part of the generation supply as regions pilot “vehicle-to-grid” programs that allow utilities to draw upon connected EVs during peak periods.[124] Effective use of all this data allows utilities to reap impressive cost savings.[125]

Thirdly, the most granular level of data involves customer data. Customer data comes in many forms, including billing information.[126] This category can include customer information, such as birthdate, address, language, electronic contact details, bank details, employment, and whether the client receives financial assistance.[127] Moreover, it can include information on the consumption site, often a private residence, including the type of metering, connection, date of construction, number of occupants and rooms, and types of equipment (e.g., rooftop solar).[128] But it can also include a more detailed accounting of the customer’s energy consumption levels and patterns through data collected by smart meters.[129] More than half of utility providers in the United States have an infrastructure that allows delivery of consumption data in hourly (or even smaller) time frames.[130] This specificity of data empowers utilities “to disaggregate consumption data and identify large loads within a household that could be schedulable, such as electric vehicle chargers and pool pumps.”[131] And because customer data can include residential, commercial, and industrial customers, this data can be the most valuable.

Both utilities and customers can realize the commercial value of this energy data. When certain regulatory structures are in place and where customers can access their data, customers can experience cost savings.[132] However, when utilities are in complete control of all this energy data, they control the extent to which its commercial value is realized. For example, the Minnesota PUC commissioned a comprehensive staff briefing paper about the data practices of its utilities with regard to customer energy use data (CEUD) and found the following:

Data are valuable. Many services are provided to customers at no charge solely to allow the service provider access to customer data – consider Google, Facebook, Yahoo and the myriad apps available for smart phones and tablets. The economic worth of these entities derives, in significant part, from the information they obtain from their users. While Staff cannot provide any estimate of the value of CEUD (no doubt it varies from person to person), it is clear from the Navigant report discussed in Section 7 that there is considerable commercial value in CEUD. Some energy customers may be content to release their CEUD to third parties for little or no compensation, but non-consensual release to vendors and conservationists (even if anonymized and aggregated) raises the question as to how that asset value should be distributed – to third parties at no charge, or maintained within the utility and released as a packaged and priced commodity that could benefit utility ratepayers.[133]

As the next Section demonstrates, the monopoly power that utilities exercise over this data can lead to perverse incentives by utilities to not only hoard this data for themselves, but to possibly use it to the detriment of their ratepayers and society at large.

D.    Anticompetitive Impacts of a Utility’s Assumed Monopoly Over Data

As the scope of utility services expands into data management, utilities may expect that the exclusive monopolies they have long enjoyed similarly extend to this area. Utilities may argue that they have exclusive rights to this data merely by virtue of having an approved monopoly over the infrastructure that captures it (e.g., smart meters). However, the vast potential associated with data analytics unveils the intricate power dynamics between public and private data, tensions between datasets, and competition amongst private companies for not only the raw data, but also the talent needed to complete the analytics.[134] Merely assuming a utility has exclusive control of such energy data, either explicitly or implicitly, renders it susceptible to questionable, and perhaps anticompetitive, data practices.

Several examples highlight the challenges posed by such data practices. Legal scholarship has been inundated with questions surrounding the collection, use, and retention of data.[135] While bias in the various datasets used to train artificial intelligence[136] has received substantial attention, significant privacy concerns also surround the collection of this data.[137] Utility data is no exception. Seemingly innocuous electricity data can be aggregated to tell a particularly compelling story about an individual—a story that they may prefer to leave untold.[138] In 2022, for instance, a California water utility targeted customers with excessive water use during a drought.[139] Las Virgenes Municipal Water District issued a “Notice of Exceedance” to more than 2,000 customers, including celebrities like Sylvester Stallone and Kim Kardashian, who surpassed 150 percent of their monthly water budgets.”[140] The local newspaper obtained the notices through a Public Records Act request, resulting in public shaming of the named celebrities.[141] Although some may have little sympathy for this particular disclosure, public shaming is just the tip of the iceberg.

More serious disputes about the proper use of electricity data have reached the desks of state attorneys general charged with protecting their citizens from abuse, manipulation, fraud, and invasion of privacy.[142] The Center on Privacy & Technology at Georgetown Law found that Equifax had taken utility customer files intended for credit evaluation purposes and sold them to Thomson Reuters to create “person-search” databases used by U.S. Immigrations and Customs Enforcement to identify people for deportation.[143] The Seventh Circuit, in holding that forcing residents to switch to smart meters violates their reasonable expectation of privacy,[144] noted that “[r]esidents certainly have a privacy interest in their energy-consumption data.”[145] Instead of a privacy focus, many of which involve invasion of privacy harms, however, this Article approaches the utility data conundrum from a different perspective—one of anticompetitive harms and antitrust.

Spurred in part, perhaps, by the government’s recent antitrust suits against Big Tech,[146] scholars have started contemplating the antitrust implications of big data. Some scholars have been hesitant to characterize private, data-hungry companies as having a data monopoly.[147] Some have critiqued the concept of data monopolies, suggesting that the term should not apply to data holders because they fail to harm consumers like traditional monopolies.[148] Others, in contrast, have begun to explore the intersection of big data and antitrust implications,[149] with some suggesting that antitrust laws will play a prominent role in promoting digital platform competition for the benefit of consumers.[150] But none have explored the applicability of state action immunity to private regulated utilities’ energy data practices.

This blind spot is odd considering the unique status of a regulated monopoly. The implications of a private regulated utility’s control, potential self-dealing, and ability to exclude others from using data are too important to slip under the radar of regulators and scholars. Such capabilities further exacerbate the inequities between those whose data is fueling these dynamics (ratepayers) and those who have found a way to capitalize on such data (utilities). Despite occasional cases of data breach associated with utilities,[151] this Part focuses on anticompetitive utility data practices that benefit the utility at the expense of the ratepayer. A utility’s exclusive access to this data also increases its opportunities to enrich itself at the ratepayer’s expense.

Importantly, a utility need not enjoy only direct financial benefit from the sale or trade of customer-provided data. There are various other ways that a utility can benefit from its treatment of data, including maximizing its own competitiveness and minimizing its use by competitors in their own and secondary energy markets. When concentrated economic power harms competition and consumers, however, this should be a cause for concern. This Part explores the two primary avenues for utilities to abuse their assumed monopolies over data: (1) barriers to entry or missed opportunities, and (2) self-dealing.

1.     Barriers to Entry

Initially, a utility’s firm grasp on energy data raises concerns about preventing competitors and customers from leveraging its potential benefits. Most scholarly attention has been focused on opening up utility treasure troves of customer data for grid modernization, whether it be through energy efficiency[152] or demand response programs.[153] Data advocates argue that utilities are hiding behind privacy[154] or cybersecurity[155] justifications to maintain their data monopoly, resulting in anticompetitive tendencies.[156] Some have even filed petitions with the Federal Trade Commission (FTC) arguing that utilities have blocked access to data that is “essential for communities to evaluate public power and other alternative business models.”[157] Petitioners allege that an Iowa utility refused to provide a city with access to customer, infrastructure, and rate data to prohibit evaluation of developing a new municipal utility, a would-be competitor to the incumbent utility.[158]

The harmful effects of such strangleholds on data intensify when there are various competitors seeking this valuable energy data[159] in both wholesale and retail energy markets. Those participating in competitive energy wholesale markets can suffer from a lack of energy data possessed by utility competitors, and those participating in competitive retail markets may be particularly susceptible to abuse.[160] Three categories of competitors highlight the problem with barriers to entry for data.[161]

The first category consists of demand response (DR) aggregators in wholesale markets.[162] These aggregators gather multiple customers together who are willing to forego electricity during peak grid times to help smooth demand and eliminate the need to construct additional, inefficient (and often fossil-fuel based) peaker generation.[163] A critical component of this business model is the need for customer data, but utilities may withhold or inflate the cost of accessing such data in ways that may not be easy to detect.[164] Such allegations are beginning to arise. A curtailment service provider (CSP) filed a Section 206 complaint with the Federal Energy Regulatory Commission (FERC) in late 2023 alleging that utilities “have consistently demonstrated limited cooperation or limited ability to cooperate” and that utilities have “refused to provide CSPs with the residential AMI data at scale that would enable CSP participation in the PJM markets.”[165]

A second category of competitors are those seeking to provide time-of-use (TOU) rates in retail markets.[166] TOU rates can assist with efforts to transition the grid by sending price signals to customers to shape their energy usage.[167] Whereas most residential customers pay block rates by volume, TOU rates fluctuate in real time based on the actual demands on the grid.[168] To create such innovative products, competitors need access to data. For instance, a competitor in Ohio has petitioned its PUC to expire the incumbent utility’s TOU rates because the incumbent, AEP, has “failed to meet its obligations and continues to delay the development of systems and processes that would provide Certified Retail Electric Suppliers (CRES) the data necessary to create and bill for dynamic TOU offerings that customers will purchase. Absent adequate data from AEP, the TOU market will never be ‘sufficiently competitive.’”[169] The competitor alleged that “if we continue down the current path where CRES providers cannot obtain adequate bill-quality Customer Energy Usage Data (CEUD) from AEP—the overall TOU market will remain stagnant, and the benefits of AMI will continue to go untapped.”[170] The Ohio PUC ruled against these CRES providers, finding that it is sufficient for AEP to provide access to the AMI data through a “manual process” and a requirement that AEP “thoroughly evaluate” the automation of this process to ensure compliance with a state regulation that “a customer’s data is provided in a standard format and providing to third parties in as close to real time as is economically justifiable. . . .”[171]

A third category of competitors are technology companies seeking to provide services that enhance the efficiencies of the grid.[172] Such firms are developing entire business plans from identifying cost-saving and efficiency gains that can save their clients money and help advance the goal of reduced fossil fuel use for the grid.[173] Companies like Arcadia just received a $200 million investment to improve its data platform by broadening its access to energy data, enabling the development of new products and services to give consumers more advanced management solutions.[174] Arcadia’s Arc platform “democratiz[es] access to energy data from 125 utilities nationwide,” purportedly “break[ing] the fossil fuel monopoly.”[175] Arcadia uses this data to provide its customers with the resources critical to making informed decisions when implementing energy efficiency goals, siting renewable energy projects, or projecting energy costs.[176]

Utilities do not appear eager to relinquish the data required by companies like Arcadia,[177] forcing them to pursue the much less efficient and roundabout route of obtaining data directly from customers.[178] One example is the circuitous path Arcadia must take to get energy data for the wind energy program it has developed.[179] With this program, Arcadia acts as a middleman between the customer and the utility, intercepting data along the way. Although this structure may help increase demand for wind energy, devoting time and resources to this suboptimal means of collecting data limits both the scope and depth of data that can be used.[180]

In one sense, the more a utility can obscure its data, the less scrutiny it will face and the more it can set up roadblocks to data sharing. The American Council for Energy Efficiency has been tracking all fifty states and their policies (or lack thereof) on data sharing with third parties, finding that the majority of states have “no policy in place that requires utilities to release energy use data to customers or third parties.”[181] Mission:data, a national coalition of technology companies seeking to empower customers with access to their own energy and cost data, is working to enhance data portability[182] and identify utility misuse of customer data.[183]

A utility’s use of its customer data is further complicated by the fact that almost all investor-owned utilities (IOUs) use private utility management software to assist customers with storing, accessing, analyzing, and computing their data in connection with accounting, regulatory, and tax needs.[184] Not only is this action outsourced, but it is outsourced to a powerful incumbent software company, creating monopolistic challenges akin to those of the public utilities themselves. In fact, one such private software company, PowerPlan, provides software services to 90 percent of utilities.[185]

Competition against PowerPlan has proved particularly vexing. When a competitor won a bid to provide these software services to one of the country’s largest utilities, AEP, PowerPlan worked to intimidate both the competitor and the utility. This included warnings to AEP that it would not be able to “permit” its utility customers to access “[PowerPlan’s] proprietary software and associated confidential information.“[186] The result is a pending antitrust lawsuit by the competitor against the incumbent software developer.[187] The competitor alleges that PowerPlan has inhibited its ability “to obtain important data reflecting customers’ needs, develop that data to accomplish business objectives, and raise revenue.“[188] Such ancillary private companies, who serve as gatekeepers of utility data, should give us pause, if not concern.

Furthermore, a utility’s resistance to using this energy data productively can also hinder other societal improvements. One example is the use of energy data to address energy insecurity. Scholars have documented how impactful additional energy data could be to helping low-income communities.[189] Yet utilities have notoriously done a poor job of using their data for good.[190] Some suggest providing market facilitators with access to individual, identifiable records.[191] A number of states have responded by expressly allowing utilities to share data to identify areas with high energy burdens and affordability problems.[192]

Not only can such utility resistance thwart innovation by third-party entities seeking to enhance efficiencies or optimize electric vehicle charging, but there may also be missed opportunities if the underutilized data sits with a complacent utility. If the utility was using this data to benefit its customers and society, its control over data might not be so troublesome. This may be consistent with serving the “public interest” in accordance with statutory mandates.[193] “Unfortunately, too many utilities struggle to produce and identify quality data to inform decision making.”[194] Utilities may realize that this data will be even more valuable in the future as the grid transforms and customers continue to generate more of their own electricity.[195] By holding onto data for the future, they may be ensuring the data’s relevance and competitiveness for an unknown utility future.[196] As old as the debate between acts and omissions, both affirmative blocking of access as well as non-use by the utility can cause anticompetitive harm.

2.     Self-dealing

If hoarding energy data is not bad enough, utilities may also engage in data practices that would be considered self-dealing. Realizing the enhanced value of both old and new data, entire industries have arisen around data brokers who trade in data.[197] Thousands of data brokers in the United States buy, aggregate, disclose, and sell billions of data elements on Americans with virtually no oversight.[198] Armed with this data, these companies are able to increase profits through targeted ads,[199] risk management,[200] and product or service optimization.[201] Similarly, utilities leverage their customer data, gathered through their regulated activities, to enhance their unregulated activities.

First, utilities may be using and profiting from the data for secondary purposes that are not essential to their traditional utility functions. For instance, a utility may use its data to promote its own products or market for a third party.[202] By synthesizing demographics, usage patterns, customer support interactions, and third-party data, utilities can predict behaviors like a person’s likelihood to pay, enroll in self-service, be interested in conservation programs, and more.[203] As a result, these utilities can segment customers and reduce costs of marketing. Although it is difficult to disentangle and quantify these benefits, the fact that a few states ban utilities from selling customer data[204] suggests that these sales may be happening in one of the many other states that do not have an express prohibition. Furthermore, these prohibitions do not preclude utilities from voluntarily sharing customer data with third-party entities.

Second, utilities may be able to leverage their monopoly power in related competitive markets.[205] For a third of the country, in traditional regulated regions, energy provision operates whereby one utility provides the generation, transmission, and distribution services to its customers.[206] In such regions, there are often parent utilities with subsidiaries that function in competitive markets.[207] They have access to information that provides them with a distinct advantage over others in their field.[208] Entities with both regulated and unregulated subsidiaries may pose the greatest risk to fair markets because the data gathered by the regulated arm may be shared with the unregulated arm, giving it a competitive advantage in its market activities.[209] For example, a French court has entertained claims that its Engie utility (formerly GDF Suez) was improperly sharing information between its regulated and unregulated subsidiaries.[210] Vertically integrated utilities in Florida, Alabama, and Georgia have also been scrutinized for improperly sharing solar data.[211]

Similarly, examining two cases involving a municipality’s ability to leverage its monopoly power into other markets, Professor Nachbar notes that “the restraints in both City of Lafayette and Hallie involved the potential to leverage the city’s monopoly power within its own jurisdiction into markets where the city was not politically accountable.”[212] Similar concerns surround a utility’s use of customer data. A utility has the potential to leverage its unique monopoly power over data in markets where it is not politically accountable.[213] In such cases, as Professor Nachbar notes for cities, there is little reason to believe that a utility’s “public interest” orientation is likely to do much work.

In short, utilities will continue to find themselves inundated with energy data, whose increasing value can result in asymmetric information dynamics. Disentangling various utility uses of this data is difficult, but there are at least allegations that utilities are not sharing this data with customers or competitors unless forced to do so. And there are real concerns that utilities will use their monopoly power to advantage themselves at the cost of ratepayers. In such scenarios, an assumed data monopoly serves no one. Utilities are functioning without the regulatory certainty that exists for their monopoly over the provision of essential services. Customers who want access to their data may find it difficult to do so.[214] And third parties who are seeking to innovate are repeatedly denied access to the data needed to do so. The degree to which these actions are anticompetitive will vary from case to case, but prudence dictates caution and additional investigation before assuming that a utility’s historic antitrust immunity for its provision of electricity services should extend to its data practices.

II. The Limits of Public Utility Immunity From Antitrust Violations

Given the anticompetitive nature of some utility data practices, antitrust law springs to mind as a potential lever to loosen utilities’ hold over energy data. But unlike other private companies, public utilities enjoy a special status with regards to competition. Although federal and state antitrust laws provide for remedies against anticompetitive conduct, the Supreme Court has carved out an exception for state-sanctioned anticompetitive action based on federalism concerns. In certain situations, the Court has extended this federal immunity to private actors working in concert with the state, including public utilities. This Part provides the foundations of federal protections against anticompetitive conduct, explains the contours of the state action immunity doctrine, and situates electric utilities, with their state-sanctioned monopoly powers, in the context of this immunity, questioning the viability of extending this immunity to a utility’s treatment of data.[215] As one economist has asked with respect to solar monopolies, “[W]hat can antitrust do that will complement as opposed to interfering with or creating tensions with regulation?”[216] The answer may lie in limiting the state action doctrine.

A.     Anticompetitive Behaviors Subject to Antitrust Violations

In response to concerns over price fixing, Congress passed the Sherman Act in 1890.[217] For the last 132 years, this statute, assisted by the Clayton Act[218] and the Federal Trade Commission Act,[219] has worked to protect competition in this country.[220] U.S. antitrust enforcement relies on a combination of public and private rights of action to protect against anticompetitive behaviors, with incentives like treble damages and attorneys’ fees driving significant private enforcement.[221] Public enforcement originates with the Federal Trade Commission (FTC) or the Department of Justice (DOJ), and as they describe:

Antitrust laws protect competition. Free and open competition benefits consumers by ensuring lower prices and new and better products. In a freely competitive market, each competing business generally will try to attract consumers by cutting its prices and increasing the quality of its products or services. Competition and the profit opportunities it brings also stimulate businesses to find new, innovative, and more efficient methods of production. Consumers benefit from competition through lower prices and better products and services. Companies that fail to understand or react to consumer needs may soon find themselves losing out in the competitive battle. When competitors agree to fix prices, rig bids, or allocate (divide up) customers, consumers lose the benefits of competition. The prices that result when competitors agree in these ways are artificially high; such prices do not accurately reflect cost and therefore distort the allocation of society’s resources. The result is a loss not only to U.S. consumers and taxpayers, but also the U.S. economy.[222]

The Sherman Act contains two relevant provisions for this analysis. Section 1 of the Sherman Act makes “every contract, combination . . . or conspiracy, in restraint of trade or commerce among the several States . . . illegal.”[223] More than an anticompetitive effect is necessary for a Section 1 violation. Such an effect must be the result of a “contract, combination . . . or conspiracy.”[224] This element of agreement distinguishes Section 1 from Section 2 of the Sherman Act, which makes it unlawful to “monopolize, or attempt to monopolize, or combine or conspire with any other person or persons, to monopolize any part of the trade or commerce among the several States.”[225] This Article is not intended to be an exhaustive treatise on antitrust law, as ample antitrust scholars around the world serve that function.[226] Instead, for purposes of this Article, it is enough to understand some of the anticompetitive behaviors targeted by the Sherman Act, the rationales for doing so, and the potential remedies. It is also important to understand the limitations of Sherman Act liability, as evidenced by the state action immunity doctrine.

B.     The Relevant Contours of State Action Immunity

Although the Sherman Act does not provide an express exclusion for government-sanctioned private monopolies, the Supreme Court has created a pathway for utilities to claim immunity from federal antitrust laws.[227] Most scholars credit the development of such immunity to the Supreme Court’s decision in Parker v. Brown.[228] As others have aptly detailed,[229] what began as a constitutional challenge to the validity of a state program to ration raisins, turned into a question by the Supreme Court as to whether the California statute was preempted by the Sherman Act.[230] In assessing the constitutionality of a state’s anticompetitive raisin practices, the Court noted that the “Sherman Act makes no mention of the state as such.”[231] Adopting not a literal interpretation, but one derived from the “purpose, the subject matter, the context and the legislative history” of the Sherman Act, the Court held that it only prohibits monopolies by individuals or corporations, not the state.[232] Grounded in federalism concerns, the Court held that state and municipal authorities are immune from federal antitrust lawsuits for actions taken pursuant to a clearly expressed state policy that, when legislated, had foreseeable anticompetitive effects.[233] When a state approves and regulates certain conduct, even if it is anticompetitive under federal antitrust standards, the federal government must respect the decision of the state.[234] This reasoning laid the foundation for what would later be known as “state action” immunity.

It was not until decades later that the state action doctrine was extended from state actors to private actors acting on behalf of the state.[235] From raisins to wine, most point to the Supreme Court’s 1980 opinion in California Retail Liquor Dealers Association v. Midcal Aluminum (Midcal) for a clearer articulation of the “state action” doctrine.[236] There, a private wine retailer challenged a state law that prohibited wine sales below a particular level as violating the Sherman Act.[237] Rejecting state action immunity, the Court found the state law to violate Section 2 of the Sherman Act and determined that the state’s involvement in the wine-pricing system was “insufficient to establish antitrust immunity under Parker v. Brown.”[238] Importantly, the Court more clearly articulated a two-part test for the state action immunity doctrine: (1) there must be a clearly articulated policy to displace competition, and (2) there must be “active[e] supervis[ion]” by the state of the policy or activity.[239]

With many questions unanswered, subsequent courts struggled to better define the contours of state action immunity.[240] The 1980s and 1990s involved, among other developments, the evolution of a “reasonably foreseeable” anticompetitive effects test,[241] as well as a compulsion requirement, whereby “mere pervasiveness of a regulatory scheme does not immunize an industry from antitrust liability for conduct that is voluntarily initiated.”[242] The big question became the degree of state involvement that was required to trigger state action immunity. Early cases suggested that only private anticompetitive activity required by the state would trigger immunity (referred to as the “compulsion requirement”), a perspective that was later rejected by the Supreme Court as described below.[243] The reasonably foreseeable test, on the other hand, relaxed the strict “intent” to displace competition requirement to allow immunity even where an anticompetitive effect of a state authorization was “merely foreseeable.”[244]

The Supreme Court in Southern Motor Carriers Rate Conference v. United States provided some clarity, affirming that the Midcal “reasoning extends to suits against private parties” and rejecting the “compulsion requirement” as a threshold requirement for state action immunity.[245] Applying Midcal, the Court held that the collective ratemaking of four private motor transportation rate bureaus was immune from Sherman Act liability because, though not compelled by the state, it was clearly sanctioned by the legislatures of the four states in which the bureaus operated.[246] This decision extended the reach of the state action immunity, finding it to cover both private parties as well as state involvement that was less than a state mandate. Its broadened interpretation held that while a state requirement was still the best evidence of satisfying the first part of the Midcal test—”clearly articulated and affirmatively expressed policy to displace competition”—it was not the only way to satisfy that prong.[247]

By 2013, however, state action immunity had fallen into disfavor.[248] Some have taken issue with the state action doctrine’s evolution from a political one, grounded in federalism concerns in Parker, to an economic one, grounded in self-dealing concerns in North Carolina State Board of Dental Examiners v. FTC.[249] Professor Nachbar, for instance, has argued for the irrelevancy of state action immunity for private parties in light of other antitrust immunities and protections. The Noerr/Pennington doctrine, for instance, protects private lobbying efforts to obtain regulation that produces anticompetitive advantages.[250] Similarly, the Filed Rate doctrine protects antitrust suits against utilities that have filed rates with the Federal Energy Regulatory Commission or a state public utility commission.[251]

In practice, however, parties and courts continue to recognize the state action doctrine’s viability as a potential immunity shield. As recent as late 2023, a federal district court applied the two-part Midcal test to a state law involving a medical center’s acquisition of three hospitals.[252] In 2022, the Ninth Circuit noted that it applies “only when it is clear that the challenged anticompetitive conduct is undertaken pursuant to a regulatory scheme that ‘is the State’s own.’”[253] And in 2018, the Federal Trade Commission applied state action doctrine to challenge a state board in which market participants exercising regulatory oversight, noting that “the state action doctrine guides this analysis.”[254]

C.    Inapplicability of State Action Immunity to Data Practices

Given its continuing viability, this last Part analyzes the merits of extending the state action immunity, traditionally associated with a utility’s provision of its electricity services, to its data practices. As shown below, a doctrinal analysis would be very state-specific, depending on whether the state has clearly addressed utility data practices. But in the majority of states, utilities arguing for such a novel extension of their historic immunity are likely to face an uphill battle. And beyond doctrine, strong normative arguments exist based on policy rationales for rejecting immunity for utility data practices.

Courts still apply the Midcal two-part test and ask whether (1) there is a clearly articulated policy to displace competition and (2) there is “active supervision” by the state of the policy or activity.[255] Furthermore, as the defendant claiming state action immunity bears the burden of proof,[256] the utilities would need to demonstrate that their data practices were taken pursuant to state policy. As discussed below, this may prove to be an elusive burden.

From a purely doctrinal view, most courts would likely reject a utility’s attempt to invoke the state action immunity over data practices. Courts have clarified that while “both theories of [antitrust] liability and defenses apply with full force to utilities,”[257] utilities are not automatically insulated from antitrust laws merely by virtue of their state regulation.[258] Nevertheless, with fifty states’ laws governing thousands of utilities in each state, judicial inquiry into this matter would result in an intensive state-specific statutory inquiry. This Part demonstrates the difficulties of applying the two-part Midcal test to utility data.

1.     Clear Intent to Displace Competition

To satisfy the first prong, a utility would need to demonstrate that its data practices are expressly authorized[259] with a clear intent to “displace competition”[260] in the data marketplace. What would this look like with respect to utility energy data practices? Perhaps a clear statement by the state through a statute or PUC order that utilities are to be the sole and exclusive stewards and users of energy data would do. Finding such a statement or order proved to be an elusive task. Searches for state statutes or public utility commission orders empowering utilities’ anticompetitive data practices left me near empty-handed.[261]

A survey of the American Council for an Energy Efficient Economy (ACEEE) database reveals that less than half the states have addressed the use of energy utility data at all, either through legislation or PUC order.[262] The majority of those states explicitly allow for energy data sharing after customer consent.[263] A handful of states require sharing of energy data with specific third parties (often state-funded energy efficiency programs or electricity generators themselves).[264] Two states prohibit utilities from selling customer data,[265] and several states have begun the process of creating statewide platforms to facilitate energy data sharing.[266] Some state privacy laws also impose obligations on utilities related to customer notice, consent, and data retention,[267] but the overwhelming majority of states are silent on this issue.[268]

This silence does not bode well for most of the country’s utilities if they tried to launch a state action immunity defense. The utilities in states that allow or require data sharing would have an uphill battle to establish state action immunity. That is because states that require data sharing may more closely reflect a clear statutory preference for competition in a relevant market, the exact opposite of what is needed to satisfy the first prong of Midcal. At least one circuit seems to agree. In 2022, the Ninth Circuit rejected state action immunity for a Phoenix water and electric utility, the Salt River Project (SRP).[269] Customers brought suit under the Sherman Act, alleging that the utility engaged in anticompetitive conduct when it charged its solar customers higher rates.[270] The Court held that the state of Arizona clearly expressed the exact opposite preference of that required for state action immunity—a preference for competition.[271] In reality, state action immunity is less likely to be necessary in states where utilities provide access to their energy data.

Even in the few states where state privacy laws have explicitly prohibited utilities from selling personally identifiable information (PII), arguments for state action immunity would be strained. The utilities could argue that this state prohibition is an implicit recognition that the utility should be the sole state steward of energy data. But, courts are inclined to find immunity where states limit competition “to achieve public objectives.”[272] A strong argument could be made that customer privacy is a valid public objective, but a strong preference for customer privacy does not necessarily indicate a policy to “displace competition” as required by the first prong of Midcal.[273] Furthermore, state law does not prohibit other non-sale methods of sharing or bartering customer energy data and does not apply to non-PII data, loopholes that may work to weaken immunity arguments.

However, the vast majority of the remaining states are functioning in a void of “clear” or “express” authorization regarding intentions about the competitiveness of data.[274] A case in point for electric utilities is Quadvest, L.P. v. San Jacinto River Authority, in which a water utility faced a Section 1 allegation.[275] In that case, the Fifth Circuit rejected state action immunity for the water utility under the “intent to displace competition” prong of Midcal.[276] Even applying the more flexible “foreseeable result” anticompetitive effects test mentioned earlier,[277] the court held that “bare authority to participate in a market [as a result of state authorization] does not inherently result in monopoly.”[278]

Importantly, the court noted that even if the utility’s enabling statute provided “monopoly power over the market for surface water . . . precedent cautions against interpreting such statutory authority as extending to the entire wholesale raw water market.”[279] The court noted that authorization from the state must be “market-specific” and rejected immunity for the water utility in their attempts to extend their authorized monopoly over surface water to the wholesale water market.[280] Similarly, even though state enabling statutes provide electric utilities with monopoly power over the provision of electricity, similar caution should be exercised before extending such monopoly to all of its data activities. In short, the traditional natural monopoly justifications for utility provision of essential services ring hollow when applied to data.

2.     Active Supervision

Even if a utility could somehow piece together an argument that the state had clearly articulated a policy to displace competition for energy data, satisfying the second Midcal prong would remain a challenge. To satisfy the second prong, a utility must demonstrate that its data practices are “actively supervised” by the state.[281] Utilities may think they are on strong footing because they are regulated by state public utility commissions. However, while PUC approval of anticompetitive measures has provided immunity for private entities in the past,[282] it is not always sufficient to satisfy the “active supervision” prong of the Midcal test. For instance, in FTC v. Ticor, the Supreme Court rejected immunity for insurance rates even though they had been approved by state commissions.[283] Instead, the Ticor test asks “whether the State has exercised sufficient independent judgment and control so that the details of the rates or prices have been established as a product of deliberate state intervention, not simply by agreement among private parties.”[284] In this case, it is not the details of rates or prices but the details of the data collection, access, and management practices that are contested. At issue are practices that appear to be at sole discretion of the utility.[285] Given the complete silence on energy data from most state legislatures and PUCs,[286] utilities in these states are unlikely to have compelling state action immunity claims. Even in those states where there is some mention of energy data, it would be a stretch to argue that there is “active and comprehensive supervision” of energy data practices sufficient to garner state action immunity.

Although monopoly status may have been imperative to establish an initial electric grid, great caution should be taken before this monopoly power is extended to other functions of the electric utility. This Part demonstrated why the doctrinal and policy rationales for providing utilities with a monopoly and immunity shield over functions like transmission often fail to extend to functions like data collection and processing. Without state action immunity to protect utility data practices, the last question that remains is whether the risk of potential antitrust liability might better incentivize states, public utility commissions, and utilities to develop more consumer-friendly energy data practices.

III. Using Antitrust Levers to Benefit Consumers

If the preceding discussion has demonstrated anything, it is that we should be cautious about defaulting to extending state action immunity to a utility’s data practices without state intentionality to do so. By not taking such immunity for granted with respect to their data practices, utilities may recognize their vulnerabilities to possible antitrust liability for actions that block competitor access to energy data.[287] This realization alone may be enough to incentivize more thoughtful data practices by utilities. But at the very least, this last Part demonstrates how even the specter of antitrust liability could catalyze states to take more intentional steps regarding the utility energy data practices.

This Part demonstrates the potential viability of a prima facie Section 2 claim and the important implications of such a holding for the transition to clean energy. It focuses on potential remedies, both internal and external, to traditional federal antitrust laws, with the ultimate goal of optimizing energy-data use in a way that allows the utilities to meet their obligations to shareholders without staunching grid innovation, customer benefits, and environmental goals. Importantly, it demonstrates why antitrust remedies provide an uncomfortable (and disfavored) fit for regulated utilities and how the unique nature of the regulated public utility should enable the same remedies to be better achieved through regulation.

A.     Traditional Antitrust Remedies: An Uncomfortable Fit

If a competitor could sustain a successful Section 2 violation, a real puzzle exists surrounding what would be the appropriate remedy. Antitrust generally addresses vertical and horizontal restraints that constrain the relevant market,[288] with courts providing broad power to develop remedies intended to restore competitive conditions.[289] This can include breaking up a company into smaller bits through forced divestiture[290] or a judicial injunction against the anticompetitive practice.[291] Structural remedies often are not as useful where an entity has not gobbled up competitors in a merger or slew of acquisitions.[292] This makes structural remedies inapplicable for a public utility, which we want to remain intact to continue to provide essential services consistent with its natural monopoly characteristics.[293]

As Professor Herbert Hovenkamp has argued, antitrust remedies should use criteria consistent with the goals of antitrust and be “evaluated by its success in increasing output, decreasing prices, improving product quality, or spurring innovation.”[294] Similar criteria should drive analyses of utility energy data behavior. The answer may turn on how one defines the optimal outcome with regards to energy data—is it to promote access to utility data, to facilitate a robust marketplace for energy data, or some other goal?

This Part explores the basics of a prima facie Section 2 claim, as well as two non-structural (behavioral) remedies that could apply to the data practices of public utilities: increased interoperability and line of business restrictions.[295] Both have complicated limitations when applied to utilities.

1.     A Duty to Deal in Data?

Although this work is focused primarily on cautioning against an assumed extension of state action immunity to a utility’s energy data practices, the strength of antitrust law’s ability to motivate state and utilities turns on the strength of a competitor’s Section 2 prima facie Sherman Act claim.[296] To establish liability for that claim, plaintiffs will need to show: (a) a utility’s possession of monopoly power in the relevant market, (b) the willful acquisition or maintenance of that power, and (c) causal antitrust injury.[297] In many cases, a plaintiff can demonstrate a utility’s monopoly power in the market for energy data[298] and a utility’s willful acquisition or maintenance of monopoly power over data.[299]

Given allegations of the utility’s refusal to share energy data, the much more interesting analysis, and the focus of this Part, is on the third element—the antitrust injury. Antitrust injury is “injury of the type the antitrust laws were intended to prevent and that flows from that which makes defendants’ acts unlawful.”[300] The difficulties arise with the lack of clarity surrounding the most likely theory of harm—the “confounding and controversial” refusal to deal and the subsequent duty to deal.[301] Although courts have interpreted Section 2 of the Sherman Act to allow one firm to refuse to conduct business with another firm,[302] they have also repeatedly found Section 2 liability where an entity’s motivation for refusing to deal was solely based on an intent to maintain a monopoly[303] or where the refusing entity controlled essential facilities.[304]

Many scholars have spent decades trying to identify the boundaries of these doctrines and understand the courts’ fluctuating support for it.[305] In 1985, the Supreme Court accepted a refusal to deal Section 2 violation in Aspen Skiing Co. v. Aspen Highlands Skiing Corp. without clear adoption of either the intent or the essential facilities test.[306] There, in a dispute between various ski resorts over a dissolution of a combined ski lift ticket, the Supreme Court found that the monopolist’s refusal to deal with another resort was “not motivated by efficiency concerns” and that the record in that case “comfortably supports an inference that the monopolist made a deliberate effort to discourage its customers from doing business with its smaller rival.[307]

The Supreme Court’s 2004 analysis in Verizon Communications Inc. v. Trinko illustrates the limitations of the duty to deal doctrine in the public utility space.[308] There, an incumbent telecommunications utility blocked access to its operations support systems. Justice Scalia rejected Section 2 liability, holding that the Telecommunications Act of 1996 governed the sharing requirements of the utility. He based his analysis in large part on the fact that the “in certain circumstances, ‘regulation significantly diminishes the likelihood of major antitrust harm.’”[309] Given the federal statute that already exists to “deter and remedy anticompetitive harm” and the Federal Communications Commission’s active regulation of this space, the Court held that competitors failed to state a Section 2 claim.[310]

Furthermore, although Justice Scalia, who frowned upon the duty to deal in Trinko, questioned the “uncertain virtue of forced sharing”,[311] there are enough distinctions in the situation of utility energy data to suggest that Trinko may not completely block a competitor’s Section 2 claim with respect to energy data. First, Justice Scalia noted that “[t]o safeguard the incentive to innovate, the Court will not find the possession of monopoly power unlawful unless it is accompanied by an element of anticompetitive conduct.”[312] As described in Part II.D., there is a variety of anticompetitive conduct a utility may take with regards to data that exists independent of its legal monopoly status to provide essential services. Second, Justice Scalia leaned heavily on the mandated access provisions of a federal telecommunications statute, a federal mandate that does not exist in the context of energy data.[313] Third, although Justice Scalia was concerned that forced sharing may disincentivize firms from investing and innovating and that “[c]ompelling such firms to share the source of their advantage is in some tension with the underlying purpose of antitrust law,” he was content with forced sharing through regulatory means.[314] A utility’s unique status as a regulated entity provides it with an advantage that is not gained by its own innovative work, but by the state, which is funded by regulated rates paid for by the ratepayers.

Despite the current disfavor of imposing a duty to deal, scholars such as Erik Hovenkamp have acknowledged that antitrust can play an important gap-filling role where regulatory policy is not explicit.[315] In Otter Tail, where there was no explicit regulatory mandate to deal with competing electricity providers and no state intent to displace antitrust jurisdiction, the Supreme Court held the refuser liable under Section 2 for a refusal to deal.[316] Similarly here, where there is no explicit regulatory mandate on utilities to deal with competing users of energy data and no intent to displace jurisdiction, the Supreme Court could find a utility liable under Section 2 for a refusal to deal. Just as Professor Hovenkamp argued that a duty to deal could be revived in cases where a defendant’s refusal to deal acts to leverage the defendant’s monopoly in one market to undermine competition in an adjacent market, a strong claim of antitrust liability against a utility may arise if a utility was using its monopoly in one market (electricity) to harm competition in an adjacent market (data).[317] Where consumer harm can be defined as damaging customers by raising prices or lowering product quality to increase firm profits,[318] one can envision a utility whose data practices make it more expensive to access data or dilute the quality of the data. Where such liability can be established, antitrust can provide a remedy unattainable through regulatory channels. The next two sections address two such remedies: increased interoperability and line of business restrictions.

2.     Increased Interoperability with Pooling

Interoperability has many definitions and can take different forms. As Professor Hovenkamp has explained, interoperability “can include everything from ‘dynamic’ interoperability, which requires real-time sharing of data and operations, to ‘static’ interoperability which requires portability but not necessarily real-time interactions.”[319] One form of interoperability is pooling, which occurs when the systems of multiple firms are linked in a way that permits users to process the same information simultaneously.[320] Such a remedy is perhaps seen most frequently in the technology industry, where patents serve as an effective barrier to entry. By pooling their intellectual property, innovative companies can create integrative products using patented intellectual property where they would otherwise need to obtain many different patent licenses.[321] While information pools can originate voluntarily, with different patent holders jointly (or even unilaterally[322]) pooling information and technology together, courts can also mandate the creation of information pools through injunctions or other orders.[323] Professor Hovenkamp noted that interoperability can be important “when a firm with dominance in a particular product refuses to interconnect with outsiders in ways that could make the network larger and more socially valuable.”[324] In the Terminal Railroad natural monopoly case, for instance, the court ordered “reorganization” so that any existing or future railroad was allowed access to the terminal properties as a joint owner.[325] Further, the reorganization had to provide for “reasonable access” to railroads that chose not to become joint owners.[326] He offered this option as a potential remedy for platforms, noting that Facebook and its spinoff firms could have “full and immediate access to all data, subject to users’ individual right to block.”[327]

If antitrust remedies are about enhancing competition to benefit the consumer, there is a strong argument that opening the customer data market to competition would benefit the ratepayers.[328] To achieve this end, courts could require greater interoperability among users of energy data through standardization of data or pooling of data into a common database. This could be interoperability requirements that compel firms to work together to develop products and services that are compatible with those offered by their competitors. In the medical context, data interoperability refers to the ways in “which data is formatted that allow diverse datasets to be merged or aggregated in meaningful ways.”[329] In the case of energy data, this might require data to be standardized in a way such that there could be a fluid exchange between utilities, third parties, and customers.

Faced with the possible imposition of such judicial remedies, utilities may even voluntarily adjust their behavior. Recognizing that their data practices are vulnerable to antitrust remedies, utilities may even affirmatively concede that state action immunity does not apply to their data practices.[330] As such, utilities may proactively reach voluntary data sharing agreements that provide equal access to their data, resulting in one of two likely strategies. In one scenario, utilities may “step up” to the challenge of competition and work to innovate and use the data in productive ways. The opportunity cost of sitting on their data could be increased, eviscerating any calculus that favored the future value of the data over its present value. Alternatively, utilities may concede to their competitors, allowing those entities to innovate in ways that provide better services and enhance social welfare. Both scenarios arguably benefit ratepayers.

Although this Article is not the place for a lengthy discussion of privacy arguments, it would be imprudent not to flag that data sharing efforts are likely to face increasing headwinds as data privacy legislation advances.[331] With no federal data privacy law, twelve states have already taken steps to enact their own data privacy laws.[332] Most of the proposed bills are largely modeled after the European Union’s General Data Protection Regulation (GDPR),[333] regarded as one of the world’s most protective data privacy laws.[334] Such laws attempt to mitigate information asymmetries by giving consumers the right to request the data collected about them and requiring companies to list any third-party recipients of the data, and, if algorithms are used, the data subjects must be given insight into the “logic” behind the profiling.[335] Similar concerns about privacy have been voiced with respect to energy data sharing.[336]

These privacy concerns should not trump the benefits of data sharing, particularly since there are many thoughtful measures that allow for striking a balance between these competing interests. In the energy industry, ample evidence suggests that methods to share data in anonymized ways are increasing.[337] Similarly, in the healthcare context, advanced data perturbation and aggregation methods have been used to preserve patient anonymity.[338] Similar anonymization of utility data would allow for optimization without compromising consumers’ privacy. Even though this remedy creates some tension between customer privacy and enhanced performance of the electric grid, courts could require interoperability of energy data through access conditioned on careful privacy protections.

3.     Line of Business Restrictions

A last-resort antitrust remedy against an anticompetitive utility could be a line of business restriction (LOBR). A LOBR is a legal limit on the range of activities in which a firm can engage.[339] Such a remedy can be used when there are concerns that “dominance is leveraged to exclude rivals in another downstream market . . . through discriminatory self-preferencing . . . or refusal-to-deal.”[340] The most famous examples of judicially enforced line of business restrictions include those in the 1956 Consent Decree that prevent AT&T from engaging in any business other than the provision of common carrier communications services.[341]

Some scholars have criticized LOBRs, arguing that preventing firms from entering certain areas of business can foreclose welfare-enhancing transactions[342] and that the LOBRs enforced against AT&T’s divested operating companies were actually preventing benefits from flowing to consumers.[343] However, careful drafting and timing stipulations can protect against shifting market conditions,[344] and continued support for this remedy can be found in proposed bills that still contemplate LOBRs.[345]

In the case of utilities, a court could issue a LOBR limiting a utility from participating in the energy data market. This could prevent the utility from self-preferencing or sharing energy data between regulated and unregulated components of its firm. It may also limit the utility’s ability to restrict access to third parties. But this would be extremely difficult to implement and enforce, given that utilities need this data to provide electricity to customers. The court order would be complicated by the entanglement of data used to enhance the operations of the grid and data used for purposes beyond the provision of services. Instead, a more creative approach may be to issue a LOBR restricting how public utilities can profit from the use of ratepayer data.

B.     Regulatory Remedies: A More Appropriate Solution

Given the uncomfortable fit of these antitrust remedies and the disfavored duty to deal,[346] regulatory remedies may provide a more fruitful resolution to anticompetitive utility behavior toward data.[347] Unlike judicially imposed or private remedies, regulatory remedies would originate with the relevant state or public utility commission. However, they would serve the same purpose of restoring competition in the energy data markets.[348] A state or PUC would first need to recognize the net welfare costs of allowing utilities to maintain monopolies over energy data. Then, functional remedies similar to those courts have imposed can be achieved through regulatory measures.[349] A recent international example of a regulatory remedy is the European Commission’s June 2023 Directive on access to metering and consumption data. It mandates that data on energy metering and consumption in EU countries use one common reference model to facilitate interoperability so that consumers will be able to get easy access to their metering data and also give permission for data on their energy consumption or generation to be used by third parties in ways which benefit them.[350] Another example of regulatory measures to address the confidentiality of consumer data can be found in the telecommunications industry. Telecommunications providers, like utilities, gather sensitive personal information about their customers during the normal course of providing an essential service (e.g., telephone numbers of calls made and received; the frequency, duration, location, and timing of such calls; and any services purchased by the consumer).[351] Termed customer proprietary network information (CPNI),[352] and facing similar privacy concerns, Congress passed the Communications Act of 1934, in part, to restrict carriers’ use and disclosure of their customers’ proprietary information.[353] Such regulatory remedies would not be constrained to addressing anticompetitive harms, but can also protect against a variety of potential consumer harms (including privacy harms) associated with customer data.[354]

Importantly, regulatory remedies to address anticompetitive harms in the United States would only be imposed if a state declines to take steps to protect public utilities from antitrust liability. Consistent with the federalist origins of state action immunity, a state would be free within its jurisdictional authority[355] to expressly and intentionally determine that a utility’s monopoly power should extend to data practices.[356] Utilities make substantial investments in the electric grid to serve their customers.[357] In fact, given these investments, one might argue that it is appropriate for the utilities to reap the sole benefits of the data they gather.[358] Others may argue that the utility, as a private company, is meeting its obligations under securities laws by using this data to enhance shareholder value.[359] And yet others may argue that there is no reason for the utilities not to capitalize on data where people have consented to its use.[360] Privacy concerns may even motivate state legislatures, justified by claims of enhancing “privacy” and “cybersecurity,” to pass similar laws restricting the sharing of customer data.[361]

Where a utility can demonstrate that all of its data practices, including more sophisticated analyses, can benefit its ratepayers or further broader public policy goals, the state or the PUC is responsible for expressly articulating that such actions—even if anticompetitive—fall within the scope of the utility’s obligations. A state can then more easily establish state action immunity for its utilities by expressly intending for the utility to be the exclusive collector, manager, and user of this data. In a scenario where a state doubles down on a utility’s monopoly powers, the regulator would hopefully also issue attendant regulatory restrictions that would help increase output, decrease prices, improve product quality, and spur innovation—all of which are goals consistent with antitrust law.

Assuming that a state declines to extend state action immunity to its utilities data practices, however, this last Part provides two possible regulatory remedies to better realize the goals of antitrust. In both scenarios, the public utility commissions would need to play a more crucial and active role in regulating their utilities’ use of energy data. In the first, a utility is required to share its energy data. In the second, a utility is required to share the benefits of its energy data.

1.     Utility is Required to Share Data

An initial regulatory remedy might require the utility to share its energy data.[362] If energy data is viewed as more of an essential facility, states could compel utilities to share this data with competitors, similar to how the Federal Energy Regulatory Commission required forced sharing of transmission lines through Order 888.[363] In fact, the vast literature exploring the illusory confines of the public interest[364] suggests that in a situation where an electric utility inherits exclusive access to data, states should compel firms to share their ratepayer-provided advantages.[365]

The regulatory version of forced sharing is beginning to materialize in some states. As noted earlier, four states are exploring platforms that would facilitate energy data transfers.[366] The Pennsylvania legislature, for example, required the sharing of smart meter data to electric generation suppliers and conservation service providers.[367] The Pennsylvania PUC has an Electronic Data Exchange Working Group (EDEWG) that is responsible for helping facilitate the electronic data interchange. It determined that electricity distributors must make historic interval usage (HIU) and billing quality interval use (BQIU) data available via an online portal.[368] Citing privacy concerns, the PUC declined to extend the data access to independent third parties, such as Mission:data, noting that these parties are not subject to the same standards of consumer privacy protection as state-sanctioned electric generation suppliers or conservation service providers.[369] Although the model of regulatory forced sharing requires each state to evaluate questions including customer consent, the scope of the sharing, and functionality, the utilities would no longer be making these calls. Instead, the PUCs would become gatekeepers of the energy data.

2.     Utility Retains Data Rights with Obligation to Benefit Ratepayers

Instead of mandating access to the actual data, a last remedy may be the most creative of all. In this scenario, states or PUCs would require utilities to share the benefits of its data monopoly with customers rather than the actual data. Given the large number of states that are silent on data practices—and despite the strong arguments against extending monopoly power to data—the monopoly that utilities assume over their data may nevertheless persist in many states. If this occurs without any remedy, the utility may reap all the benefits of this data, even those external to the benefits needed to enhance grid operations. This Part briefly explores the rationale for such a remedy, as well as implementation options.

a.     Rationale for Sharing Benefits of the Data

A few powerful arguments exist to support sharing the benefits of utility data with customers. First, customers are important financial backers of the very means of gathering data. Public utility commissions across the country have approved the installation of smart meters and AMI to gather massive amounts of previously unavailable granular data.[370] The costs of these investments are then passed on to the ratepayer while the utility enjoys a healthy rate of return.[371] Therefore, the utility’s duty to its ratepayers is bolstered by the fact that many jurisdictions used ratepayer money to roll out smart meters[372]—meters that have led to substantial benefits to the utility. Importantly, many of these utilities have failed to demonstrate the promised benefits for ratepayers from these ratepayer-funded installations. Baltimore Gas and Electric is one exception. After the Maryland Public Service Commission rejected its request to invest in smart meters, this utility was required to provide a bill credit to customers for decreasing peak usage.[373]

Second, unlike deciding to voluntarily share information with particular internet browsers or social media platforms,[374] customers are extremely limited in their choices with respect to utilities. As an initial matter, customers rarely have a choice in the utility that provides them with electricity.[375] In fact, only fifteen states allow customers any choice in electric utility, and that is limited to their generation provider.[376] Even in those areas, if no utility provider is selected, any new customer in a utility’s territory will be served by the default incumbent electricity provider.[377] More importantly, customers also do not have a choice in handing over their data to their utility.[378] Therefore, the illusion of “choice” that drives many data transfers outside of the energy context is completely absent from the utility-ratepayer dynamic since customers subject to a monopoly distribution utility cannot exercise any effective choice in the disclosure of their data when the only alternative is to go without heat, gas, or electricity.

Such unilateral data grabs by the utilities can lead to information asymmetries—substantial differences between the information available to the companies who collect data and the information to the consumers who provide the data.[379] This asymmetric information flow results in consumers being unable to make informed decisions about the use of their data. Consumers do not know what information companies have on them and thus cannot control the fate of the data they provide.[380] Even as data disclosure laws begin to flourish, most consumers do not invoke their rights under legislation because they are unaware which companies hold their data and what data they hold, or they simply do not care.[381] Even something as mundane as tracking one’s reproductive cycle now unwittingly places women in the crosshairs of Dobbs v. Jackson Women’s Health and subsequent state restrictions on abortion, rendering such information not only personal but also potentially criminal.[382] Whoever holds, controls, and makes this data available wields enormous power beyond what may be obvious to the average user.[383]

Third, even when data is shared, few of the direct benefits of consumer data collection trickle down to individual customers.[384] Many customers lack sophistication or access to the various technologies that allow them to act on this knowledge.[385] There are also difficulties in parsing out the individual benefits that utilities reap from this data as opposed to the societal benefits that utilities may bestow. For instance, although some indirect benefits may be seen, customers rarely see any direct financial benefit from their utilities.[386] Utilities and advocates tout the advantages of enhancing data access, including cost savings, coordination, and more.[387] Some even inveigle customers to hand over more of their data under the allure of cost savings.[388] A few utilities already share data, including monthly usage, in an effort to shape behavioral change, but they only offer limited empirical data to demonstrate its beneficial impact.[389] Additionally, such benefits seem to only benefit the utility shareholders. At a 2018 conference, for instance, Duke Energy CIO Chris Heck emphasized that data processed by OSIsoft saved Duke Energy over $130 million by predicting transformer failures before they occurred.[390] That same year, however, Duke Energy increased the average residential rate of electricity in South Carolina by 6.3 percent.[391] It is difficult to draw a straight connection between such events, as the rate increase may be due to grid investments in other areas. Alternatively, the rate could have been raised by much more than 6.3 percent but for the use of data predictions on transformers.

In at least some circumstances, the realized benefits seem to reside solely with the utility[392] or with third-party entities.[393] Since the electricity sector started to use big data, I have yet to identify an example of a utility advertising a rate reduction due to their use of customer data.[394] Even progressive companies like Arcadia[395] have engaged with utilities and customers to obtain data for use in analytics for other private corporations,[396] but it is unclear how consumers can benefit without time-of-use policies in place in their jurisdictions.[397] Such technological innovations may be benefiting large corporate entities, with little benefits reaching the consumer.[398]

Lastly, as others have argued, “public interest” obligations on utilities should include efforts to enhance energy equity.[399] The U.S. Energy Information Administration has estimated that almost one third of all Americans experience energy insecurity and worry about paying their bills.[400] The rising prices of electricity[401] and the growing energy insecurity of Americans can provide additional impetus for policies where utilities pass on more of their data-related benefits to their ratepayers.[402] Tangible financial credits or rebates discussed below could satisfy these important equity considerations and even assist those who struggle to pay for their essential services.[403]

b.      Implementation Through a “Data Duty”

As a result of these inequities between a utility and its ratepayers, the state laws and regulations that some refer to as the regulatory compact should be updated to include obligations associated with the use of data obtained, specifically a “data duty.”[404] As discussed earlier, unlike public regulated monopolies, private regulated monopolies are “clothed with a public interest.”[405] The state may therefore have a little more leverage to use against these private companies. By gathering evidence that access to data can facilitate state environmental goals, for instance, regulators may be able to leverage the regulatory compact that exists between the state and the private entities to enhance data equality. Consistent with this logic, just as utilities are expected to develop their generation, transmission, and distribution resources to serve their customers,[406] utilities should only be allowed to develop their data in ways that serves their customers.

As the data was acquired by utilities in the course of their public obligations, one can similarly argue that the data should come with conditions attached to its use. If a regulated monopoly wants to use public data for private gains, a guiding principle should demand that the individuals sharing their data reap a direct benefit commensurate with that of their corporate utility analogues.[407]

The justification for this remedy stems from an argument that regulated monopolies should not be allowed to benefit from the data derived as part of their public duties without providing a pass-through benefit for the ratepayers in their jurisdiction. These benefit-sharing requirements could be modeled after data compensation laws in the federal pesticide registration laws, which compensate the private company for the costs of collecting and managing the data in exchange for allowing competitors to use and rely on this energy data.[408] Instead of requiring pooling of the data itself, this more indirect remedy would require a utility to share the benefits of that data with their ratepayers through (1) direct compensation or (2) indirect compensation. Both options would help to address the growing inequities that exist for the multitude of ratepayers struggling to make ends meet and include customers as partners in the move toward a cleaner electric grid.  

Direct Compensation to Ratepayers. Scholars have long argued for monetary benefits to pass through to customers instead of being distributed to shareholders.[409] A number of creative, modern pricing reforms have been piloted across the country to address misaligned utility business models.[410] The first option involves compensating the public for use of its data through direct payments or rebates. Such tools are not foreign to utility pricing.[411] For example, San Diego Gas and Electric allows residential customers to receive financial incentives and bill credits by enrolling in energy savings programs aimed at reducing consumption at peak times.[412] Yet quantifying the benefits enjoyed by the utility is notoriously difficult. Still, even approximations would serve to value the customer data and demonstrate to customers that they are part of a joint effort with utilities.

Indirect Facilitation of Cost Savings to Ratepayer. Besides a direct payment to a utility customer, a second option would be for the utility to facilitate cost savings for the customer. The National Association of Regulatory Utility Commissioners (NARUC) commissioned a study that identified how customers can benefit from enhanced energy data.[413] The results suggest that customers can reduce their own electricity bills by adjusting their behavior based on the data provided.[414] Unfortunately, allowing customers to take advantage of their own data requires a level of sophistication that not all ratepayers have and a regulatory framework.[415] Even sophisticated ratepayers operating within a favorable regulatory framework may still be unable to take advantage of their data due to the lack of a pricing infrastructure.[416] Regardless, the second option provides an opportunity for utilities to satisfy their public interest obligations by facilitating cost savings through lower electricity bills.

Utilities can enact the second option through a number of mechanisms. First, a utility can help customers actualize the benefits of having access to data by sharing its data diagnostics with the public alongside resources for customer education and training. Utilities have instituted such training and educational programs to address other challenges, such as increasing access to electric vehicles and encouraging the use of sustainable energy in low-income neighborhoods.[417] Here, too, a state or utility could embark on a comprehensive educational campaign to enhance the sophistication of ratepayers. Such efforts would need to be coupled with corresponding pricing reforms that allow customers to take greater control of their own energy profiles.

A second mechanism could be the creation of a special reduced rate category, or a rate case with the PUC that decreases customer rates to reflect the value of the cost savings that the utility enjoys from the customer data. In some situations, PUCs have imposed a special reduced rate for those in need.[418] A utility may similarly be able to allow a reduced rate for those who provide proof of need. In other cases, PUCs have granted requests for a rate reduction.[419] Either strategy could be instituted for customers who share their data, being cautious about inadvertently creating incentives for individuals to “sell” their privacy for cost savings.[420]

In sum, antitrust law may provide an underappreciated lever to achieve more energy data sharing. Because of the high stakes associated with Sherman Act liability—including divestment and damages—elimination of state action immunity may be sufficient to motivate utilities to engage in some form of good faith data practices. Knowing that others may use their data, utilities may be encouraged to develop innovative ways to enhance customer experience and work towards a cleaner grid. To avoid federal antitrust liability, utilities may engage in voluntary risk management practices that enhance competition for energy data.

If private utilities do not voluntarily take the initiative, states and regulators should stand ready to step in to require actions that enhance competition, consumer welfare, and environmental goals. At the very least, each state should provide an express preference for whether utility data practices are to be subject to competitive market pressures, or instead be insulated from antitrust laws with a sanctioned monopoly. Although sharing the data or the benefits is no guarantee that these goals will be achieved, rejecting state action immunity creates an underappreciated pathway to increasing output, improving product quality, and spurring innovation—the goals originally envisioned by antitrust law.[421]

Conclusion

The tensions between privacy and competition are real. Utilities control access to our most vital needs.[422] Whereas most scholars in this space argue for transparency and public access to the private data, they have failed to develop workable approaches to do so. This Article takes a much more realistic approach. It argues against extending state action immunity over a utility’s energy data practices, demonstrating why immunity fails both doctrinally and theoretically. It acknowledges that the threat of antitrust liability may be necessary to motivate utilities to engage in risk management activities to avoid antitrust liability, demonstrate their willingness to release the stranglehold they currently have on energy data, or motivate legislatures to more clearly express a desire for an anticompetitive data marketplace.

How energy utilities manage data can have broader implications for other public utilities, modern interpretations of state action immunity, energy law, and antitrust law more generally. After exploring the viability of last-resort antitrust remedies such as pooling and line of business restrictions, this Article finds regulatory remedies more appropriate for electric utilities. It sets forth both data sharing and a new customer-focused data duty as possible mechanisms to enhance consumer (ratepayer) welfare in this space. Whether performed voluntarily or under mandate, such actions would hopefully come with conditions attached to the utility’s use that will serve to facilitate innovation and enhance competition, leading to efficiency and environmental benefits for not only ratepayers but society at large.

Appendix A: State Electric Utility Data Access Laws

Please see the PDF version of the article for access to the Appendix. [423]

Copyright © 2024 Amy L. Stein, Associate Dean for Curriculum and Cone Wagner Professor of Law, University of Florida Levin College of Law. I am grateful to Danny Sokol, Bill Page, Ari Peskoe, James Coleman, Felix Mormann, William Boyd, Josh Macey, Heather Payne, David Spence, Sharon Jacobs, Shelley Welton, Sara Bensley, Erik Hovenkamp, my colleagues at the Berkeley/Penn Energy Workshop and the SMU Law Faculty Workshop, Texas A&M Environmental Workshop, and the participants of the Stanford Law School Environmental Law Workshop for their valuable feedback; and to my research assistants, Jeffrey Katz, Jenna Cliatt, Jordan Mitchell, Jacob Wright, and Erica Clements.

           [1].     See, e.g., United States v. Google, No. 20-cv-3010 (APM), 2024 WL 3647498, *3 (D.D.C. Aug. 5, 2024) (holding that Google violated Section 2 of the Sherman Act with exclusive distribution agreements for general search services and advertising); Complaint at 1–2, Fed. Trade Comm’n v. Amazon, No. 114-1495 (W.D. Wash. Sept. 26, 2023) (accusing Amazon of exerting monopoly power in the e-commerce market to overcharge customers and sellers on the platform); Complaint, United States v. Google, No. 1-108 (E.D. Va. Jan. 24, 2023) (alleging that Google systematically and deliberately monopolized digital advertising technologies to the detriment of other digital publishers); Fed. Trade Comm’n v. Meta Platforms, Inc., No. 20-3590 (D.D.C. Apr. 26, 2023) (claiming that Meta Platforms holds a monopoly over social networks following its anticompetitive acquisitions of WhatsApp and Instagram); Fed. Trade Comm’n v. Facebook, Inc., 581 F. Supp. 3d 34, 43, 51 (D.D.C. 2022) (alleging Facebook maintained an impermissible monopoly and engaged in anticompetitive conduct); Klein v. Facebook, Inc., 580 F. Supp. 3d 743, 760 (N.D. Cal. 2022) (filing consolidated antitrust claims against Facebook); Reveal Chat Holdco, LLC v. Facebook, Inc., 471 F. Supp. 3d 981, 987 (N.D. Cal. 2020) (granting Facebook’s motion to dismiss class action antitrust suit); In re Google Digit. Advert. Antitrust Litig., 627 F. Supp. 3d 346, 358–59 (S.D.N.Y. Sept. 13, 2022) (claiming Google’s digital advertising practices violated Sherman Act); Reilly v. Apple Inc., 578 F. Supp. 3d 1098, 1104 (N.D. Cal. 2022) (alleging that Apple maintained a monopoly over the iOS App distribution market).

           [2].     See, e.g., Complaint at 1–2, United States. v. Google, No. 1:23-cv-00108 (E.D. Va. Jan. 24, 2023) (alleging that Google monopolizes key digital advertising technologies that website publishers depend on to sell ads and that advertisers rely on to buy ads and reach potential customers); Klein, 580 F. Supp. 3d at 761 (alleging that Facebook monopolizes social media advertising); In re Google Digit. Advert. Antitrust Litig., 627 F. Supp. 3d at 359 (alleging that Google monopolizes various markets related to online display ads and unlawfully uses its market power to tie sales of one distinct product to another).

           [3].     See infra Part I.C.

           [4].     Investor-owned Utilities Serve 72% of U.S. Electricity Customers in 2017, U.S. Energy Info. Admin. (Aug. 15, 2019), https://www.eia.gov/todayinenergy/detail.php?id=40913 [https://perma.cc/BV6Q-82LH] [hereinafter Energy Info. Admin., Investor-owned Utilities].

           [5].     Verizon Commc’ns. Inc. v. Trinko, 540 U.S. 398 (2004).

           [6].     Cnty. of Stanislaus v. Pac. Gas & Elec. Co., No. CV-F-93-5866-OWW, 1995 U.S. Dist. LEXIS 21411 (E.D. Cal. 1995).

           [7].     Ellis v. Salt River Project Agric. Improvement & Power Dist., 24 F.4th 1262 (9th Cir. 2022).

           [8].     See Heather Payne, Private (Utility) Regulators, 50 Env’t L. 999, 1005 (2020).

           [9].     See, e.g., Daniel J. Solove & Woodrow Hartzog, Unifying Privacy and Data Security, in Breached! Why Data Security Law Fails and How to Improve it (2022) (making no reference to “utility” or “utilities”); Danielle Keats Citron & Daniel J. Solove, Privacy Harms, 102 B.U. L. Rev. 793 (2022) (making no reference to “utility” or “utilities”); Neil M. Richards & Jonathan H. King, Big Data Ethics, 49 Wake Forest L. Rev. 393 (2014) (making no reference to “utility” or “utilities”); Paul M. Schwartz, Property, Privacy, and Personal Data, 117 Harv. L. Rev. 2056 (2004) (making no reference to “utility” or “utilities”). But see Cal. Pub. Util. Code § 8380 (West 2021) (requiring best data management practices for California utilities).

         [10].     See, e.g., Erik Hovenkamp, The Antitrust Duty to Deal in the Era of Big Tech, 131 Yale L.J. 1483, 1488–89 (2022) [hereinafter E. Hovenkamp: Antitrust Duty to Deal] (noting increased antitrust scholarship on practices of large tech firms that mimic those of companies such as Apple and Amazon); Rebecca Haw Allensworth, Antitrust’s High-Tech Exceptionalism, 130 Yale L.J. F. 588, 590 (2021) (arguing that antitrust law should address the market power of accumulated by big tech firms); Herbert Hovenkamp, Antitrust and Platform Monopoly, 130 Yale L.J. 1952, 1956 (2021) [hereinafter H. Hovenkamp: Antitrust and Platform Monopoly] (arguing that antitrust law should govern large tech platforms where applicable).

         [11].     See, e.g., Barbara J. Evans, Power to the People: Data Citizens in the Age of Precision Medicine, 19 Vand. J. Ent. & Tech. L. 243, 264 (2018) (noting laws that prioritize public health over individual privacy concerns and suggesting that data science need not come at the expense of privacy); David Deming, Balancing Privacy with Data Sharing for the Public Good, N.Y. Times (Feb. 19, 2021), https://www.nytimes.com/2021/02/19/business/privacy-open-data-public.html [https://perma.cc/AF2N-2RHQ]; see also Matthew B. Kugler & Meredith Hurley, Protecting Energy Privacy Across the Public/Private Divide, 72 Fla. L. Rev. 451, 511 (2020) (discussing the massive amounts of data that utilities accumulate with the rise of integrated smart homes and proposing a regulatory framework that would allow utilities to share anonymized aggregate data); Benjamin L. Ruddell, Dan Cheng, Eric Daniel Fournier, Stephanie Pincetl, Caryn Potter & Richard Rushforth, Guidance on the Usability-Privacy Tradeoff for Utility Customer Data Aggregation, 67 Utils. Policy 1, 4 (2020) (employing a statistical analysis to account for vulnerable groups when balancing privacy concerns with the sustainability and conservation goals of utility data sharing).

         [12].     Michael Wara, Competition at the Grid Edge: Innovation and Antitrust Law in the Electricity Sector, 25 N.Y.U. Env’t L.J. 176 (2017).

         [13].     Although the focus of this analysis is on the antitrust aspects of utility data practices, a brief discussion of the unavoidable privacy issues can be found infra Part III.B.2.a.

         [14].     See supra note 11 and accompanying text.

         [15].     See, e.g., Complaint of OhmConnect, Inc. against Southern California Edison Company for Data Failures at 8, OhmConnect, Inc. v. S. Cal. Edison Co., No. C1903005 (Cal. Pub. Util. Comm’n Mar. 8, 2019) (documenting Southern California Edison failing to share data requested by customers). Direct examples of utilities hoarding data are difficult to obtain, but ancillary evidence suggests energy data is severely underutilized. One study estimates that 97 percent of smart meters are not providing customer benefits. Herman K. Trabish, 97% of Smart Meters Failed to Provide Customer Benefits. Can $3B in New Funding Change That?, Util. Dive (Oct. 5, 2022), https://www.utilitydive.com/news/97-of-smart-meters-fail-to-provide-promised-customer-benefits-can-3b-in/632662/ [https://perma.cc/SCR3-5VWA]. Another survey suggests that less than one third of utilities have a formal data strategy. Trey Thornton, Why the Future of Power and Utilities Depends on Data, Ernst & Young (Dec. 2, 2022), https://www.ey.com/en_us/power-utilities/why-the-future-of-power-and-utilities-depends-on-data [https://perma.cc/H4KP-R6UL].

         [16].     ComEd, a major utility in Illinois, offers anonymous data for sale in bundles based on ZIP code for $900 and $1300. Anonymous Data FAQs, Commonwealth Edison Co., https://www.comed.com/smart-energy/innovation-technology/anonymous-data-service/anonymous-data-faqs [https://perma.cc/8K8Z-SHDP] (last visited Oct. 27, 2023).

         [17].     OSIsoft asset analytics helped Duke save $130 million on transformer maintenance and helped DTE Electric reduce outages by 6.6 million minutes per year. Further, Franklin Energy used its demand response software NGAGE to help NYC Consolidated Edison’s reduce the cost of system upgrades from $1.2 billion to $200 million with non-wire alternatives. Herman K. Trabish, The Biggest Numbers Game in the Power Sector: Data Analytics and the Utility Community of the Future, Util. Dive (Mar. 25, 2019), https://www.utilitydive.com/news/the-biggest-numbers-game-in-the-power-sector-data-analytics-and-the-utilit/550660/ [https://perma.cc/LA5F-SGNY].

         [18].     See Kugler & Hurley, supra note 11, at 511–14 (recognizing the potential of utility data as an important tool to decarbonize and develop the smart grid and combat climate change); Alexandra Klass & Elizabeth Wilson, Remaking Energy: The Critical Role of Energy Consumption Data, 104 Calif. L. Rev. 1095, 1100–02 (2016) (demonstrating how electricity consumption data can be shared to advance decarbonization goals).

         [19].     See Shelley Welton & Joel B. Eisen, Clean Energy Justice: Charting an Emerging Agenda, 43 Harv. Env’t. L. Rev. 307, 339–40 (2019) (using data on consumer use of new technologies such as net metering and community solar to evaluate how states may address clean energy justice concerns).

         [20].     Pauline Henriot, Unleashing the Benefits of Data for Energy Systems, Int’l Energy Agency (May 12, 2023), https://www.iea.org/commentaries/unleashing-the-benefits-of-data-for-energy-systems [https://perma.cc/N6UW-5V4U] (discussing how leveraging data offers significant gains to power systems and energy companies by helping them foresee grid tensions and providing insights on consumption patterns).

         [21].     See Establish Data Sharing Relationships as Early as Possible, U.S. Dep’t of Energy, https://rpsc.energy.gov/tips-for-success/establish-data-sharing-relationships-early-possible [https://perma.cc/FJ4K-MFV8] (last visited Nov. 6, 2023) (noting that the South East Energy Alliance struggled to obtain utility bill data because utilities did not have the proper resources to do so, or they “would only release data for a fee” despite homeowner consent forms); Catherine Lane, Alabama Allows Largest Utility to Increase ‘Solar Tax’ – Guts State Solar Industry, SolarReviews, https://www.solarreviews.com/blog/alabama-power-solar-charge [https://perma.cc/A99J-DPGR] (describing how utilities like Alabama Power often hold significant social, economic, and political power in their state, illustrating some of the many power dynamics favoring incumbent utilities); John Gartner, EV Market Slowed by the Utility Data Disconnect, Ctr. For Sustainable Energy (Feb. 6, 2023), https://energycenter.org/thought-leadership/blog/ev-market-slowed-utility-data-disconnect [https://perma.cc/XL9H-5755] (identifying that electric vehicle (EV) fast charger installations are currently limited by utilities’ reluctance to share data about locations on the grid that can handle additional load).

         [22].     See infra Part III.A.1.

         [23].     See Werner Troesken, Regime Change and Corruption: A History of Public Utility Regulation, in Corruption and Reform: Lessons from America’s Economic History 259–63 (Edward L. Glaeser & Claudia Goldin eds., 2006).

         [24].     See Payne, supra note 8, at 1005 (stating that the rationale for giving utilities a monopoly was for a public purpose).

         [25].     See, e.g., Jerry Ellig, Retail Electric Competition and Natural Monopoly: The Shocking Truth 2 (Geo. Wash. Univ. Regul. Stud. Ctr., Working Paper, May 21, 2020) (“Regulated monopoly remains the dominant paradigm for electricity retailing in the United States.”).

         [26].     U.S. Energy Info. Admin., Investor-owned Utilities, supra note 4.

         [27].     Proprietors of Charles River Bridge v. Proprietors of Warren Bridge, 36 U.S. 420, 422 (1837).

         [28].     Munn v. Illinois, 94 U.S. 113, 114 (1876); see also Charles C. Read & Marc T. Campopiano, Climate Change, the Regulatory Compact, and Public Utility Rights, 60 Infrastructure 1, 9 (2021).

         [29].     Jersey Cent. Power & Light Co. v. Fed. Energy Regul. Comm’n, 810 F.2d 1168, 1189 (D.C. Cir. 1987) (Starr, J., concurring) (“The utility business represents a compact of sorts; a monopoly on service in a particular geographical area . . . is granted to the utility in exchange for a regime of intensive regulation, including price regulation, quite alien to the free market.”); see Payne, supra note 8, at 1001; Jim Rossi, Universal Service in Competitive Retail Electric Power Markets: Whither the Duty to Serve?, 21 Energy L.J. 27, 30 (2000). But see Ari Peskoe, Utility Regulation Should Not Be Characterized as a “Regulatory Compact,” Harv. Env’t Pol’y Initiative (2016), http://eelp.law.harvard.edu/wp-content/uploads/Harvard-Environmental-Policy-Initiative-QER-Comment-There-Is-No-Regulatory-Compact.pdf [https://perma.cc/3PK6-XWSA].

         [30].     See, e.g., An Overview of PUCs for State Environment and Energy Officials, U.S. Env’t Prot. Agency (May 20, 2010), https://www.epa.gov/sites/default/files/2016-03/documents/background_paper.pdf [https://perma.cc/QK53-9SA7] (“As a general rule, utility commissions are charged with assuring that utilities provide reasonable, adequate and efficient service to customers at just and reasonable prices.”).

         [31].     Emily Hammond & David B. Spence, The Regulatory Contract in the Marketplace, 69 Vand. L. Rev. 141, 142–44 (2016); Shelley Welton, Public Energy, 92 N.Y.U. L. Rev. 267, 313–14 (2017); Peskoe, supra note 29.

         [32].     Mandates Versus Movement: State Public Service Commissions and Their Evolving Power Over Our Energy Sources, 135 Harv. L. Rev. 1614, 1619 (2022) (citing a 910-percent rate of return on equity); see S.C. Pub. Serv. Comm’n, A Lesson on Return on Equity (ROE) and How Electric Utilities Make Money, https://dms.psc.sc.gov/Attachments/Matter/5f64b1b3-d2bc-4b20-abb7-6e36ed1a220f [https://perma.cc/YMM6-DXJ2] (“In the U.S., utility company average ROE is 10.13%.”).

         [33].     David Roberts, Power Utilities are Built for the 20th Century. That’s Why They’re Flailing in the 21st, Vox (Sept. 9, 2015), https://www.vox.com/2015/9/9/9287719/utilities-monopoly [https://perma.cc/F6GK-L6HQ]; Jonas J. Monast, Electricity Competition and the Public Good: Rethinking Markets and Monopolies, 90 U. Colo. L. Rev. 667, 674–76 (2019); Carl Pechman, Regulation and the Monopoly Status of the Electric Distribution Utility, Nat’l Regul. Rsch. Inst. 4–5 (June 2022), https://pubs.naruc.org/pub/B284311B-1866-DAAC-99FB-C52B7A570087 [https://perma.cc/6WQ8-8DGP].

         [34].     See generally Robert Michaels, Electricity and Its Regulation, Econlib https://www.econlib.org/library/Enc/ElectricityandItsRegulation.html [https://perma.cc/TJH9-EDFZ] (last visited Nov. 6, 2023) (providing an overview of the development of electricity ownership structure).

         [35].     See U.S. Electricity Grid & Markets, U.S. Env’t Prot. Agency, https://www.epa.gov/green-power-markets/us-electricity-grid-markets [https://perma.cc/8UFA-SKW5] (last visited Nov. 6, 2023); Kathryne Cleary & Karen Palmer, US Electricity Markets 101, Res. for the Future (Mar. 17, 2022), https://www.rff.org/publications/explainers/us-electricity-markets-101/ [https://perma.cc/2EA7-QRQS] (last visited Oct. 24, 2023) (explaining that despite the success of competitive generation, utilities cannot “cost-effectively create their own power line infrastructure”); The Federal Power Act and Electricity Markets, Cong. Rsch. Serv. (Mar. 10, 2017), https://crsreports.congress.gov/product/pdf/R/R44783 [https://perma.cc/Q49W-JR9V].

         [36].     Pub. Util. Regul. Pol’ys Act, 16 U.S.C. §§ 2601, 824a (encouraging competition by requiring utilities to purchase energy produced by cogeneration and renewables from “Qualified Facilities” at the same rate it would have cost the utility to generate the energy themselves).

         [37].     Energy Pol’y Act of 2005, Pub. L. No. 109-58, 119 Stat. 594 (providing tax incentives for small-scale and distributed domestic energy production including wind and solar, as well as committing resources to analyzing competition in the wholesale and retail energy markets to increase total energy production and diversify U.S. energy sources).

         [38].     See, e.g., Promoting Wholesale Competition, FERC Order No. 888, 75 FERC ¶ 61,080 (Apr. 26, 1996) (opening up transmission line access); Open Access Same-Time Information System, FERC Order. No. 889, 75 FERC ¶ 61,078 (Apr. 26, 1996) (opening up transmission lines); FERC Order No. 2222, 172 FERC ¶ 61,247 (Sept. 17, 2020) (opening up wholesale markets to demand response).

         [39].     Ari Peskoe, Is the Utility Transmission Syndicate Forever?, 42 Energy L.J. 1, 2, 26 (2021); Kristen van de Biezenbos, Against Transmission Monopolies, 101 Wash. U. L. Rev. 69, 73; see also Complaint of Salsa Solar Energy, LLM and Towner Wind Energy III LLC at 25–26, No. EL24-__-000 (Fed. Energy Regul. Comm’n Dec. 22, 2023), https://elibrary.ferc.gov/eLibrary/filedownload?fileid=CE2AD405-3FA8-C830-B4C5-8CA684700000 [https://perma.cc/S54A-V3YA] (“Put simply, it very much looks like PSCo [the Public Service Utility of Colorado] is trying to advantage its own generation via its control of transmission and the interconnection process.”).

         [40].     See, e.g., Thomas Philbeck & Nicholas Davis, The Fourth Industrial Revolution: Shaping a New Era, 72 J. Int’l Aff. 17, 17–18 (2019); Klaus Schwab, The Fourth Industrial Revolution 12–13 (2016).

         [41].     Schwab, supra note 40, at 11.

         [42].     See, e.g., Lina M. Kahn, Amazon’s Antitrust Paradox, 126 Yale L.J. 710, 780 (2017) (arguing that Amazon’s data dominance exacerbates the risks of anticompetitive effects from its vertical market control); Mason Marks, Biosupremacy: Big Data, Antitrust, and Monopolistic Power Over Human Behavior, 55 UC Davis L. Rev. 513, 518–19 (2021) (suggesting that the major tech companies have created data monopolies with the intent of controlling human behavior); Marco Gambaro, Big Data Competition and Market Power, 2 Mkt. & Competition L. Rev. 99, 114 (2018) (suggesting that a dominant position obtained from collection and processing of big data can lead to price discrimination and degradation of services); Annie Brett, Information as Power: Democratizing Environmental Data, 2022 Utah L. Rev. 127, 147 (2022) (arguing that federal agencies’ holding onto environmental data has hurt conservation efforts); Andrei Hagiu & Julian Wright, When Data Creates Competitive Advantage and When it Doesn’t, Harv. Bus. Rev. Mag. (Jan. 2020) (describing how proprietary data and data facilitating product improvements can create competitive advantages); Bridget A. Fahey, Data Federalism, 135 Harv. L. Rev. 1007, 1009 (2022) (describing how the power of controlling data applies to public, as well as private entities).

         [43].     For example, Google’s $3.2 billion purchase of Nest in 2014 “was less about a device sales play . . . but more about a data play.” See Indigo Advisory Group, Monetizing Utility Data — The ‘Utility Data as a Service’ Opportunity, Medium (Jan. 3, 2017), https://medium.com/@indigoadvisory/monetizing-utility-data-the-utility-data-as-a-service-opportunity-e73e2aeaa650 [https://perma.cc/8H3W-P4Y2]; But see generally U.S. General Services Administration, Data.gov, www.data.gov [https://perma.cc/2P9M-KWXN] (last visited Oct. 27, 2023) (the U.S. Government’s open data website where over 200,000 datasets are compiled and shared across state and federal agencies).

         [44].     See, e.g., Pamela Vagata & Kevin Wilfong, Scaling the Facebook Data Warehouse to 300 PB, Eng’g at Meta (Apr. 10, 2014), https://engineering.fb.com/2014/04/10/core-infra/scaling-the-facebook-data-warehouse-to-300-pb/ [https://perma.cc/G6A6-6ZJN] (stating that the company was receiving 600 terabytes of data a day to its Hive data warehouse); Maddy Osman, Wild and Interesting Facebook Statistics, Kinsta (Sept. 22, 2023), https://kinsta.com/blog/facebook-statistics/ [https://perma.cc/36WP-JV73] (stating Facebook generated four petabytes of data per day in 2020); Dan Price, Infographics: How Much Data is Produced Every Day, CloudTweak, https://cloudtweaks.com/2015/03/how-much-data-is-produced-every-day/ [https://perma.cc/95YL-NZ3S] (estimating Amazon has one exabyte of data stored on their servers); Greg Petro, Amazon’s Acquisition of Whole Foods is About Two Things: Data and Product, Forbes (Aug. 2, 2017), https://www.forbes.com/sites/gregpetro/2017/08/02/amazons-acquisition-of-whole-foods-is-about-two-things-data-and-product/?sh=3c75d79ba808 [https://perma.cc/5WPE-5AU6] (hypothesizing that Amazon’s primary reason for its Whole Foods acquisition was to acquire massive amounts of consumer data to better understand its consumers’ needs); Glen Sears, GDPR Data Exports Reveal Spotify Tracks Absolutely Everything About You, Dance Music N.W. (Aug. 3, 2018), http://dancemusicnw.com/spotify-gdpr-data-exports-user-tracking/ [https://perma.cc/EP2A-7EH8] (reporting the extent of consumer data that Spotify collects from listeners, including the brand of their headphones, volume changes, and more).

         [45].     See, e.g., Sears, supra note 44; Susanne Barth & Menno D.T. de Jong, The Privacy Paradox, 34 Telematics & Informatics 1038, 1039 (2017), https://www.sciencedirect.com/science/article/pii/S0736585317302022 [https://perma.cc/X82V-BMG9] (noting the discrepancy between users’ attitudes in favor of privacy and actual behavior); Noam Kolt, Return on Data: Personalizing Consumer Guidance in Data Exchanges, 38 Yale L. & Pol’y Rev. 77, 78–79 (2019) (explaining the increased recognition that users trade their data to use free or low-cost online platforms); Vikram Rao & Kruttika Dwivedi, To Share or Not to Share, Deloitte Insights (Sept. 5, 2017), https://www2.deloitte.com/us/en/insights/industry/retail-distribution/sharing-personal-information-consumer-privacy-concerns.html [https://perma.cc/8GU8-8VS5] (finding that consumers have become more willing to share certain data with companies if they perceive some return benefit).

         [46].     Exec. Off. of the Pres., Big Data: Seizing Opportunities, Preserving Values 51 (May 2014), https://obamawhitehouse.archives.gov/sites/default/files/docs/big_data_privacy_report_may_1_2014.pdf [https://perma.cc/2AVV-Y2PQ] [hereinafter Exec. Off. of the Pres.: Big Data] (“The average consumer is unlikely to be aware of the range of data being collected or held or even to know who holds it.”); see Swish Goswami, The Rising Concern Around Consumer Data and Privacy, Forbes (Dec. 14. 2020), https://www.forbes.com/sites/forbestechcouncil/2020/12/14/the-rising-concern-around-consumer-data-and-privacy/?sh=58782af1487e [https://perma.cc/U95E-SKVB] (“Consumers previously did not fully grasp the amount of their personal data that companies were collecting.”).

         [47].     See, e.g., Katie Tarasov, Amazon Dominates the $113 Billion Smart Home Market – Here’s How it Uses the Data it Collects, CNBC (Sept. 28, 2022), https://www.cnbc.com/2022/09/28/amazon-dominates-the-smart-home-now-privacy-groups-oppose-irobot-deal.html [https://perma.cc/GB7E-UW6J] (discussing the privacy and data collection implications of Amazon’s home smart devices such as Echo, Alexa, and iRobot); Jeff Plungis, Who Owns the Data Your Car Collects?, Consumer Rep. (May 2, 2018), https://www.consumerreports.org/automotive-technology/who-owns-the-data-your-car-collects/ [https://perma.cc/T8UW-22TK] (discussing the massive amounts of data that the automobile industry collects from technology inside of cars).

         [48].     See, e.g., Nir Kshetri, Big Impact on Privacy, Security and Consumer Welfare, 38 Telecomms. Pol’y 1134, 1134 (2014) (highlighting consumers’ growing concern with “high-velocity data” collection, such as GPS data, cookies, click-stream, and social media usage, which can have dangerous consequences if obtained by exploitative third-party companies); Kashmir Hill, The Secretive Company That Might End Privacy as we Know It, N.Y. Times (Jan. 18, 2020), https://www.nytimes.com/2020/01/18/technology/clearview-privacy-facial-recognition.html [https://perma.cc/6DQD-RAL8] (explaining Clearview’s scraping the Internet for billions of facial images); Viktoria H.S.E. Robertson, Excessive Data Collection: Privacy Considerations and Abuse of Dominance in the Era of Big Data, 57 Common Mkt. L. Rev. 1, 13 (Inst. of Corp. & Int’l Comm. L., Working Paper, 2020) (discussing potential drawbacks and legal implications of excessive data collection).

         [49].     See, e.g., Regulation (EU) 2016/679 of the European Parliament and of the Council of 27 April 2016 on the Protection of Natural Persons with Regard to the Processing of Personal Data and on the Free Movement of Such Data and Repealing Directive 95/46/EC (General Data Protection Regulation), art. 4(2), 2016 OJ (L 119) 33 (EU) [hereinafter GDPR] (data retention rules that require any personal data that is collected or processed to be kept only for as long as data is required to achieve the purpose for which the information was collected); Alexander Tsesis, Data Subjects’ Privacy Rights: Regulation of Personal Data Retention and Erasure, 90 U. Colo. L. Rev. 593, 603, 619–20 (2019) (analyzing First Amendment jurisprudence to explain the contrast between the United States’s data retention policies, which allow companies to retain an unlimited amount of consumer data indefinitely, with the European Union’s data retention policies, which are centered around safeguarding consumer data privacy).

         [50].     See, e.g., Matthew Rosenberg, Cambridge Analytica and Facebook: The Scandal and the Fallout So Far, N.Y. Times (Apr. 4, 2018), https://www.nytimes.com/2018/04/04/us/politics/cambridge-analytica-scandal-fallout.html [https://perma.cc/8ABS-PSVN] (discussing Facebook’s improper sharing of millions of customers’ data with a conservative data company for use in voter profiling); Dan Milmo, Twitter Fined $150M for Handing Users’ Contact Details to Advertisers, Guardian (May 26, 2022), https://www.theguardian.com/technology/2022/may/25/twitter-user-data-advertising-settlement [https://perma.cc/A9EP-VGKC] (discussing how Twitter gave advertisers personal information collected for security purposes over a six-year period); Devin Coldewey, Uber Fined in Settlement with NY Over ‘God View’ Tracking, NBC News (Jan. 6, 2016), https://www.nbcnews.com/tech/tech-news/uber-fined-settlement-ny-over-god-view-tracking-n491706 [https://perma.cc/A6F7-23J4] (discussing how Uber was fined for using a feature that allowed employees to see every rider’s current location and personal information without disclosing this knowledge to the customer); Paul Jurcys, Chris Donewald, Jure Globocnik, & Markus Lampinen, My Data My Terms: A Proposal for Personal Data Use Licenses, 33 Harv. J.L. & Tech. Dig. 1, 1–3 (2020) (discussing individuals’ lack of control over their data and proposing a system of data licensing that allows individuals to control who has access to their data); Woodrow Hartzog & Neil M. Richards, Privacy’s Constitutional Moment and the Limits of Data Protection, 61 B.C. L. Rev. 1687, 1714–16 (2020) (arguing that US lawmakers should look beyond simple data protections to create data privacy laws that accommodate a broad range of privacy issues by addressing the relational and power differentials between individuals and corporations).

         [51].     See, e.g., Corporate Data Responsibility, Bridging the Consumer Trust Gap, KPMG (Aug. 2021), https://kpmg.com/us/en/articles/2023/bridging-the-trust-chasm.html [https://perma.cc/DY6L-3N99] (finding 86 percent of the U.S. general population say data privacy is a growing concern); Timothy R. Graeff & Susan Harmon, Collecting and Using Personal Data: Awareness and Concerns, 19 J. Consumer Mktg. 302, 302–03 (2002), https://www.emerald.com/insight/content/doi/10.1108/07363760210433627/full/pdf?title=collecting-and-using-personal-data-consumers-awareness-and-concerns [https://perma.cc/CE9C-BBUF] (examining the extent to which consumers are concerned with the use of their data regarding privacy concerns and the impact it has on purchase behavior); Megan McLean, How Smart Is Too Smart?: How Privacy Concerns Threaten Modern Energy Infrastructure, 18 Vand. J. Ent. & Tech. L. 879, 885 (2016) (describing some of the public’s resistance to having smart meters installed because of their ability to gather personal data); Yafit Lev-Aretz & Katherine J. Strandburg, Privacy Regulation and Innovation Policy, 22 Yale J.L. & Tech. 256, 267 (2020) (expressing concern over data collected as a by-product of providing goods and services); Jathan Sadowski, When Data is Capital: Datafication, Accumulation, and Extraction, Big Data & Soc’y (Jan. 7, 2019), https://journals.sagepub.com/doi/full/10.1177/2053951718820549#bibr83-2053951718820549 [https://perma.cc/87ZX-UDX3] (arguing that data has evolved into a critical form of capital, influencing various sectors of the economy and challenging the conventional perception of data merely as a commodity by analyzing data through a lens of privacy concern).

         [52].     Kate Crawford & Jason Schultz, Big Data and Due Process: Toward a Framework to Redress Predictive Policy Harms, 55 B.C. L. Rev. 93, 109–121 (2014) (acknowledging that companies are using Big Data to determine individuals’ characteristics and to make potentially harmful decisions about prospective clients, employees, etc., or “predictive privacy harms.” This Article argues that rather than relying on policies that regulate the initial gathering of personal data, procedural due process can serve as the legal mechanism through which people can enforce their rights and ensure fair usage of their data).

         [53].     Christopher G. Bradley, Privacy for Sale: The Law of Transactions in Consumers’ Private Data, 40 Yale J. on Regul. 127, 132 (2023) (noting privacy experts “must be appointed in bankruptcy proceedings when consumer information is put up for sale”).

         [54].     See, e.g., Daniel J. Solove & Danielle Keats Citron, Risk and Anxiety: A Theory of Data Breach Harms, 96 Tex. L. Rev 737, 749–52 (2018) (outlining theories of harm plaintiffs may advance in data-breach cases); Ari Ezra Waldman, The New Privacy Law, 55 UC Davis L. Rev. Online 19, 22–30 (2021) (discussing the development of privacy law from the creation of policy structures to the addition of individual rights); Michael Washington & Neil Richards, Digital Civil Liberties and the Translation Problem, in Oxford Handbook of Criminal Process 365, 365–91 (Darryl K. Brown, Jenia I. Turner, & Bettina Weisser eds., 2019) (explaining the disruptive effect and difficulties of translating existing legal rules and doctrine to new technologies).

         [55].     As of July 2024, 19 states have enacted state privacy laws. U.S. State Privacy Legislation Tracker, Intl Assoc. of Privacy Pros., https://iapp.org/resources/article/us-state-privacy-legislation-tracker/ [https://perma.cc/JD22-5JYJ] (last visited Aug. 23, 2024).

         [56].     Razieh Nokhbeh Zaeem & K. Suzanne Barber, A Study of Web Privacy Policies Across Industries, 13 J. Info. Priv. & Sec. 169, 171, 180 (2017) (finding that 61 percent of Global 500 in the U.S. had posted privacy policies and that on average only 31 percent of North American companies did not have a privacy policy or notice on their website); see, e.g., Amazon.com Privacy Notice, Amazon, https://www.amazon.com/gp/help/customer/display.html?nodeId=GX7NJQ4ZB8MHFRNJ [https://perma.cc/3AKT-WJEV] (last visited Oct. 23, 2023) (providing examples of data that Amazon collects from users and how the data is used); Google Privacy Policy, Google, https://policies.google.com/privacy?hl=en-US [https://perma.cc/TTT7-S5VA] (last visited Oct. 23, 2023) (describing how and why Google collects data from users while they are both logged into and out of a Google account); Consumer Privacy Notice, Tesla, https://www.tesla.com/en_eu/legal/privacy [https://perma.cc/SZZ7-CZWX] (last visited Oct. 23, 2023) (offering an overview of Tesla’s data collection, use, and sharing).

         [57].     Stacy-Ann Elvy, Paying for Privacy and the Personal Data Economy, 117 Colum. L. Rev. 1369, 1380 (2017) (describing studies that show how a “significant number of consumers are using various self-help measures to protect their privacy”).

         [58].     See KPMG, supra note 51, at 1 (finding 86 percent of the United States’ general population is concerned about data privacy, but 70 percent of companies increased collection of consumer personal data in the last year); Dongyeon Kim, Kyuhong Park, Yongjin Park, & Jae-Hyeon Ahn, Willingness to Provide Personal Information: Perspective of Privacy Calculus in IoT Services, 92 Computs. in Hum. Behav. 273, 278 (2019) (concluding that consumers look past privacy concerns when receiving personalized benefit); see also Teresa Fernandes & Nuno Pereira, Revisiting the Calculus: Why are Consumers (Really) Willing to Disclose Personal Data Online?, 65 Telematics & Informatics 1, 7 (2021) (“Overall, people are paradoxically willing to disclose personal data despite privacy concerns.”).

         [59].     See Peter Segrist, How the Rise of Big Data and Predictive Analytics are Changing the Attorney’s Duty of Competence, 16 N.C. J.L. & Tech. 527, 571–72 (2015) (“[I]ntegrating diverse data can lead to what some analysts call the ‘mosaic effect,’ whereby personally identifiable information can be derived or inferred from datasets that do not even include personal identifiers, bringing into focus a picture of who an individual is and what he or she likes.”); See generally Frederik Zuiderveen Borgesius, Informed Consent: We Can Do Better to Defend Privacy, In Our Orbit (June 13, 2016), https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7085952 [https://perma.cc/6M58-2Y4Y] (“A user might only provide small bits of data, but companies could still construct detailed profiles by combining data from different sources.”).

         [60].     See, e.g., Cornelia Bjola, Data as Power, Am. Acad. in Berlin, https://www.americanacademy.de/data-as-power/ [https://perma.cc/UFP4-QK7N] (discussing data as power in the international political sphere, the utility of data governance principles, and the importance of managing tensions that arise when new forms of power arise).

         [61].     See generally, e.g., Hannah Bloch-Wehba, Visible Policing: Technology, Transparency, & Democratic Control, 109 Calif. L. Rev. 917 (2021) (advocating for more transparency in the way law enforcement uses modern technology to engage in surveillance); Hannah Bloch-Wehba, Access to Algorithms, 88 Fordham L. Rev. 1265 (2020) (suggesting the use of access law to promote transparency in the way governments use algorithms); Andrew Ferguson, Big Data and Predictive Reasonable Suspicion, 163 U. Pa. L. Rev. 327 (2015) (highlighting the complications that arise from reliance on “big data” suspicion for Fourth Amendment stops); Micah Altman, Alexandra Wood, David R. O’Brien, Salil Vadhan, & Urs Gasser, Towards a Modern Approach to Privacy-Aware Government Data Releases, 30 Berkeley Tech. L.J. 1967 (2015) (suggesting the need for a more systematic approach to privacy analysis by policymakers); Mary D. Fan, The Right to Benefit from Big Data as a Public Resource, 96 N.Y.U. L. Rev. 1438 (2021) (proposing a right to access pooled public data by incentivizing private companies to share data).

         [62].     See generally, e.g., Jules Polonetsky & Omer Tene, Privacy and Big Data: Making Ends Meet, 66 Stan. L. Rev. 25 (2013) (discussing the difficulties with balancing privacy risks with the benefits of utilizing big data); Jay P. Kesan, Carol M. Hayes, & Masooda N. Bashir, Information Privacy and Data Control in Cloud Computing: Consumers, Privacy Preferences, and Market Efficiency, 70 Wash. & Lee L. Rev. 341 (2013) (discussing the asymmetry in private companies’ terms and conditions especially related to privacy issues); Joseph Tomain, Online Privacy & the First Amendment: An Opt-In Approach to Data Processing, 83 U. Cin. L. Rev. 1 (2014) (suggesting online private parties should be required to obtain an individual’s opt-in consent prior to data processing); Amy Kapczynski, The Law of Informational Capitalism, 129 Yale L.J. 1460 (2019) (explaining the rise of “informational capitalism” as a driver of productivity and development and its potential for abuse); Jeffrey L. Vagle, Privacy’s Commodification and the Limits of Antitrust, 77 Ark. L. Rev. 51 (2024) (arguing that subjecting privacy to market mechanisms is corrosive to individual and societal norms and shifts costs onto the individual).

         [63].     See Solove & Cintron, supra note 54, at 745 (arguing that courts should consider how the use of personal data would affect the financial security and emotional state of a reasonable person impacted by a data breach); Woodrow Hartzog & Evan Selinger, Big Data in Small Hands, 66 Stan. L. Rev. Online 81, 82 (2013) (arguing that current scholarship under-accounts for the effects of big data on individual social relationships); Joel R. Reidenberg, N. Cameron Russell, Alexander J. Callen, Sophia Qasir, & Thomas B. Norton, Privacy Harms and the Effectiveness of the Notice and Choice Framework 8, 24–25 (Fordham L. Legal Studies Research Paper No. 2418247, Mar. 31, 2014) (summarizing broad critiques of the notice-and-consent framework for securing adequate consent to personal data and information sharing and reviewing examples of unauthorized disclosures of individuals’ data); Daniel J. Marcus, The Data Breach Dilemma: Proactive Solutions for Protecting Consumers’ Personal Information, 68 Duke L.J. 555, 557–58 (2018) (detailing the need for proactive solutions and comprehensive data security in a landscape where consumers have “data breach fatigue” and certain industries do not allow consumers to “opt out” of data sharing practices); Tomain, supra note 62, at 4.

         [64].     See D. Daniel Sokol & Roisin E. Comerford, Antitrust and Regulating Big Data, 23 Geo. Mason L. Rev. 1129, 1140–41 (2016) (discussing big data as a potential antitrust concern as stewards of data may have an unfair advantage over other competitors); Maurice E. Stucke & Allen P. Grunes, Debunking the Myths Over Big Data and Antitrust, CPI Antitrust Chron. 7 (Univ. Tenn. Knoxville, Research Paper No. 276, Sept. 2015) (debunking the myth that data provides its owners with little to no competitive advantage and has little significance as a barrier to entry into a market); Daniel McIntosh, We Need to Talk About Data: How Digital Monopolies Arise and Why They Have Power and Influence, 23 J. Tech. L. & Pol’y 186, 207 (discussing how mass amounts of data give the largest tech companies the power to bias search results and there is no incentive for them to share their data to help develop solutions to large problems); see also Janna Anderson & Lee Rainie, The Future of Big Data, Pew Rsch. Ctr. (July 20, 2012), https://www.pewresearch.org/internet/2012/07/20/the-future-of-big-data/ [https://perma.cc/DW65-3HTL] (“[C]ompanies, governments, and organizations that are able to mine this resource will have an enormous advantage over those that don’t . . . Big Data allows us to move from a mindset of ‘measure twice, cut once’ to one of ‘place small bets fast.’”).

         [65].     See supra note 18. See generally Heather Payne, Sharing Negawatts: Property Law, Electricity Data, and Facilitating the Energy Sharing Economy, 123 Penn. St. L. Rev. 355 (2019) (demonstrating how data can promote the efficiency of the electric grid); Brett, supra note 42 (demonstrating how data can generate more effective environmental regulation); Evan Feinauer, Sean Fernandes, Cole Francis, Alex Gross, Molly Jardine, Nick Oliver, & Anna Sims, Regulatory Guide – Freeing Energy Data: A Guide for Regulators to Remove One Barrier to Residential Energy Efficiency, Abrams Env’t L. Clinic, U. Chi. L. Sch. 7, 13 (June 2016), https://www.law.uchicago.edu/files/file/freeing_energy_data_report_abrams_environmental_clinic_june_2016.pdf [https://perma.cc/CG3H-GQ2L] (discussing ways in which open data can reduce energy costs and improve energy-efficiency measures).

         [66].     See, e.g., Clean Power Plan, Env’t Prot. Agency (May 9, 2017), https://archive.epa.gov/epa/cleanpowerplan.html [https://perma.cc/8FS5-VG3A]; Regulations for Greenhouse Gas Emissions from Passenger Cars and Trucks, Env’t Prot. Agency (Apr. 12, 2023), https://www.epa.gov/regulations-emissions-vehicles-and-engines/regulations-greenhouse-gas-emissions-passenger-cars-and [https://perma.cc/A2DT-222R]; Claire Moser, Joshua Mantell, & Nidhi Thakar, Cutting Greenhouse Gas from Fossil-Fuel Extraction on Federal Lands and Water, Ctr. for Am. Progress (Mar. 19, 2015), https://www.americanprogress.org/article/cutting-greenhouse-gas-from-fossil-fuel-extraction-on-federal-lands-and-waters/ [https://perma.cc/9VC7-S85V] (citing numerous Obama administration climate policies and considering the emissions reduction potential from policies targeted at fossil fuel resources); Exec. Off. of the Pres., United States Mid-Century Strategy for Deep Decarbonization (Nov. 2016), https://unfccc.int/files/focus/long-term_strategies/application/pdf/mid_century_strategy_report-final_red.pdf [https://perma.cc/ACD5-JGYP] (reviewing both federal and state policies to combat greenhouse gas emissions and actions targeted at fossil fuel providers such as tax incentives, loan guarantee programs, federal carbon pollution standards, energy efficiency standards, and other climate legislation and action); Joint Declaration from Energy Importers and Exporters on Reducing Greenhouse Gas Emissions from Fossil Fuels, U.S. Dep’t of State (Nov. 11, 2022), https://www.state.gov/joint-declaration-from-energy-importers-and-exporters-on-reducing-greenhouse-gas-emissions-from-fossil-fuels/ [https://perma.cc/MYC3-B4V2] (calling for both domestic and global action to reduce greenhouse gas emissions, announcing an intent to reduce methane emissions by 30 percent by 2030 and committing the United States to reducing emissions in the fossil energy sector “to the fullest extent practicable”).

         [67].     Int’l Renewable Energy Agency, Renewable Energy Prospects: United States of America 3 (Jan. 2015), https://www.irena.org/-/media/Files/IRENA/Agency/Publication/2015/Jan/IRENA_REmap_USA_summary_2015.pdf?la=en&hash=EB538B5534AEDE4694E5C4067926AE7FA060E876#:~:text=The%20renewable%20energy%20share%20in,the%20manufacturing%20industry%20and%20buildings [https://perma.cc/J8XZ-5UT2].

         [68].     See U.S. Energy Info. Admin., Renewable Energy Consumption and Electricity Preliminary Statistics 2010 2 (June 2011) (showing that biomass comprised over 50 percent of renewable energy electricity creation in 2010, and wind sources doubled their electricity creation from 2006 to 2010). For an overview of distributed energy sources, see generally Mudathir Funsho Akorede, Hashim Hizam, & Edris Pouresmaeil, Distributed Energy Resources and Benefits to the Environment, 14 Renewable & Sustainable Energy Revs. 724 (Feb. 2010) (overviewing distributed generation technologies and their ability to help meet rising energy needs).

         [69].     U.S. Energy Info. Admin., Today in Energy: Wind, Solar, and Batteries Account for More New U.S. Power Capacity Additions (Elesia Fasching ed., Mar. 6, 2023), https://www.eia.gov/todayinenergy/detail.php?id=55719 [https://perma.cc/HT99-GH3S] (“As of January 2023, 73.5 gigawatts (GW) of utility-scale solar capacity was operating in the United States, about 6% of the U.S. total. . . . As of January 2023, 141.3 GW of wind capacity was operating in the United States, about 12% of the U.S. total.”).

         [70].     Joel Jaeger, Explaining the Exponential Growth of Renewable Energy, World Res. Inst. (Sept. 20, 2021), https://www.wri.org/insights/growth-renewable-energy-sector-explained#:~:text=Since%202010%2C%20the%20cost%20of,due%20to%20positive%20feedback%20loops. [https://perma.cc/YY7Q-YJ6W].

         [71].     Solar and Battery Storage to Make Up 81% of New U.S. Electric-Generating Capacity in 2024, U.S. Energy Info. Admin.,   https://www.eia.gov/todayinenergy/detail.php?id=61424#:~:text=Solar%20and%20battery%20storage%20to,U.S.%20Energy%20Information%20Administration%20(EIA) [https://perma.cc/CWP9-LR3W] (last visited Aug. 23, 2024). An additional 23% is coming from energy storage.

         [72].     What is U.S. Electricity Generation By Energy Source?, U.S. Energy Info. Admin.,  https://www.eia.gov/tools/faqs/faq.php?id=427&t=3 [https://perma.cc/6HXV-9SJA] (last visited Aug. 23, 2024).

         [73].     Inflation Reduction Act of 2022, Pub. L. No. 117-169, 136 Stat. 1818 (2022); Biden-Harris Administration Announces $26 Million Program From Bipartisan Infrastructure Law to Demonstrate How U.S. Power Grid Can Run on 100% Clean Energy, U.S. Dep’t of Energy (Aug. 2, 2022), https://www.energy.gov/articles/biden-harris-administration-announces-26-million-program-bipartisan-infrastructure-law [https://perma.cc/V5ZZ-FF9Z].

         [74].     Energy Independence and Security Act of 2007, Pub. L. No. 110–140, 121 Stat. 1492 (2007) (defining “smart grid” as an expansive term that includes increased use of digital information as well as distributed and renewable resources).

         [75].     Your Electric Meter Before & After Solar, SolarBook, https://solarbook.pickmysolar.com/solar-basics/electric-meter-solar/ [https://perma.cc/GF5J-4FYE] (last visited Nov. 6, 2023).

         [76].     Anne Immomen, Jussi Kiljander, & Matti Aro, Consumer Viewpoint on a New Kind of Energy Market, 180 Elec. Power Sys. Rsch. 1, 1 (2020) (“Internet-of-Things (IoT) systems enable a huge amount of data to be produced by distributed, connected sensors and smart devices that also communicate and exchange the data with each other.”).

         [77].     DERs include behind-the-meter generation; energy storage on the utility side or customer side of the meter; aggregated DER, a virtual resource formed by multiple distribution generation, behind-the-meter, or energy storage devices; microgrids; cogeneration formed as a byproduct of energy production; and emergency stand-by or back-up generation facilities. U.S. Electric Grid Moving Toward Distributed Energy Resources to Address New Realities, Concentric Energy Advisors (Feb. 16, 2022), https://ceadvisors.com/u-s-electric-grid-moving-toward-distributed-energy-resources-to-address-new-realities/ [https://perma.cc/XRK7-86FC]; Kelsey Horowitz, Zac Peterson, Michael Coddington, Fei Ding, Ben Sigrin, Danish Saleem, Sara E. Baldwin, Brian Lydic, Sky C. Stanfield, Nadav Enbar, Steven Coley, Aditya Sundararajan, & Chris Schroeders, An Overview of Distributed Energy Resource (DER) Interconnection: Current Practices and Emerging Solutions, Nat’l Renewable Energy Lab. (Apr. 2019), https://www.nrel.gov/docs/fy19osti/72102.pdf [https://perma.cc/FAQ7-SBLV] (detailing current and predicted contributions of distributed generation technologies to the grid and how new data collection methods such as “bottom-up methodology” are used to predict the adoption of these advancing and interconnected generation technologies).

         [78].     See Ken Aramaki, Studying the System of the Future, Today, Energy Sys. Integration Grp. (Sept. 9, 2022), https://www.esig.energy/studying-the-system-of-the-future-today/ [https://perma.cc/CP75-X94Q].

         [79].     Consumer vs Prosumer: What’s the Difference?, Off. of Energy Efficiency & Renewable Energy, U.S. Dep’t of Energy (May 11, 2017), https://www.energy.gov/eere/articles/consumer-vs-prosumer-whats-difference [https://perma.cc/X6XW-6CAB]; Amy L. Stein, Distributed Reliability, 87 U. Colo. L. Rev 887, 887 (2016); Sharon B. Jacobs, The Energy Prosumer, 43 Ecology L.Q. 519, 533 (2016); Shelly Welton, Grasping for Energy Democracy, 116 Mich. L. Rev. 581, 597–602 (2018); Today in Energy: Homes and Buildings in the West and Northeast Have the Largest Share of Small-Scale Solar, U.S. Energy Info. Admin. (Carolyn Hronis, Zack Marohl, Ross Beall, & Laura Gellert eds., Oct. 25, 2022), https://www.eia.gov/todayinenergy/detail.php?id=54379 [https://perma.cc/PN9Y-DPYK] (reporting that 3.7 percent of U.S. single-family homes generated electricity from solar in 2020).

         [80].     Solar Industry Research Data, Solar Energy Indus. Ass’n, https://www.seia.org/solar-industry-research-data [https://perma.cc/E7R8-M2UT] (last visited Oct. 27, 2023) (providing data from cumulative U.S. residential installations from 2011 to 2021).

         [81].     Solar Integration: Inverters and Grid Services Basics, Off. of Energy Efficiency & Renewable Energy, U.S. Dep’t of Energy, https://www.energy.gov/eere/solar/solar-integration-inverters-and-grid-services-basics#:~:text=An%20inverter%20is%20one%20of,which%20the%20electrical%20grid%20uses [https://perma.cc/Y6TF-V6CD] (last visited Mar. 10, 2024).

         [82].     AMI installations range from basic hourly interval meters to real-time meters with built-in two-way communication that are capable of recording and transmitting instantaneous data. Frequently Asked Questions (FAQs): How Many Smart Meters are Installed in the United States, and Who Has Them?, U.S. Energy Info. Admin., https://www.eia.gov/tools/faqs/faq.php?id=108&t=3 [https://perma.cc/Q2FW-K3DY] (last visited Oct. 22, 2023).

         [83].     Id.

         [84].     GridX, The Digital Transformation of Utility Ratemaking, Util. Dive (Oct. 23, 2023), https://www.utilitydive.com/spons/the-digital-transformation-of-utility-ratemaking/696380/ [https://perma.cc/34J8-QQSQ].

         [85].     Advance Marketing Infrastructure (AMI) Market is Expected to Reach USD 52.40 Billion by 2030, GlobeNewswire (Apr. 3, 2023), https://www.globenewswire.com/news-release/2023/04/03/2639284/0/en/Advanced-Metering-Infrastructure-AMI-Market-is-Expected-to-Reach-USD-52-40-Billion-By-2030-Report-by-Market-Research-Future-MRFR.html [https://perma.cc/DAU4-KND4]; see also Electric Power Annual 2022, U.S. Energy Info. Admin. (Oct. 2023), https://www.eia.gov/electricity/annual/html/epa_10_05.html [https://perma.cc/A8FC-RAM7] (showing that AMI counts have more than doubled from 2013 to 2022).

         [86].     Haider Tarish Haider, Ong Hang See & Wilfried Elmenreich, A Review of Residential Demand Response of Smart Grid, 59 Renewable & Sustainable Energy Revs. 166, 167 (2016) https://www.sciencedirect.com/science/article/abs/pii/S1364032116000447 [https://perma.cc/38FL-UU76]; Energy Efficiency, NextEra Energy, https://www.nexteraenergy.com/sustainability/customers/energy-efficiency.html#:~:text=Customers%20volunteer%20to%20participate%20in,times%20of%20high%20energy%20usage [https://perma.cc/2XLE-BEGJ] (explaining that more than 700,000 Florida Power & Light (FPL) customers are voluntarily enrolled in the On Call Program, receiving a credit on their monthly bill in exchange for allowing FPL to turn off selected appliances for short periods of time to help manage peak energy demands).

         [87].     Stewardship, Exelon Corp., https://www.exeloncorp.com/sustainability/stewardship#WebPartWPQ2 [https://perma.cc/7CP2-4PGB] (“In 2022, through a combination of new and prior-year investments, our Exelon utilities helped customers save 24.8 million MWh of energy through the ComEd Energy Efficiency Program, PECO Energy Efficiency programs, BGE Smart Energy Savers Program and PHI Home Energy Savings Program”); Neighborhood Energy Saver Program, Duke Energy, https://www.duke-energy.com/home/products/income%20qualified/neighborhood%20energy%20saver?jur=NC02 [https://perma.cc/3H9N-TGZZ] (“The Duke Energy Neighborhood Energy Saver Program offers free walk-through energy assessments designed to help customers learn how their homes use energy and how to lower monthly electric bills.”).

         [88].     Amy Legate-Wolfe, Electric Vehicle Registrations Grew More Than 250% Over the Last Five Years, Yahoo! Finance (Oct. 11, 2022), https://finance.yahoo.com/news/number-electric-vehicles-us-roads-183000357.html [https://perma.cc/SX78-C523].

         [89].     EEI Projects 26.4 Million Electric Vehicles Will Be on U.S. Roads in 2030, Edison Elec. Inst. (June 2022), https://www.eei.org/resources-and-media/energy-talk/Articles/2022-06-eei-projects-264-million-electric-vehicles-will-be-on-us-roads-in-2030# [https://perma.cc/SBA8-AMXZ].

         [90].     Alternative Fuels Data Center, U.S. Dep’t of Energy, https://afdc.energy.gov/fuels/electricity_benefits.html [https://perma.cc/79FL-CX49] (last visited Mar. 10, 2024).

         [91].     GridX, supra note 84.

         [92].     See, e.g., Dirk Lauinger, François Vuille & Daniel Kuhn, A Review of the State of Research on Vehicle-to-Grid (V2G) Progress and Barriers to Deployment, (Euro. Battery, Hybrid, & Fuel Cell Elec. Vehicle Cong. Geneva, Conference Paper, Mar. 16, 2017), https://www.researchgate.net/profile/Dirk-Lauinger/publication/315144641_A_review_of_the_state_of_research_on_vehicle-to-grid_V2G_Progress_and_barriers_to_deployment/links/58cbe97ea6fdccdf531c6e47/A-review-of-the-state-of-research-on-vehicle-to-grid-V2G-Progress-and-barriers-to-deployment.pdf [https://perma.cc/5QXZ-G9LJ].

         [93].     Colin Parris, Innovation & the Grid: Why Modernizing the Electrical Grid is a Global Imperative, Gen. Elec. Vernova, https://www.ge.com/digital/blog/innovation-grid-why-modernizing-electrical-grid-global-imperative [https://perma.cc/VQA5-RMJN].

         [94].     Int’l Energy Agency, Unlocking Smart Grid Opportunities in Emerging Markets and Developing Economies 9 (June 2023), https://iea.blob.core.windows.net/assets/0b8c1500-2b02-4aaf-9072-90d88ae1e66c/UnlockingSmartGridOpportunitiesinEmergingMarketsandDevelopingEconomies.pdf [https://perma.cc/6JAC-KKGG].

         [95].     GridX, supra note 84.

         [96].     See Pirathaynini Srikantha & Deepa Kundur, Intelligent Signal Processing and Coordination for the Adaptive Smart Grid: An Overview of Data-Driven Grid Management, 36 IEEE Signal Processing Mag. 82, 83 (May 2019), https://ieeexplore.ieee.org/abstract/document/8700669 [https://perma.cc/8MWU-WKYD]; David Becker, Herbert Falk, John Gillerman, Stephen Mauser, Robin Podmore, & L. Schneberger, Standards-Based Approach Integrates Utility Applications, 13 IEEE Comp. Apps. in Power 13, 14 (Oct. 2000).

         [97].     For example, since at least the 1960s, utilities have used data to forecast future electricity demands and to plan future generation accordingly. See Bridger M. Mitchell, Judith Wilson Ross, Rolla Edward Park, & RAND Corp., A Short Guide to Electric Utility Forecasting (1986). Today, AEP is using data from smart meters to improve customer service and predict potential issues. Brad Smith, Using Data to Improve Your Service, AEP Ohio, https://www.aepohiowire.com/smart-grid-powers-better-customer-experience/ [https://perma.cc/63HA-L9MF] (last visited Oct. 27, 2023).

         [98].     Juan Pablo Carvallo, Peter H. Larsen, Alan H. Sanstad, & Charles A. Goldman, Load Forecasting in Electric Utility Integrated Resource Planning, Off. of Sci. & Tech. Info., U.S. Dep’t of Energy (Lawrence Berkeley Nat’l Lab’y, Report No. 1006395, Oct. 2016), https://www.osti.gov/servlets/purl/1371722 [https://perma.cc/4YUC-PCC9] (noting utilities are required to conduct integrated resource planning).

         [99].     Aram Shumavon, Paul de Martini, Laura Wang & More Than Smart, Data and the Electricity Grid: A Roadmap for Using System Data to Build a Plug & Play Grid 4, http://gridworks.org/wp-content/uploads/2016/10/MTS-System-Data-Paper.pdf [https://perma.cc/ADU7-RZDS]

      [100].     Id. at 3.

      [101].     Berkeley Law Ctr. for L., Energy & the Env’t, UCLA Sch. of L. Emmett Inst. on Climate Change & the Env’t & Bank of Am., Data Access for a Decarbonized Grid (Feb. 2021), https://www.law.berkeley.edu/wp-content/uploads/2021/02/Data-Access-for-a-Decarbonized-Grid-February-2021.pdf [https://perma.cc/S8Y6-WXYL]; see, e.g., Exelon Privacy Policy, Exelon, https://www.exeloncorp.com/privacy-policy [https://perma.cc/XEJ2-E8TA] (last updated Feb. 1, 2022) (“[Personally identifiable information (PII)] includes information where your name is combined with your Social Security number, driver’s license number, state identification card number, bank account number, credit card or debit card number, or unique biometric data. We may also collect PI and PII when you create or modify an online account, complete any self-service transaction with us online, or otherwise provide us with [personal information (PI)] and PII in any correspondence. This may include any of your questions, comments, or suggestions submitted through our Site or if you fill out a survey.”).

      [102].     Michael Cox & David Ellsworth, Application-Controlled Demand Paging for Out-of-Core Visualization, MJR/NASA Ames Rsch. Ctr. (1997), https://ntrs.nasa.gov/api/citations/20020046803/downloads/20020046803.pdf [https://perma.cc/2SEA-EWAP]. In 1997, Michael Cox and David Ellsworth coined the term “big data” to refer to datasets exceeding 100 gigabytes in size. Now, those datasets reach thousands of terabytes to exabytes (one million terabytes). Rustem Dautov & Salvatore Distefano, Quantifying Volume, Velocity, and Variety to Support (Big) Data-Intensive Application Development, in Proceedings – 2017 IEEE International Conference on Big Data (2017). Volume refers to the astronomical amount of data being generated. When a dataset has a high volume, it becomes impractical to store and analyze in a traditional dataset. Variety refers to the differing types, forms, and format of data being collected such as video, audio clips, images, or texts. Velocity refers to the speed at which data is generated and moves around. As an example, Google receives 5.7 million search queries every minute. Data Never Sleeps 9.0: How Much Data is Generated Every Minute?, Domo, https://web-assets.domo.com/blog/wp-content/uploads/2021/09/data-never-sleeps-9.0-1200px-1.png [https://perma.cc/E4F2-QKZC].

      [103].     The Importance of Data Needs for an Electric Utility, IKEgps (Mar. 10, 2022), https://ikegps.com/the-importance-of-data-needs-for-an-electric-utility/ [https://perma.cc/Q3BQ-E6M2].

      [104].     See Michael Palmer, Data is the New Oil, ANA Mkt. Maestros Blog (Nov. 3, 2006), https://ana.blogs.com/maestros/2006/11/data_is_the_new.html [https://perma.cc/B8SG-CJPQ] (expanding on Clive Humby’s coined phrase “Data is the new oil” with, “Data is just like crude. It’s valuable, but if unrefined it cannot really be used. It has to be changed into gas, plastic, chemicals, etc. to create a valuable entity that drives profitable activity; so must data be broken down, analyzed for it to have value.”).

      [105].     Ann Klee, The Digital Transformation of Environment, Health, and Safety, LinkedIn (Feb. 3, 2016), https://www.linkedin.com/pulse/digital-transformation-environment-health-safety-ann-klee-ann-klee [https://perma.cc/7A49-ZQQ3].

      [106].     David L. Olson, Data Mining in Business Services, 1 Serv. Bus. 181 190–91 (2007); G. Hass, P. Simon & R. Kashef, Business Applications for Current Developments in Big Data Clustering: An Overview, in 2020 IEEE International Conference on Industrial Engineering and Engineering Management 195 (2020) (“[G]lobal industry giants such as Amazon, Walmart, Alibaba, and Google . . . have embraced and integrated big data as a core business component to gain significant competitive advantages over their peers.”).

      [107].     Milind A. Mandlik & Djavlonbek Kadirov, Big Data Approaches and Outcome of Information Asymmetry: Opportunities for Future Research, 8 Int’l J. Bus. Continuity & Risk Mgmt. 303, 305–06 (2018) (saying that one of the most valuable aspects of big data analysis is how it enables firms to use data from multiple personal electronic devices, from different users, to make real-time inferences about potential consumers, which is a considerable improvement from past methods of data analysis).

      [108].     David Bollier & The Aspen Institute, The Promise and Peril of Big Data 36 (2010). For example, research suggests depressed Instagram users are inclined to post more pictures in black-and-white and fewer group photos. See generally Andrew G. Reece & Christopher M. Danforth, Instagram Photos Reveal Predictive Markers of Depression, 6 EPJ Data Sci. 1 (2017) (using machine learning to identify markers of depression based on Instagram data).

      [109].     See generally Amy L. Stein, Artificial Intelligence and Climate Change, 37 Yale J. Reg. 890 (2020) (identifying various ways the electric grid could benefit from machine learning).

      [110].     Mandlik & Kadirov, supra note 107, at 307 (“[D]ata once collected is stored forever . . . [and] can be used, re-used, and cross-referenced with other data to harness new and otherwise unnoticed behavioural insights. Consumption and associated behavioural dimensions that were not possible or obvious in the past, start to emerge as the data starts to ‘speak’.”).

      [111].     Id. at 312 (“[C]onsumers . . . are in effect consenting to capture of behavioural data. Later these behavioural insights are shared with a network of firms, even the firm harnessing such data insights are largely unaware of the possible secondary or tertiary usage of the data they collect. These firms do not know what they might discover in the data once collected, how that might spur novel product/service idea for future deployment. This very nature of secondary and tertiary analysis makes it harder for focal firms to ask consumers to consent to possible use of their behavioural insights.”). One of the most extreme examples of consumers handing over personal data without knowledge of how it is being used is the proliferation of wearable technologies. Wearable technologies, like Apple Watches and Fitbits, are constantly recording personal health data, like heart rates and sleep patterns, to help consumers live healthier lives. While Apple and Google may argue that this collection of intimate data is a known feature of the product, not a bug, consumers have not expressly consented for these products to take personal data and send it to third parties like advertisement companies. For a more thorough analysis of consumer data that has been collected by wearable technologies, see generally Marie Lemensch, Putting Our Bodies Online: The Privacy Risks of Tech Wearables, Ctr. for Int’l Governance Innovation (Aug. 11, 2021), https://www.cigionline.org/articles/putting-our-bodies-online-the-privacy-risks-of-tech-wearables/ [https://perma.cc/3W4L-WCPL] (reviewing what some scholars call the rise of surveillance capitalism, and the inadequacy of the legal framework for data collection and use related to wearable technologies and contact-tracing digital applications).

      [112].     Thornton, supra note 15.

      [113].     Boosting the Utility Customer Experience Through Analytics, Vertexone (May 24, 2021), https://www.vertexone.net/blog/boosting-the-utility-customer-experience-through-analytics [https://perma.cc/P8CD-P26U]; Brian Crow, How Utilities Leverage Data Analytics to Improve Efficiency and Enhance Operations, EE Online (May–June 2015), https://electricenergyonline.com/energy/magazine/868/article/How-Utilities-Leverage-Data-Analytics-to-Improve-Efficiency-and-Enhance-Operations.htm [https://perma.cc/Q98C-WV6L].

      [114].     Public Service Electric and Gas Company, Alliance to Save Energy, https://www.ase.org/profile/public-service-electric-and-gas-company-pseg [https://perma.cc/CG3H-GQ2L].

      [115].     New Data Leading to Better Decision Making, Gen. Elec. Vernova, https://www.ge.com/gas-power/resources/case-studies/pseg [https://perma.cc/WCU7-7WZ4].

      [116].     Richard Wernsing & Angela Rothweiler, Data Enables Proactive Asset Management, T&D World (Apr. 29, 2015), https://www.tdworld.com/grid-innovations/distribution/article/20965453/data-enables-proactive-asset-management [https://perma.cc/2ANS-QV7W].

      [117].     Capgemini Consulting, Big Data BlackOut: Are Utilities Powering Up Their Data Analytics? 4 (2015), https://www.capgemini.com/consulting-no/wp-content/uploads/sites/36/2017/08/bigdata_blackout.pdf [https://perma.cc/MGD3-9PU4].

      [118].     See Matt Piper, How and Why Utilities Are Shifting to Renewables, Env’t Sys. Rsch. Inst. (Aug. 27, 2019), https://www.esri.com/about/newsroom/publications/wherenext/how-and-why-utilities-are-shifting-to-renewables/ [https://perma.cc/389K-3J3W] (discussing Austin Energy’s use of GIS to forecast electric-vehicle usage in the city); Portland Gen. Elect., Clean Energy Plan and Integrated Resource Plan 2023 352–53 (2023), https://downloads.ctfassets.net/416ywc1laqmd/6B6HLox3jBzYLXOBgskor5/63f5c6a615c6f2bc9e5df78ca27472bd/PGE_2023_CEP-IRP_REVISED_2023-06-30.pdf [https://perma.cc/MR7W-CA6R] (incorporating customer data with other datasets to create a detailed plan for their clean energy transition).

      [119].     See, e.g., Klass & Wilson, supra note 18; Payne, supra note 8.

      [120].     See also Klass & Wilson, supra note 18, at 1116.

      [121].     Denice Ross, Tom Wilson & Chris Irwin, A White House Real-Time, Standardized, and Transparent Power Outage Data, Off. of Sci. & Tech. Pol’y (Nov. 22, 2022), https://www.whitehouse.gov/ostp/news-updates/2022/11/22/a-white-house-call-for-real-time-standardized-and-transparent-power-outage-data/ [https://perma.cc/F2VQ-AEHB]; Data Analytics for Utilities: The Future of Outage Maintenance and Prevention, AspenTech, https://www.aspentech.com/en/apm-resources/data-analytics-for-utilities#:~:text=FAQs,and%20then%20taking%20informed%20action [https://perma.cc/HY36-XPVM] (using IoT devices like sensors and meters, which are connected through the internet to provide real-time communication to monitor customer and grid equipment to determine optimal performance of products); Kathy Pretz, Novel Approaches for Forecasting Electricity Demand: Researchers Offer Ways to Make More Accurate Predictions Post-COVID, IEEE Spectrum (Nov. 4, 2021), https://spectrum.ieee.org/-forecasting-electricity-demand [https://perma.cc/L3RM-AWRQ].

      [122].     What Is a Smart Meter?, NRG, https://www.picknrg.com/en/resource-center/what-is-a-smart-meter/ [https://perma.cc/Q7YX-8N7C].

      [123].     Jacques Leslie, Utilities Grapple with Rooftop Solar and the New Energy Landscape, Yale Env’t 360 (Aug. 31, 2017), https://e360.yale.edu/features/utilities-grapple-with-rooftop-solar-and-the-new-energy-landscape [https://perma.cc/C88E-X5R5] (“[R]ooftop solar provides valuable unacknowledged benefits such as . . . avoiding the costs of building more power plants and transmission lines.”).

      [124].     VGI Policy, Pilots and Technology Enablement, Cal. Pub. Util. Comm’n, https://www.cpuc.ca.gov/industries-and-topics/electrical-energy/infrastructure/transportation-electrification/vehicle-grid-integration-activities [https://perma.cc/A5CC-6SNA] (last visited Nov. 6, 2023).

      [125].     See, e.g., Jason Glickman, Pratap Mukharji, & Joseph Scalise, How Utilities Can Save Their Customers $15 Billion, Forbes (Nov. 28, 2017), https://www.forbes.com/sites/baininsights/2017/11/28/how-utilities-can-save-their-customers-15-billion/?sh=6fb35d946895 [https://perma.cc/LSH5-VBML] (“[A]rmed with industry performance data on costs and other metrics, [senior utility executives] can lead their organizations toward [cost reduction].”); Joe Daniel, How Utilities Can Save Customers Billions of Dollars, Rocky Mt. Inst. (Jan. 16, 2023), https://rmi.org/how-utilities-can-save-customers-billions-of-dollars/ [https://perma.cc/CX8E-EKZ5] (discussing how decisions driven by data on which resources will run and which will not can save consumers billions of dollars every year).

       [126].     See Step 4: Streamline Access to Utility Data, Off. of Energy Efficiency & Renewable Energy, U.S. Dep’t of Energy, https://eere.energy.gov/energydataguide/step4.shtml [https://perma.cc/Z74N-7UAY] (outlining ways for customers to access and utilize billing information).

      [127].     See, e.g., Notice Concerning Customer Information, Puget Sound Energy (June 1, 2023), https://www.pse.com/en/pages/privacy [https://perma.cc/K4YY-WDN8].

      [128].     Id.

      [129].     See Dejan Radovanovic, Andreas Unterweger, Günther Eibl, Dominik Engel, & Johannes Reichl, How Unique is Weekly Smart Meter Data? 5 Energy Informatics Supp. 1, 3, 9 (showing that smart meter data collected in regular fifteen-minute intervals for one week still created consumption use profiles that were analyzed to successfully identify single households out of an anonymized dataset).

      [130].     See U.S. Energy Info. Admin., supra note 82.

      [131].     Betsy Loeff, Finding Value in Utility Data, Am. Pub. Power Ass’n (Sept. 7, 2022), https://www.publicpower.org/periodical/article/finding-value-utility-data [https://perma.cc/Q742-Z7VR].

      [132].     Rate designs like time-of-use rates facilitate such cost savings.

      [133].     Minn. Pub. Utils. Comm’n, Staff Briefing Paper for Docket No. E, G-999/CI-12-1344 46 (2016), https://www.edockets.state.mn.us/edockets/searchDocuments.do?method=showPoup&documentId={DB2CAA0E-FFF5-4735-A910-362D64F868A3}&documentTitle=201611-126574-01 [https://perma.cc/L4CP-3DNN].

      [134].     Yusuf Latief, Survey: Energy Sector Seeing Major Data Science Skills Gap, Smart Energy Int’l (Mar. 29, 2023), https://www.smart-energy.com/industry-sectors/data_analytics/survey-energy-sector-seeing-major-data-science-skills-gap/ [https://perma.cc/KAJ8-EP8S].

      [135].     See supra notes 42–44.

      [136].     See generally Joshua A. Kroll, Joanna Huey, Solon Barocas, Edward W. Felten, Joel R. Reidenberg, David G. Robinson & Harlan Yu, Accountable Algorithms, 165 U. Pa. L. Rev. 633, 685 (2017) (arguing for further synergistic collaboration between computer science, law, and policy to advance the design of automated decision processes for accountability); Ignacio N. Cofone, Algorithmic Discrimination Is an Information Problem, 70 Hastings L.J. 1389, 1392 (2019) (noting that “algorithms disproportionately disadvantage members of vulnerable minorities”); Reva Schwartz, Apostol Vassilev, Kristen Greene, Lori Perine, Andrew Burt, Patrick Hall, NIST Special Publication 1270 – Towards a Standard for Identifying and Managing Bias in Artificial Intelligence (2022), https://nvlpubs.nist.gov/nistpubs/SpecialPublications/NIST.SP.1270.pdf [https://perma.cc/HFE8-G5NK] (describing issues related to AI bias and examining methods to mitigate bias) .

      [137].     Neil Richards, Why Privacy Matters (Oxford Press, pub., Nov. 2021); Citron & Solove, supra note 9, at 831 (noting that given the current landscape, tort law and other legal remedies are ill-equipped to address modern day issues related to the collection and use of individuals’ personal data, which is especially unsettling given the vast “typology” of harms that can come from data collection).

      [138].     See generally Exec. Off. of the Pres.: Big Data, supra note 46, at 49 (“[D]igital data left today as a matter of routine can be reassembled to reveal intimate personal details.”); Sarah Murphy, Watt Now?: Smart Meter Data Post-Carpenter, 61 B.C. L. Rev. 785 (2020) (discussing law enforcement use of utility data as evidence).

      [139].     Elvia Limón, Today’s Headlines: Celebrities Accused as Some of the Biggest Water Wasters in SoCal, L.A. Times (Aug. 22, 2022), https://www.latimes.com/world-nation/newsletter/2022-08-22/celebrities-water-waste-drought-southern-california-todays-headlines-newsletter-todays-headlines [https://perma.cc/B698-XZEN] (“[The celebrities were among more than] “2,000 customers who were issued ‘notices of exceedance’ by the Las Virgenes Municipal Water District, which found that they had surpassed 150% of their monthly water budgets at least four times since the agency declared a drought emergency at the end of last year.”).

      [140].     Id.

      [141].     Id.

      [142].     See, e.g., Michael Murray, Mission:data Collaborates with North Carolina Attorney General John Stein on State-of-the-Art Data Portability and Privacy Rule, Mission:data (Feb. 20, 2020), http://www.missiondata.io/news/2020/2/20/missiondata-collaborates-with-north-carolina-attorney-general-josh-stein-on-state-of-the-art-data-portability-and-privacy-rule [https://perma.cc/7HSF-88DB] (announcing that Attorney General Josh Stein submitted a first-of-its-kind draft rule to the North Carolina Utilities Commission [NCUC] on data privacy and data portability).

      [143].     Nina Wang, To Ensure Every American Has Access to Water and the Internet, Stop Selling Utility Data to ICE, Bos. Globe (May 12, 2022), https://www.bostonglobe.com/2022/05/12/opinion/ensure-every-american-has-access-water-internet-stop-selling-utility-data-ice/ [https://perma.cc/B23M-4KPD]. As a result of this pressure, data broker Equifax discontinued sharing this data with ICE. Drew Harwell, Utility Giants Agree to No Longer Allow Sensitive Records to Be Shared with ICE, Wash. Post (Dec. 8, 2021), https://www.washingtonpost.com/technology/2021/12/08/utility-data-government-tracking/ [https://perma.cc/U9YV-AMDD].

      [144].     Naperville Smart Meter Awareness v. City of Naperville, 900 F.3d 521, 527 (7th Cir. 2018) (“[Smart meter] data, even when collected at fifteen-minute intervals, reveals details about the home that would be otherwise unavailable to government officials with a physical search. Naperville therefore ‘searches’ its residents’ homes when it collects this data.”).

      [145].     Id. at 528.

      [146].     See supra note 1 (collecting cases).

      [147].     Sokol & Comerford, supra note 64, at 1135; Maurice E. Stucke, Should We Be Concerned About Data-opolies?, 2 Geo. L. Tech. Rev. 275, 279 (2018); D. Daniel Sokol and Jingyuan (Mary) Ma, Understanding Online Markets and Antitrust Analysis, 15 Nw. J. Tech. & Intell. Prop. 43, 48–50 (2017) (arguing that the low barrier to entry for digital platforms and other markets utilizing big data reduces the likelihood that new entrants will be at a considerable disadvantage relative to incumbents).

      [148].     Stucke, supra note 147, at 279; Joe Kennedy, Info. Tech. & Innovation Found., The Myth of Data Monopoly: Why Antitrust Concerns About Data Are Overblown 1 (2017), https://www2.itif.org/2017-data-competition.pdf [https://perma.cc/425F-5CZM].

      [149].     Hovenkamp: Antitrust Duty to Deal, supra note 10, at 1551; Warren Grimes, Antitrust Confronts Big Data: U.S. And European Perspectives, 9 J. Int’l Media & Ent. L. 171, 172 (2020–21).

      [150].     Allensworth, supra note 10, at 589; Hovenkamp: Antitrust and Platform Monopoly, supra note 10, at 2006.

      [151].     Clarion Energy Content Directors, PG&E Fined $2.7M by Feds for Third Party’s Data Breach, Power Eng’g (Aug. 28, 2018), https://www.power-eng.com/policy-regulation/pg-e-fined-2-7m-by-feds-for-third-party-s-data-breach/#gref [https://perma.cc/3R3X-CADD] (explaining that California-based Pacific Gas & Electric was fined $2.7 million in 2019 by federal regulators for an inadvertent data breach causing confidential information to be available on the internet for more than two months).

      [152].     Abrams Env’t L. Clinic, U. Chi. L. Sch., Regulatory Guide: Freeing Energy Data: A guide for regulators to remove one barrier to residential energy efficiency 17–19 (2016), https://epic.uchicago.edu/wp-content/uploads/2019/08/Freeing-Energy-Data-report-Abrams-Environmental-Clinic-June-2016.pdf [https://perma.cc/Y53Q-BDRZ].

      [153].     Id. at 4 n.1.

      [154].     Jonathan Arentsen, Jenny Han & MJ Taylor, The Need for Public Utility Data: A Case Study on Lexington, MA 4 (2022), https://www.bu.edu/rccp/files/2022/01/Energy-Data.pdf [https://perma.cc/L2Y4-JAMQ] (“Despite the importance of [electricity data], . . . [u]tility providers . . . state privacy concerns as a reason not to share more.”); Abrams Env’t L. Clinic, supra note 152, at 16–19 (categorizing the liability, reputational concerns, and privacy concerns that may be influencing a utility’s tight grip on its data); Itron, More Intelligence & More Possibilities: How Real-Time Data and Analytics are Transforming Utilities and Cities 27 (2022), https://go.itron.com/Resourcefulness-Report-2022 [https://perma.cc/7FHF-ZTNB] (reporting that “81% of utility executives are extremely or very concerned about ensuring the privacy of customer data,” which utility operators consider the biggest obstacle to making full use of their real-time data analytics applications).

      [155].     See, e.g., Abrams Env’t L. Clinic, supra note 152, at 16–19 (noting that negative ramifications from data breaches may disincentivize utilities from sharing customer data); U.S. Dep’t of Energy, Cybersecurity Considerations for Distributed Energy Resources on the U.S. Electric Grid (2022), https://www.energy.gov/sites/default/files/2022-10/Cybersecurity%20Considerations%20for%20Distributed%20Energy%20Resources%20on%20the%20U.S.%20Electric%20Grid.pdf [https://perma.cc/7G23-T3SB].

      [156].     Application for Rehearing of Direct Energy Business, LLC and Direct Energy Services, LLC at 1, In the Matter of the App. of Ohio Power Co. for Approval to Expire its gridSMART Experimental Tariffs, No. 13-1937-EL-ATA (Pub. Utils. Comm’n of Ohio Aug. 13, 2021).

      [157].     Petition to the FTC to Commence Article 6(B) Investigation re. Electric Utility Industry’s Abusive Practices, 15 (June 14, 2022), https://www.biologicaldiversity.org/programs/energy-justice/pdfs/FTC-Petition-Re-Utilities-2022-05-16.pdf [https://perma.cc/ACC7-SWP4].

      [158].     Id.

      [159].     Two thirds of the country is restructured in competitive wholesale markets and one third of the country function with traditional vertically integrated utilities, meaning the harms of withholding energy data may be felt differently across the different regulatory regimes.

      [160].     Nat’l Renewable Energy Lab., An Introduction to Retail Electricity Choice in the United States (2017), https://www.nrel.gov/docs/fy18osti/68993.pdf [https://perma.cc/3RDB-G3EF]. Independent power producers and retail suppliers seek this information to compete in their respective competitive markets.

      [161].     Thomas Meyer & Kristen Chambers, Arcadia Raises $200 Million Led by J.P. Morgan’s Sustainable Growth Equity Team, Precision Newswire (May 10, 2022), https://www.prnewswire.com/news-releases/arcadia-raises-200-million-led-by-jp-morgans-sustainable-growth-equity-team-301543649.html [https://perma.cc/ES6U-UHHX] (“Access to comprehensive, accurate utility data has been a fundamental barrier for businesses looking to build climate tech and innovative energy products.”).

      [162].     See, e.g., Rodrigo Henríquez, George Wenzel, Daniel E. Olivares, & Matías Negrete-Pincetic Participation of Demand Response Aggregators in Electricity Markets: Optimal Portfolio Management, 9 IEEE Trans. on Smart Grid 4861, 4862 (2018) (explaining that DR aggregators can operate an intermediary between consumers and ISOs in the wholesale market).

      [163].     See also Today in Energy: Demand-Side Management Programs Save Energy and Reduce Peak Demand, U.S. Energy Info. Admin. (Mar. 29, 2019), https://www.eia.gov/todayinenergy/detail.php?id=38872 [https://perma.cc/E24D-6N9K] (“Instead of offering to fulfill electricity demand with generation, an aggregator of customers willing to stop using energy at a certain time for payment will offer a price into the market for not using a certain amount of energy.”). For an explanation of peaker plants, see What is a Peaking Power Plant?, Enel (May 11, 2023), https://www.enelnorthamerica.com/insights/blogs/what-is-a-peaking-power-plant [https://perma.cc/LK6B-KW28].

      [164].     Michael Murray, Digital Platform Regulations for Electric Utilities: Part 1, T&D World (Mar. 8, 2021), https://www.tdworld.com/smart-utility/metering/article/21157106/digital-platform-regulations-for-electric-utilities-part-1 [https://perma.cc/5SMV-9HE9] (“There is a substantial risk that utilities will act discretely to hobble, undermine, or ‘slow-walk’ their digital interactions with third-party DERs in an anti-competitive fashion.”). The California Public Utilities Commission has abandoned the approach of aggregators getting the data directly from utilities in favor of consumers giving aggregators permission to access this data. See FAQ – Demand Response Provides (DRPs)/Aggravators, Cal. Pub. Util. Comm’n, https://www.cpuc.ca.gov/industries-and-topics/electrical-energy/electric-costs/demand-response-dr/registered-demand-response-providers-drps-aggregators-and-faq [https://perma.cc/WC34-QA8X] (last visited Nov. 6, 2023).

      [165].     Complaint of Enerwise Global Technologies at 6, Enerwise Glob. Techs. v. PJM Interconnection, No. EL23-___-000 (Fed. Energy Regul. Comm’n, Sept. 28, 2023), https://elibrary.ferc.gov/eLibrary/filelist?accession_number=20230928-5025&optimized=false [https://perma.cc/HXE7-AGSN].

      [166].     Demand Response and Time-Variable Pricing Programs, Fed. Energy Mgmt. Program, U.S. Dep’t of Energy, https://www.energy.gov/femp/demand-response-and-time-variable-pricing-programs [https://perma.cc/88M2-4YUS] (last visited Nov. 6, 2023).

      [167].     Herman K. Trabish, Rate Design Roundup: Demand Charges vs. Time-Based Rates, Util. Dive, (June 2, 2016), https://www.utilitydive.com/news/rate-design-demand-charges-time-based-rates/419997/ [https://perma.cc/334E-7828] (“The problem with traditional utility rate structures is they do not convey the real cost of electricity at any given moment . . . To correct this, time-based rates . . . vary by time of day to more accurately reflect costs. These price signals can motivate customers to alter their usage patterns in ways that can reduce both peak and overall load.”).

      [168].     Id.

      [169].     Application for Rehearing of Direct Energy Business, LLC and Direct Energy Services, LLC at 4, In the Matter of the App. of Ohio Power Co. for Approval to Expire its gridSMART Experimental Tariffs, No. 13-1937-EL-ATA (Pub. Utils. Comm’n of Ohio Aug. 13, 2021).

      [170].     Initial Comments of Direct Energy Business & Direct Energy Services at 10, In the Matter of the Application of Ohio Power Company, No. 13-1937-EL-ATA (Pub. Utils. Comm’n of Ohio Jul. 10, 2020).

      [171].     Entry on Rehearing at 7, In the Matter of the App. of Ohio Power Co. for Approval to Expire its gridSMART Experimental Tariffs, No. 13-1937-EL-ATA (Pub. Utils. Comm’n of Ohio Sept. 8, 2021).

      [172].     Other entities that may want data access include market analysis companies, which want to identify trends and opportunities in the market and energy consultants. However, some perceive these entities as wanting the data for what are considered to be secondary markets instead of the primary markets (within which utilities operate).

      [173].     Efficiency-As-A-Service, Better Buildings, U.S. Dep’t of Energy, https://betterbuildingssolutioncenter.energy.gov/financing-navigator/option/efficiency-a-service [https://perma.cc/AY55-YY6B] (last visited Nov. 6, 2023).

      [174].     Meyer & Chambers, supra note 161.

      [175].     Id.

      [176].     Introducing Arc™ by Arcadia®: The Technology Platform Accelerating the Energy Revolution, Precision Newswire (Nov. 17, 2021), https://www.prnewswire.com/news-releases/introducing-arc-by-arcadia-the-technology-platform-accelerating-the-clean-energy-revolution-301426054.html [https://perma.cc/6XMW-PVQV]. Arcadia uses application programming interfaces (APIs), a set of definitions and protocols to build and integrate application software to aggregate utility data.

      [177].     See Maria McCoy, Monopolistic Utility Companies Suppress the Use of Customer Data – Episode 155 of Local Energy Rules, Inst. for Local Self-Reliance (Apr. 27, 2022), https://ilsr.org/utilities-customer-data-portability-ler155/ [https://perma.cc/3RZK-SXF5] (“Utilities have fought to control customer data and limit the customer’s ability to share information with third parties . . . [T]hird party aggregators and other efficiency services are a threat to the monopoly’s control over the market.”).

      [178].     See, e.g., Dashboard Quick Start Guide, (arc) by Arcadia, https://docs.arcadia.com/v1.0-Utility-Cloud/docs [https://perma.cc/TG8L-U8BT] (last visited Mar. 11, 2024) (providing instructions for customers to access utility data); Introducing Arc, the New Technology Platform Here to Clean Up the Energy Industry, Arcadia Blog (Nov. 17, 2021), https://blog.arcadia.com/introducing-arc [https://perma.cc/QJ5P-PRF9] (“Arc allows your customers to securely connect their utility accounts to your business. Utility bills contain dozens of data points, from customer address to rate class and usage to payment history, all of which Arc captures and standardizes.”); Heather Clancy, Investors Bet Big on Energy Data Startup Arcadia, GreenBiz (May 12, 2022), https://www.greenbiz.com/article/investors-bet-big-energy-data-startup-arcadia [https://perma.cc/E87B-EXXR] (“We built a platform that can unlock the meter-lever data — individual by individual, business by business.”).

      [179].     How Does the Wind Energy Program Work?, Arcadia, https://support.arcadia.com/hc/en-us/articles/360017920693-How-does-the-Wind-Energy-program-work [https://perma.cc/S25B-LJAG] (last visited Aug. 23, 2024); Arcadia, How Arcadia’s Wind Energy Program Works, YouTube (Jan. 17, 2020), https://youtu.be/TucA0hNcIRQ?si=0rjKdSABQq4S6mae [https://perma.cc/737J-3EDB].

      [180].     John McKay, Three Challenges Facing Companies in the New Energy Economy, Arcadia (Aug. 8, 2022), https://www.arcadia.com/blog/three-challenges-new-energy-economy [https://perma.cc/Q3BV-PGMC].

      [181].     Data and Local Policy Database: Data Access, Am. Council for an Energy-Efficient Econ., https://database.aceee.org/state/data-access [https://perma.cc/4XN4-HRVN] (last visited Nov. 16, 2023).

      [182].     Direct Testimony of Michael Murray on Behalf of Mission:data Coalition at 6, Development of a Statewide, Multi-use Online Energy Data Platform, No. DE 19-197 (N.H. Pub. Utils. Comm’n Aug. 17, 2020), https://www.puc.nh.gov/Regulatory/Docketbk/2019/19-197/TESTIMONY/19-197_2020-08-17_MISSIONDATA_TESTIMONY_MURRAY.PDF [https://perma.cc/UM3N-APT7] (distinguishing between “data access,” which is a customer obtaining data directly from a utility, and “data portability,” which is the direct transfer of customer data to a third part without passing through the customer).

      [183].     Mission:data, http://www.missiondata.io/ [https://perma.cc/97TR-6T3K] (last visited Oct. 19, 2023).

      [184].     Lucasys, Inc. v. PowerPlan, Inc., 576 F. Supp. 3d 1331, 1337 (N.D. Ga. 2021).

      [185].     Id.; About PowerPlan, PowerPlan, https://powerplan.com/about-us [https://perma.cc/ZFG5-B9TQ] (last visited Nov. 6, 2023) (reporting that nine out of ten North American IOUs run on PowerPlan).

      [186].     Lucasys, 576 F. Supp. 3d at 1339.

      [187].     Id. (denying defendant’s motion to dismiss).

      [188].     Id. at 1340.

      [189].     See, e.g., Heather Payne, Electrifying Efficiency, 40 Stan. Env’t. L.J. 57, 105 (2021); Elizabeth Ross, Megan Day, Christiana Ivanova, Akua McLeod, & Jane Lockshin, Intersections of Disadvantaged Communities and Renewable Energy Potential, 41 Renewable Energy Focus 1, 1 (2022); Hossein Hassani, Mohammad Rez Yeganegi, Christina Beneki, Stephan Unger, & Mohammad Moradghaffari, Big Data and Energy Poverty Alleviation, 3 Big Data & Cognitive Comput. 50, 53 (2019).

      [190].     Robert Walton, The Energy System is ‘Inherently Racist,’ Advocates Say. How are Utilities Responding to Calls for Greater Equity?, Util. Dive (Oct. 26, 2022), https://www.utilitydive.com/news/energy-system-inherently-racist-utilities-responding-equity-ej-justice40/634203/ [https://perma.cc/L5B4-3KL3] (suggesting that utilities collect more customer data, including on race, to assess whether their investments are equitable).

      [191].     Payne, supra note 65, at 397.

      [192].     See, e.g., Cecily McChalicher, An Avalanche of Energy Data: The Rise of Energy Data Sharing, N.E. Energy Efficiency P’ships (May 19, 2021), https://neep.org/blog/avalanche-energy-data-rise-energy-data-sharing [https://perma.cc/3P4R-E22P] (discussing numerous utility data sharing programs, including the MassSave data program in Massachusetts that allows for targeted geographical analysis with a demographics overlay to “help target programs to previously underserved communities or demographic groups”).

      [193].     See, e.g., Mass. Gen. Laws Ann. ch. 161A, § 41(e) (West 2000) (including public interest factors for electric utility businesses and granting them the broad authority to “do all things necessary, convenient or desirable to carry out the purposes of providing electricity . . . or powers implied in this chapter”).

      [194].     Kristen Ellerbe, Too Much of a Good Thing, Util. Analytics Inst. (Feb. 15, 2021), https://utilityanalytics.com/2021/02/too-much-of-a-good-thing/ [https://perma.cc/N49H-773K]; see also Itron, Microsoft & Itron: The Power of Real-Time Data: DISTRIBUTECH 2023, YouTube (Mar. 6, 2023), https://www.youtube.com/watch?v=EgA2wYu-CwQ&list=PLWMtYp-Qwjtfa703UBN_fSTVgg72dracB&index=5&ab_channel=Itron [https://perma.cc/2AL9-HGP8] (discussing how current data use by utilities is “spotty”).

      [195].     The shift in consumer power generation has changed the value of certain data. For example, customer usage data is vital to optimize the integration of distributed energy resources (DER), allowing utilities to forecast demand and modify their business model. However, if consumers can generate their own power without sharing that data with the utilities, then utilities begin to lose their monopoly on consumer energy data. See, e.g., Power to the People: The Shift Toward Consumer-Driven Energy, Morgan Stanley (Oct. 7, 2019), https://www.morganstanley.com/ideas/consumer-generated-electricity [perma.cc/T5WX-ERP9] (“[A]s more consumers install their own supply, utilities will need to shift their role to aggregation.”); see also Accenture, Best of Utilities: Summer Reading List 39 (2021) (discussing how “[electric] distribution companies need to move toward building a more data-driven . . . energy system” for threats such as “increased distributed generation”); see also generally Itron, supra note 154 (discussing how utility data can help transform the energy landscape and how Itron wants to equip customers with the ability to enable resourcefulness, meaning sustainability and renewables on the grid and put consumers in charge of how they are using the service).

      [196].     See Stephanie Jamison, Will they Still be “Utilities” by 2030?, Accenture (June 24, 2021), https://www.accenture.com/us-en/blogs/accenture-utilities-blog/will-they-still-be-utilities-by-2030 [https://perma.cc/C955-9E7P] (“[M]aintaining industrial competitiveness[] will call for widespread digitization . . . to enable the shift to a data-driven energy system”).

      [197].     See Leanne Roderick, Discipline and Power in the Digital Age: The Case of the US Consumer Data Broker Industry, 40 Critical Socio. 729, 730 (2014), https://journals.sagepub.com/doi/pdf/10.1177/0896920513501350 [https://perma.cc/8ZA7-NP5R].

      [198].     Consumer Privacy: Data Brokers, Epic.org, https://epic.org/issues/consumer-privacy/data-brokers/ [https://perma.cc/7UD9-K58S].

      [199].     Christena Garduno, How Big Data Is Helping Advertisers Solve Problems, Forbes (Mar. 15, 2022), https://www.forbes.com/sites/forbesagencycouncil/2022/03/15/how-big-data-is-helping-advertisers-solve-problems/?sh=325771fe25e0 [https://perma.cc/986B-J8VM].

      [200].     Starbucks uses consumer data to identify the best store locations, accounting for population, income levels, traffic patterns, and proximity to other coffee shops. See Bernard Marr, Starbucks: Using Big Data, Analytics, and Artificial Intelligence to Boost Performance, Forbes (May 28, 2018), https://www.forbes.com/sites/bernardmarr/2018/05/28/starbucks-using-big-data-analytics-and-artificial-intelligence-to-boost-performance/?sh=a2ab72065cdc [https://perma.cc/DTK5-WKLC].

      [201].     See, e.g., Elizabeth Mixson, Data Science at Netflix: How Advanced Data & Analytics Helps Netflix Generate Billions, AI Data & Analytics Network (Mar. 30, 2021), https://www.aidataanalytics.network/data-science-ai/articles/data-science-at-netflix-how-advanced-data-analytics-helped-netflix-generate-billions [https://perma.cc/8FNW-BSKR] (reviewing how Netflix uses data paired with algorithms to personalize video recommendations, develop content, and personalize artwork); Case Study: How Spotify Prioritizes Data Projects for a Personalized Music Experience, Pragmatic Inst., https://www.pragmaticinstitute.com/resources/articles/data/case-study-how-spotify-prioritizes-data-projects-for-a-personalized-music-experience/ [https://perma.cc/DXE9-RF86] (discussing Spotify’s data investment, processes, and how the company uses multiple models to personalize content and recommend music to users).

      [202].     Gautam Aggarwal, How Utilities Can Use Data and AI to Turn Every Interaction into a Marketing Opportunity, Forbes (June 8, 2021), https://www.forbes.com/sites/forbescommunicationscouncil/2021/06/08/how-utilities-can-use-data-and-ai-to-turn-every-interaction-into-a-marketing-opportunity/?sh=62f3aa572b25 [https://perma.cc/4RC6-ZGEZ]. See generally, e.g., Michael A. Meyer, Note, Advertising by Public Utilities as an Allowable Expense for Ratemaking: Assault on Management Prerogative, 13 Valparaiso U. L. Rev. 87 (1978) (assessing the merits of state control of utility advertising expenses).

      [203].     Rajesh K. Ahir & Basab Chakraborty, A Meta-Analytic Approach for Determining the SuccessFactors for Energy Conservation, 230 Energy 1, 2–10 (2021), https://www.sciencedirect.com/science/article/pii/S0360544221010690 [https://perma.cc/XB8G-7EJE]; Vertexone, supra note 113.

      [204].     See Lena Radosavljevic, Security and Privacy Requirements in the Public Utility Space, Helpy.io (Feb. 10, 2021), https://helpy.io/blog/security-and-privacy-requirements-in-the-public-utility-space/ [https://perma.cc/9CKX-HFDT].

      [205].     Lincoln L. Davies, Alexandra B. Klass, Hari M. Osofsky, Joseph P. Tomain & Elizabeth J. Wilson, Energy Law and Policy 139 (3d ed. 2021).

      [206].     Cleary & Palmer, supra note 35.

      [207].     See generally Aneil Kovvali & Joshua Macey, Hidden Value Transfers in Public Utilities (Coase-Sandor Working Paper Series in L. & Econ., No. 986, 2023) (explaining the impacts of utilities that transfer value to non-rate regulated subsidiaries participating in the competitive market).

      [208].     See Ryan Fulleman, Collaboration or Competition Between Utilities and Tech Firms?, Cadmus, https://cadmusgroup.com/articles/future-grid-collaboration-or-competition-utilities-tech-firms/ [https://perma.cc/3XH4-EKYW] (reviewing the competitive advantages that data offers and recognizing that longstanding incumbent utilities can leverage relationships that newer competitors lack); Pat Kennedy, Six Big Data Challenges for the Power Industry, Util. Dive (May 17, 2018), https://www.utilitydive.com/spons/six-big-data-challenges-for-the-power-industry/523298 [perma.cc/73WS-B9RN] (“[I]n some fields like oil and gas, operational data can provide the key to unlocking their competitive advantages.”).

      [209].     See, e.g., Troy A. Rule, Utility Mission Creep, UC Davis L. Rev. 591, 606 (2022) (describing how the Solar Partner program allowed the Arizona Public Service (APS) to leverage its advantages as a rate-regulated utility to undercut the market-driven prices of private rooftop solar companies); Something New Under the Sun: Competition & Consumer Protection Issues in Solar Energy, Segment 1 Transcript, Fed. Trade Comm’n. (June 21, 2016), https://www.ftc.gov/system/files/documents/videos/something-new-under-sun-competition-consumer-protection-issues-solar-energy-workshop-part-1/ftc_solar_energy_workshop_-_transcript_segment_1.pdf [https://perma.cc/Z9MZ-24VZ] [hereinafter FTC Transcript] (discussing the FTC’s interest in a competitive marketplace for solar energy production, and the need for comprehensive regulation and regulatory understanding as energy markets continue to evolve).

      [210].     See Case COMP/M.4180—Gaz de France/Suez, Comm’n Decision, ¶ 91 (Nov. 14, 2006) (summary at 2010 O.J. (C 57) 13), https://ec.europa.eu/competition/mergers/cases/decisions/m4180_20061114_20600_en.pdf [https://perma.cc/NZ46-PVZN].

      [211].     Amy L. Stein, Regulated Reliability, 54 Hous. L. Rev. 1191, 1259 (2017) (“The major utilities in Georgia and Alabama received regulatory approval to establish subsidiaries to provide third-party solar services to customers in the unregulated markets. These utilities are in direct competition with the nonutility third-party solar providers.”).

      [212].     Thomas B. Nachbar, Antitrust and the Politics of State Action, 60 Wm. & Mary L. Rev. 1395, 1417 (2019).

      [213].     See, e.g., Maria Tullia Galanti & Matteo Turri, Accountability in Local Public Utilities. Not Only Corporate Governance, 44 Int’l J. Pub. Admin. 578, 579–80 (2020) (recognizing that the politics of “who is accountable to whom” creates a weakening of political accountability).

      [214].     Exceptions exist. For example, Texas provides customers with monthly access to their data, encouraging more thoughtful energy consumption. Smart Meter Texas, CenterPoint Energy, https://www.centerpointenergy.com/en-us/services/pages/your-electric-usage.aspx?sa=ho&au=res [https://perma.cc/D4AP-DYAC]; see Green Button, U.S. Dep’t of Energy, https://www.energy.gov/data/green-button [https://perma.cc/E3MT-L5S5]. Local programs that turn ownership and data on its head also exist. See, e.g., Compare Your Home’s Energy Use with Your Neighbor, Gainesville Green, http://gainesville-green.com [https://perma.cc/43YP-YGNB] (allowing users to compare home energy consumption to others in their area).

      [215].     This analysis will focus on federal antitrust immunity but recognizes that several states have their own statutory versions of state action immunity, many of which provide a more restrictive interpretation. See, e.g., Miller’s Pond Co., LLC v. City of New London, 273 Conn. 786, 825 (2005) (citing Connecticut’s state action immunity statute).

      [216].     See FTC Transcript, supra note 209, at 7.

      [217].     15 U.S.C. §§ 1–7 (1890).

      [218].     15 U.S.C. §§ 12–27 (1914).

      [219].     15 U.S.C. §§ 41–58 (1914).

      [220].     Even though our “antitrust laws are supposed to deal with concentrated economic power,” some claim that evolving jurisprudence focuses more on consumer welfare, “as measured almost exclusively by price and quantity effects in output markets,” which has weakened Sherman Act and Clayton Act enforceability. Marshall Steinbaum & Maurice E. Stucke, The Effective Competition Standard, 86 U. Chi. L. Rev. 595, 595–96 (2008).

      [221].     See U.S. Dep’t of Justice, Antitrust Enforcement and the Consumer (2001), https://www.govinfo.gov/content/pkg/govpub-j-purl-lps16084/pdf/govpub-j-purl-lps16084.pdf [https://perma.cc/T9KR-4FYV].

      [222].     Id.

      [223].     15 U.S.C. § 1 (1890).

      [224].     Fisher v. City of Berkeley, 475 U.S. 260, 266 (1986).

      [225].     15 U.S.C. § 2 (1890).

      [226].     See generally, e.g., Herbert Hovenkamp, Antitrust Policy After Chicago, 84 Mich. L. Rev. 213 (1985) (critiquing the Chicago School model); Joshua D. Wright & Douglas H. Ginsburg, Essay, The Goals of Antitrust: Welfare Trumps Choice, 81 Fordham L. Rev. 2405 (2013) (discussing the flaws of the consumer choice standard); Michael A. Carrier, Unraveling the Patent-Antitrust Paradox, 150 U. Pa. L. Rev. 761 (2002) (reconciling antitrust and patent laws); Daniel A. Crane, Technocracy and Antitrust, 86 Tex. L. Rev. 1159 (2008) (advocating for a greater antitrust technocratic shift); C. Scott Hemphill, An Aggregate Approach to Antitrust: Using New Data and Rulemaking to Preserve Drug Competition, 109 Colum L. Rev. 629 (2009) (analyzing and proposing a solution to anticompetitive behavior between brand-name and generic drug manufacturers).

      [227].     See Cal. Liquor Dealers Ass’n v. Midcal Aluminum, Inc., 445 U.S. 97, 105 (1980) (discussing the standards for antitrust immunity); 15 U.S.C. § 2; see also Wara, supra note 12, at 205 (detailing the history of exemptions for regulated utilities from antitrust claims).

      [228].     317 U.S. 341 (1943); see, e.g., William H. Page, Antitrust, Federalism, and the Regulatory Process: A Reconstruction and Critique of the State Action Exemption After Midcal Aluminum, 61 B.U. L. Rev. 1099, 1101 (1981) (criticizing Midcal’s supervision requirement as an unjustified reliance on command-and-control regulation); Justin Desautels-Stein, A Structuralist Approach to the Two State Action Doctrines, 7 N.Y.U. J.L. & Liberty 254, 344 (2013) (comparing the constitutional and antitrust state action doctrines and crediting Parker v. Brown with the origination of the antitrust state action immunity doctrine).

      [229].     See Nachbar, supra note 212, at 1400–02.

      [230].     Compare Brown v. Parker, 39 F. Supp. 895, 896 (S.D. Cal. 1941), with Parker v. Brown, 317 U.S. 341 (1943). Some discuss the earlier Olsen case as foreshadowing the decision in Parker because the Olsen court relied on state sovereignty to hold that a state statute restricting the right to pilot water vessels to only those who were duly appointed by the governor did not violate federal antitrust law. See William H. Page & John E. Lopatka, Parker v. Brown, the Eleventh Amendment, and Anticompetitive State Regulation, 60 Wm. & Mary L. Rev. 1465, 1469 (2019) (citing Olsen v. Smith, 195 U.S. 332, 344–45 (1904)).

      [231].     Parker, 317 U.S. at 351.

      [232].     Id.

      [233].     Id.

      [234].     See, e.g., City of Lafayette, La. v. La. Power & Light Co., 435 U.S. 389, 417 (1978) (“[A] State properly may . . . direct or authorize its instrumentalities to act in a way which . . . would be inconsistent with the antitrust laws.”).

      [235].     A plurality of the Supreme Court originally refused to extend the immunity to an electric utility because Parker was limited to state actors. Cantor v. Detroit Edison Co., 428 U.S. 579 (1976).

      [236].     445 U.S. 97 (1980).

      [237].     Id. at 99.

      [238].     Id. at 105.

      [239].     Id. The state failed under the second prong. The state simply authorized price setting and enforced the prices established by private parties. It does not establish prices, review the reasonableness of price schedules, regulate the terms of fair-trade contracts, monitor market conditions, or engage in any “pointed reexamination” to satisfy the “active supervision” prong.

      [240].     See Stephen C. Sherrill, Note, Parker v. Brown Revisited: The State Action Doctrine after Goldfarb, Cantor, and Bates, 77 Colum. L. Rev. 898, 899–900 (1977); Page, supra note 228, at 1100–01; Desautels-Stein, supra note 228, at 344; Alexander Volokh, Antitrust Immunity, State Administrative Law, and the Nature of the State, 52 Ariz. St. L.J. 191, 207–10 (2020).

      [241].     See Yeager’s Fuel, Inc. v. Pa. Power & Light, 22 F.3d 1260, 1268 (3d Cir. 1994).

      [242].     MCI Commc’ns Corp. v. Am. Tel. & Tel. Co., 708 F.2d 1081, 1103 (7th Cir. 1983) (noting that even though the Federal Communications Commission [FCC] had authority to compel interconnection, the utility voluntarily made an interconnection decision, which had not been approved by the FCC).

      [243].     See S. Motor Carriers Rate Conf., Inc. v. United States, 471 U.S. 48, 48 (1985).

      [244].     Yeager’s Fuel, 22 F.3d at 1260.

      [245].     S. Motor Carriers Rate Conf., 471 U.S. at 56.

      [246].     Id. at 65.

      [247].     Id. at 62.

      [248].     See, e.g., Fed. Trade Comm’n v. Phoebe Putney Health Sys., Inc., 568 U.S. 216, 220 (2013) (holding that state action immunity did not apply where a state had not clearly articulated a policy that would substantially lessen competition).

      [249].     See Nachbar, supra note 212, at 1399 (citing N.C. State Bd. of Dental Examiners v. Fed. Trade Comm’n, 574 U.S. 494 (2015)); see also Jim Rossi, Antitrust Process and Vertical Deference: Judicial Review of State Regulatory Inaction, 93 Iowa L. Rev. 185 (2007) [hereinafter Antitrust Process] (arguing for judges to replace the Midcal test with a more process-based analysis).

      [250].     Nachbar, supra note 212, at 1413, 1433–37. Understanding that the nature of regulation means that nearly all lobbying efforts are requests for anticompetitive results and would potentially violate antitrust law, the Noerr/Pennington doctrine immunizes private parties who petition regulators to adopt laws and regulations that would benefit their industry. With this in mind, Professor Nachbar argues for greater reliance on the Noerr/Pennington doctrine in state action immunity analyses for private parties to create more predictable outcomes in state action cases. Reliance on the doctrine would also more clearly further the political, federalist purpose of state action immunity, as opposed to the economic focus that courts have recently used. For example, Professor Nachbar uses North Carolina State Board of Dental Examiners v. FTC to illustrate how the court could have employed the Noerr/Pennington doctrine to more accurately position the court to answer the political question of whether the Board making the regulatory acts was the state—and therefore immune from liability—rather than engaging in difficult speculation about potential economic harms that self-interested regulators may create to decide whether the Board was the state.

      [251].     See Kevin M. Decker, Filed-Rate Doctrine: Leaving Regulation to the Regulators, 34 William Mitchell L. Rev. 1351, 1351–52 (2008); But see Jim Rossi, Why the Filed Rate Doctrine Should Not Imply Blanket Judicial Deference to Regulatory Agencies, 34 Admin. & Reg. L. News 11, 11–12 (2008) (questioning the filed-rate doctrine’s deference to regulatory agencies amidst market deregulation); see also Sandeep Vaheesan, Market Power in Power Markets: The Filed-Rate Doctrine and Competition in Electricity, 46 U. Mich. J.L. Reform 921, 946–54 (2013) (arguing that the filed-rate doctrine’s application to electricity markets is misguided).

      [252].     Order & Reasons at 16–20, La. Child.’s Med. Ctr. v. Att’y Gen. of the U.S., No. 23-1305 (E.D. La. Sept. 27, 2023), https://www.govinfo.gov/content/pkg/uscourts-laed-2_23-cv-01305/pdf/uscourts-laed-2_23-cv-01305-0.pdf [https://perma.cc/TV23-XMUV].

      [253].     See, e.g., Ellis v. Salt River Project Agric. Improvement & Power Dist., 24 F.4th 1262, 1276 (9th Cir. 2022) (declining to apply state action immunity).

      [254].     Opinion and Order of the Comm’n at 1, In the Matter of La. Real Estate Appraisers Bd., No. 9374 (Fed. Trade Comm’n Apr. 10, 2018), https://www.ftc.gov/system/files/documents/cases/d09374_opinion_and_order_of_the_commission_04102018_redacted_public_version.pdf [https://perma.cc/N932-8JB8].

      [255].     Cal. Retail Liquor Dealers Ass’n v. Midcal Aluminum, Inc., 445 U.S. 97, 105 (1980).

      [256].     See Yeager’s Fuel, Inc. v. Pa. Power & Light, 22 F.3d 1260, 1266 (3d Cir. 1994) (explaining that state action immunity is an affirmative defense, thus putting the burden of proof on the party raising the doctrine as a defense).

      [257].     Id. (interpreting the plain language of the Public Utilities Regulatory Policy Act of 1978 to imply that antitrust theories of liability and defense apply in full force to utilities).

      [258].     See, e.g., Ellis, 24 F.4th at 1276 (rejecting state action immunity because Arizona had not articulated a policy to displace competition, but rather expressed a policy preference for competition in electricity generation and supply); Midcal, 445 U.S. at 106 (holding that the state’s involvement in a pricing system does not itself confer state action immunity); Quadvest, L.P. v. San Jacinto River Auth., 7 F.4th 337, 344 (5th Cir. 2021) (denying immunity to a river authority on an antitrust claim brought by two private water companies); Miller’s Pond Co., LLC v. City of New London, 273 Conn. 786, 813 (2005) (rejecting state action immunity for water utilities); McCaw Personal Communications, Inc. v. Pac. Telesis Group, 645 F. Supp. 1166, 1173 (N.D. Cal. 1986) (rejecting a telecommunication utility’s claim of immunity under the Midcal test). But see City of Columbia v. Omni Outdoor Advertising, 499 U.S. 365, 374 (1991) (finding Parker immunity for a city ordinance due because antitrust liability would unduly restrict competition in implementation of the state policy).

      [259].     See, e.g., Midcal, 445 U.S. at 106; Town of Hallie v. City of Eau Claire, 471 U.S. 34, 38–39 (1985); Omni Outdoor Advertising, 499 U.S. at 370.

      [260].     See Town of Hallie, 471 U.S. at 41–42.

      [261].     “A search of state energy data access for third parties in the ACEEE database resulted in findings that the majority of states that have addressed the issue support allowing data sharing with customer consent.” Am. Council for an Energy-Efficient Econ., supra note 181.

      [262].     Id. (showing that twenty of fifty states have addressed energy utility data). Their chart has been updated with four additional state laws addressing data privacy, reflected in Appendix A, bringing the total to 24 states.

      [263].     Id.

      [264].     Id.

      [265].     Cal. Pub. Util. Code § 8380(a)(2) (West 2021) (“An electrical corporation or gas corporation shall not sell a customer’s electrical or gas consumption data or any other personally identifiable information for any purpose.”); Wash. Rev. Code. Ann. § 480-100-153 (West 2015) (“A utility may not sell customer information.”).

      [266].     See Appendix A for a chart summarizing ACEEE’s relevant findings; Am. Council for an Energy-Efficient Econ., supra note 181 (noting Maine, New Hampshire, New York, and Pennsylvania); McChalicher, supra note 192.

      [267].     As of July 2024, 19 states have enacted state privacy laws. Int’l Ass’n of Priv. Pros., supra note 55. Many of these laws provide blanket requirements that data collectors “maintain reasonable security measures” to protect from unauthorized disclosure (see Illinois 815 ILCS 530/45), and allow customers to opt out. See Utah S.B. 227 Consumer Privacy Act, https://le.utah.gov/~2022/bills/sbillenr/SB0227.pdf [https://perma.cc/L247-JZ7N].

      [268].     Some municipal level data sharing pilots exist. See, e.g., Energy Usage Data Request: Helping you Reach your Sustainability Goals, Fla. Power & Light, https://www.fpl.com/business/energy-usage-data.html [perma.cc/MJ8W-3JCA] (FPL’s “Real Zero” pilot in Miami).

      [269].     The Ninth Circuit also rejected the filed-rate doctrine defense to antitrust immunity, finding that because SRP determines its own rates without any agency or PRC approval, this self-regulation makes it distinct from almost all other utilities and disqualifies it from this defense. Ellis v. Salt River Project Agric. Improvement & Power Dist., 24 F.4th 1262, 1275 (9th Cir. 2022).

      [270].     Id.

      [271].     Id. at 1277.

      [272].     N.C. State Bd. of Dental Exam’rs v. Fed. Trade Comm’n, 574 U.S. 494, 503 (2015).

      [273].     Id. at 498.

      [274].     Am. Council for an Energy-Efficient Econ., supra note 181 (finding that thirty-one states lack clear regulations or authorizations regarding the process for utilities sharing customer data with third parties).

      [275].     7 F.4th 337, 339–40 (5th Cir. 2021).

      [276].     The court understood the Midcal test to involve two distinct questions: (1) does state law authorize the defendant to engage in the challenged conduct?, and (2) did the state authorize the challenged conduct with an intent to displace competition with regulation or monopoly service? Id. at 346.

      [277].     Id. at 348.

      [278].     Id.; see also Cal. Retail Liquor Dealers Ass’n v. Midcal Aluminum, Inc., 445 U.S. 97, 105–06 (1980) (noting the “risk of private entities influencing a state entity’s decisions”); Rossi, Antitrust Process, supra note 249, at 212 (arguing mere jurisdiction to regulate should be insufficient).

      [279].     Quadvest, 7 F.4th at 348.

      [280].     Id.

      [281].     Midcal Aluminum, 445 U.S. at 105.

      [282].     S. Motor Carriers Rate Conf. v. United States, 471 U.S. 48, 66 (1985) (holding that the intrastate truck carriers were immune from antitrust scrutiny where the state public utility commission approved uniform rates for intrastate truck transportation).

      [283].     Fed. Trade Comm’n v. Ticor Title Ins. Co., 504 U.S. 621, 638 (1992).

      [284].     Id. But see Rossi, Antitrust Process, supra note 249, at 203–07 (documenting various examples of undeserved deference courts provide to state regulation in deregulated electricity markets under the state action doctrine).

      [285].     Practices that involve utility discretion and incomplete regulation may invalidate state action immunity. See, e.g., Borough of Ellwood City v. Pa. Power Co., 462 F. Supp. 1343, 1348–49 (W.D. Pa. 1979) (rejecting antitrust protections by narrowly construing the supervision requirement—holding that if the “full mechanism” is not within the PUC’s control or if the activity in question falls beyond PUC regulation or purview, then active supervision “is necessarily absent” and Parker immunity does not apply); see also Mobilfone of N.E. Pa. v. Commwealth Tel. Co., 571 F.2d 141, 147 (3d Cir. 1978) (recognizing state supervision as sufficient to invoke immunity where the state’s policy was “clearly and affirmatively expressed by both statute and . . . the PUC . . . and the state supervision of the challenged activity is comprehensive and active”).

      [286].     See Am. Council for an Energy-Efficient Econ., supra note 181.

      [287].     See Barry J. Kessler, State Action Antitrust Exemption as Applied to Public Utility Regulation: Borough of Ellwood City v. Pennsylvania Power Co., 20 Urban L. Annual 289, 302–04 (1980) (suggesting that the ambiguous scope and application of the active supervision element of state action immunity may create unforeseen antitrust liability for public utilities).

      [288].     Horizontal market power involves controlling prices across a market. Vertical market power involves blocking competitors from an upstream product.

      [289].     See, e.g., Volasco Prods. Co. v. Lloyd A. Fry Roofing Co., 346 F.2d 661 (6th Cir. 1965) (holding the district court was justified in issuing an injunction against price discrimination); United States v. Am. Tel. & Tel. Co., 552 F. Supp. 131 (D.D.C. 1982) (breaking up AT&T’s operating companies).

      [290].     Am. Tel. & Tel. Co., 552 F. Supp. at 222; Rory Van Loo, In Defense of Breakups: Administering a “Radical” Remedy, 105 Cornell L. Rev. 1955, 1956 (2020) (“Academics have driven a renaissance in antitrust scholarship, calling for stronger remedies for anticompetitive behavior, with some proposing breakups.”); Michael A. Carrier, Big Tech, Antitrust, and Breakup, Geo. J. Int’l Affs. (Jan. 14, 2020), https://gjia.georgetown.edu/2020/01/14/big-tech-antitrust-and-breakup/ [https://perma.cc/5UVY-E6M4].

      [291].     15 U.S.C §§ 26, 53(b); see Fed. Trade Comm’n v. Whole Foods Mkt., 548 F.3d 1028, 1034–35 (D.C. Cir. 2008); Jesse W. Markman Jr., Lessons for Competition Law from the Economic Crisis: The Prospect for Antitrust Responses to the “Too-Big-To-Fail” Phenomenon, 16 Fordham J. Corp. & Fin. L. 261, 262 (2011).

      [292].     Herbert J. Hovenkamp, Antitrust Interoperability Remedies [hereinafter H. Hovenkamp: Antitrust Interoperability Remedies], 123 Colum. L. Rev. 1, 15–16 (2023).

      [293].     Id. at 15–20 (discussing how forced divestiture is not desirable for firms with natural monopoly characteristics).

      [294].     H. Hovenkamp: Antitrust and Platform Monopoly, supra note 10, at 2006.

      [295].     Other antitrust remedies such as restructured management that improve competition through internal decisions could also be an appropriate remedy for anticompetitive utilities, particularly a requirement to add at least one ratepayer to each utility’s Board of Directors. See, e.g., David Eggleston, Norwich Ratepayer Representative to CMEEC Annual Report to the City Council 1–3 (2021), https://www.norwichct.org/ArchiveCenter/ViewFile/Item/1263 [https://perma.cc/TH5K-QUR7]. Maine Electric Ratepayer Advisory Council, mandated by a 2022 legislation, is made up of a mix of consumers, equal justice advocates, consumer-owned distributers or transmitter reps, and investor-owned distributer or transmitter reps. The Council’s role is to make recommendations to the state’s Public Advocate regarding rate proposals, energy efficiency, and equity. An Act To Create the Electric Ratepayer Advisory Council, 2022 M.E. Pub. L. ch. 623 (2022), https://www.maine.gov/meopa/sites/maine.gov.meopa/files/inline-files/LD%201913_Chap%20Law.pdf [https://perma.cc/5TG6-RJTJ].

      [296].     15 U.S.C. § 2.

      [297].     In re Google Play Store Antitrust Litig., No. 20-CV-05761-JD, 2022 WL 17252587, at *8–12 (N.D. Cal. Nov. 28, 2022) (citing Fed. Trade Comm’n v. Qualcomm Inc., 969 F.3d 974, 990 (9th Cir. 2020) (internal quotations omitted)).

      [298].     Fed. Trade Comm’n v. Facebook Inc., 581 F. Supp. 3d 34, 44 (D.D.C. 2022) (explaining that determining the relevant market in antitrust cases is typically a factual inquiry with certain “legal principles” and includes the “product market” and the “geographic market”). The relevant product market here would likely be the market for energy data and the relevant geographic area would be the state-sanctioned utility service territory area.

      [299].     See infra Part II.C.

      [300].     In re Google Play Store Antitrust Litig., at *9 (citing Olean Wholesale Grocery Coop., Inc. v. Bumble Bee Foods LLC, 31 F.4th 651 (9th Cir. 2022) (internal citation omitted)). As discussed infra, these antitrust harms are often conflated with other consumer harms, including privacy harms.

      [301].     E. Hovenkamp: Antitrust Duty to Deal, supra note 10, at 1487; Refusal to Deal, Fed. Trade Comm’n, https://www.ftc.gov/advice-guidance/competition-guidance/guide-antitrust-laws/single-firm-conduct/refusal-deal [https://perma.cc/TYL8-8XZV] (“One of the most unsettled areas of antitrust law has to do with the duty of a monopolist to deal with its competitors.”).

      [302].     See United States v. Colgate, 250 U.S. 300, 307–08 (1919); Verizon Commc’ns Inc. v. Trinko, 540 U.S. 398, 408 (2004).

      [303].     See Eastman Kodak Co. v. S. Photo Materials Co., 273 U.S. 359, 375 (1927).

      [304].     See Otter Tail Power Co. v. United States, 410 U.S. 366, 368 (1973).

      [305].     See generally E. Hovenkamp: Antitrust Duty to Deal, supra note 10 (using Big Tech companies to argue that the duty to deal should be redefined to continue protecting investments while also allowing prosecution of meritorious cases); Marina Lao, Search, Essential Facilities, and the Antitrust Duty to Deal, 11 Nw. J. Tech. & Intell. Prop. 275 (2013) (arguing that a duty to deal does not apply to Google in preferencing its own content in search results); James C. Burling, William F. Lee, & Anita K. Krug, The Antitrust Duty to Deal and Intellectual Property Rights, 24 J. Corp. L. 527 (1999) (exploring the application of the duty to deal in intellectual property cases and suggesting that courts should devote considerable attention to patent law in deciding whether or not to apply a duty to deal).

      [306].     472 U.S. 585, 602–04 (1985).

      [307].     Id. at 610–11.

      [308].     Verizon Commc’ns Inc., 540 U.S. at 414–15; see id. at 411 (noting that the Supreme Court has “never recognized such a doctrine” as the essential facilities doctrine); E. Hovenkamp: The Antitrust Duty to Deal, supra note 10, at 1553–54.

      [309].     540 U.S. at 412 (quoting Town of Concord v. Boston Edison Co., 915 F.2d 17, 25 (1st Cir. 1990)).

      [310].     Id. at 415–16.

      [311].     Id. at 408.

      [312].     Id. at 407.

      [313].     Such a mandate does exist in Order 888, which mandates access to transmission lines, but there is no corollary for access to data.

      [314].     Verizon Commc’ns, Inc. v. Trinko, 540 U.S. 398, 407–08 (2004) (stating that forced sharing may disincentivize firms to invest in economically beneficial technology).

      [315].     E. Hovenkamp, Antitrust Duty to Deal, supra note 10, at 1553.

      [316].     Otter Tail Power Co. v. United States., 410 U.S. 366 (1973).

      [317].     E. Hovenkamp, Antitrust Duty to Deal, supra note 10, at 1553. Evidence of vertical agreements between the utility and customers (as opposed to unilateral refusals to deal) could provide an even stronger avenue for liability.

      [318].     Patrick Rey, Paul Seabright, & Jean Tirole, The Activities of a Monopoly Firm in Adjacent Competitive Markets: Economic Consequences And Implications For Competition Policy 3 (Institut d’Economie Industrielle (IDEI), Toulouse, Working Paper No. 132, 2001).

      [319].     H. Hovenkamp: Antitrust Interoperability Remedies, supra note 292, at 1.

      [320].     See Daphna Renan, Pooling Powers, 115 Colum. L. Rev. 211, 213 (2015).

      [321].     Robert P. Merges & Michael Mattioli, Measuring the Costs and Benefits of Patent Pools, 78 Ohio St. L.J. 281, 284–85 (2017); George Slover, Interoperability is Important for Competition, Consumers, & the Economy, Ctr. for Democracy & Tech. (Jan. 12, 2023), https://cdt.org/insights/interoperability-is-important-for-competition-consumers-the-economy/ [https://perma.cc/7CH5-PTZ6].

      [322].     Jorge L. Contreras, Patent Pledges, 47 Ariz. St. L.J. 543, 564–65 (2015).

      [323].     See MCI Commc’ns Corp. v. Am. Tel. & Tel. Co., 708 F.2d 1081, 1132 (7th Cir. 1983).

      [324].     H. Hovenkamp: Antitrust Interoperability Remedies, supra note 292, at 8.

      [325].     United States v. Terminal R.R. Assn. of St. Louis, 224 U.S. 383, 411 (1912).

      [326].     Id.; see also H. Hovenkamp: Antitrust Interoperability Remedies, supra note 292, at 10–11 (referring to Terminal Railroad as an example of court-mandated interoperability).

      [327].     H. Hovenkamp: Antitrust and Platform Monopoly, supra note 10, at 2033. See generally Renan, supra note 320 (exploring how pooling amongst administrative agencies can provide increased efficiency and flexibility but noting that pooling could undermine democratic accountability in this context); Rudy Santore, Michael McKee, & David Bjornstad, Patent Pools as a Solution to Efficient Licensing of Complementary Patents? Some Experimental Evidence, 53 J.L. & Econ. 167 (2010) (providing empirical evidence showing that increased coordination or pooling among complementary patent holders benefits both industry efficiency and consumer welfare).

      [328].     See supra note 11 and accompanying text.

      [329].     Data Inoperability, Natl. Library of Med., https://www.nnlm.gov/guides/data-glossary/data-interoperability [https://perma.cc/5GJU-SPHX].

      [330].     See, e.g., Yeager’s Fuel, Inc. v. Pa. Power & Light, 22 F.3d 1260, 1264 (3d Cir. 1994) (noting that the electric utility had conceded that “it does not seek state action immunity for [benefits provided pursuant to agreements]”).

      [331].     Hossein Rahnama & Alex “Sandy” Pentland, The New Rules of Data Privacy, Harv. Bus. Rev. (Feb. 25, 2022), https://hbr.org/2022/02/the-new-rules-of-data-privacy [https://perma.cc/8MJC-66VY].

      [332].     Husch Blackwell, supra note 55.

      [333].     See Müge Fazlioglu, U.S. Federal Privacy Legislation Tracker Introduced in the 118th Congress (2023-24), Int’l Ass’n Privacy Pro’s. (2024), https://iapp.org/media/pdf/resource_center/us_federal_privacy_legislation_tracker.pdf [https://perma.cc/MJ5M-GN9V]. Fifty-nine bills about data privacy were introduced during the 118th Congress. Some bills, such as the Mind Your Own Business Act of 2021 and the Consumer Data Privacy and Security Act of 2021, aimed at general individual privacy. Other bills, such as the Protecting Sensitive Personal Data Act or the My Body, My Data Act of 2022, focused on more niche areas of privacy such as financial or health privacy. Other countries like Brazil and India enacted legislation that mirrors the aims of the GDPR. Lei Geral de Protecao de Deados [General Data Privacy Law], LEI No. 13.709 (Aug. 14, 2018), Diario Oficial Da Uniao de 15.8.2018 (Braz.); India’s Personal Data Protection Bill of 2019 (PDPB). Although many of the principles remain the same, the fines for noncompliance are significantly lower than those for the GDPR.

      [334].     Many private companies now include privacy pop-ups for users, and most private entities more prominently disclose their privacy policies. See, e.g., Privacy Policy, PG&E (Dec. 6, 2023), https://www.pge.com/en/privacy-center/privacy-policy.html [https://perma.cc/5GJU-SPHX]; Privacy Policy, Duke Energy, https://www.duke-energy.com/legal/privacy-policy [https://perma.cc/7YFA-73G2] (last updated Nov. 14, 2023).

      [335].     GDPR at n. 2, arts. 13(2)f, 14(2)f.

      [336].     See Kugler & Hurley, supra note 11, at 499.

      [337].     Several state PUCs have adopted a 15/15 rule for sharing aggregated data. The 15/15 rule requires that an aggregated dataset has at least fifteen customers and that no customer represents more than 15 percent of the data. See, e.g., Final Decision at 33–36, 76 CPUC 2d 29, 1997 WL 868376 (Cal.P.U.C. Oct. 9, 1997).

      [338].     See generally Matthias Templ & Murat Sariyar, A Systematic Overview on Methods to Protect Sensitive Data Provided for Various Analyses, 21 Int’ J. Info. Sec. 1233 (2022) (providing an overview of the different methods of data anonymization currently being used).

      [339].     Chris Pike, Lines of Business Restrictions – Background Note, Org. for Econ. Coop. & Dev. (May 19, 2020), https://one.oecd.org/document/DAF/COMP/WP2(2020)1/en/pdf [https://perma.cc/Z4RK-TPR2]. Although some include structural and behavioral remedies together when discussing line of business restrictions, this analysis separates structural from non-structural remedies.

      [340].     Id. at 2.

      [341].     United States v. Am. Tel. & Tel. Co., 552 F. Supp. 131, 152–53 (D.D.C. 1965) (replaced by a 1982 Consent Decree). These LOBRs lasted until they were superseded by the 1982 Consent Decree that removed all LOBRs on AT&T (except for a restriction on electronic publishing) following the divestiture of AT&T’s local operating companies into seven regional systems. Id. at 222–26.

      [342].     Lawrence J. Spiwak, The Folly of Line of Business’ Restrictions for Big Tech, The Hill (Feb. 19, 2021), https://thehill.com/blogs/congress-blog/politics/539682-the-folly-of-line-of-business-restrictions-for-big-tech/ [https://permaGK9N-F8FT].

      [343].     Kenneth J. Arrow, Dennis W. Carlton & Hal S. Sider, The Competitive Effects of Line-of-Business Restrictions in Telecommunications, 16 Managerial & Decision Econs. 301, 310 (1995).

      [344].     See Ford Motor Co. v. United States, 405 U.S. 562, 578 (1972).

      [345].     Christian M. Dippon & Matthew D. Hoelle, The Economic Costs of Structural Separation, Line of Business Restrictions, and Common Carrier Regulation of Online Platforms and Marketplaces 10 (Oct. 20, 201), https://www.nera.com/content/dam/nera/publications/2021/Platform_Regulation_Conceptual_10_20_21.pdf [https://perma.cc/8ZHD-LLVT] (noting the inclusion of LOBRs in three 2021 proposed bills).

      [346].     Competition and Monopoly: Single Firm Conduct Under Section 2 of the Sherman Act: Chapter 7, U.S. Dep’t of Just., https://www.justice.gov/archives/atr/competition-and-monopoly-single-firm-conduct-under-section-2-sherman-act-chapter-7 [https://perma.cc/2ENT-V23J] (“[U]nilateral, unconditional refusals to deal should not play a meaningful part in Section 2 enforcement.”).

      [347].     Regulatory remedies are generally more suited to applying complicated behavioral restrictions within a specific industry because they can enact more specific rules and enforce them more efficiently. E. Hovenkamp: Antitrust Duty to Deal, supra note 10, at 1554.

      [348].     Although one may question whether the prior analysis about state action immunity is irrelevant if regulatory remedies could prove sufficient, the threat of antitrust liability for utilities may be needed to catalyze some regulators into action. See id. at 1554–56 (suggesting that while a hypothetical regulatory regime is likely more efficient in regulating Big Tech, antitrust scrutiny should remain on the table).

      [349].     For instance, judicially imposed interoperability remedies, such as the mandated access to railroad facilities in United States v. Terminal R.R. Assn. of St. Louis, 224 U.S. 383 (1912), are very similar to the regulatory remedies of open access to transmission lines that FERC has imposed on utilities through Order 888, which mandated transmission access for non-incumbent electricity generators. Promoting Wholesale Competition, FERC Order No. 888, 18 C.F.R. Part 35 (Apr. 26, 1996).

      [350].     Eur. Comm’n, EU Directive on Interoperability Requirements and Non-Discriminatory and Transparent Procedures for Access to Metering and Consumption Data, 2023 O.J. (C 11162).

      [351].     Annual CPNI Certifications Due March 1, 2023, Fed. Commc’ns Comm’n Enforcement Advisory (Feb. 1, 2023), https://docs.fcc.gov/public/attachments/DA-23-93A1.doc [https://perma.cc/M656-XZAS].

      [352].     CPNI is defined as (A) information that relates to the quantity, technical configuration, type, destination, location, and amount of use of a telecommunications service subscribed to by any customer of a telecommunications carrier, and that is made available to the carrier by the customer solely by virtue of the carrier-customer relationship; and (B) information contained in the bills pertaining to telephone exchange service or telephone toll service received by a customer of a carrier. 47 U.S.C. § 222(h)(1).

      [353].     Section 201(b) requires carriers’ practices be just and reasonable, including practices related to privacy, data protection, and cybersecurity. Section 222 restricts carriers’ use and disclosure of their customers’ proprietary information and CPNI. See also 47 C.F.R. § 64.2001 et seq.

      [354].     Nat’l Sci. & Tech. Council, National Strategy to Advance Privacy-Preserving Data Sharing and Analytics 20 (2023) (noting that responsible practices would address concerns surround democratic values, broader privacy issues, and the creation of data monopolies).

      [355].     At least one PUC has already held a hearing to determine, in part, whether its jurisdiction over a utility’s “services” includes its data and related practices. Staff Briefing Paper at 46, No. E,G-999/CI-12-1344 (Minn. Pub. Utils. Comm’n Dec. 1, 2016).

      [356].     Notably, deferring to a state will not necessarily result in a more robust marketplace for energy data.

      [357].     In 2019, U.S. utilities spent $31.4 billion on capital investments for distribution. Major Utilities’ Spending on the Electric Distribution System Continue to Increase, U.S. Energy Info. Admin. (May 27, 2021), https://www.eia.gov/todayinenergy/detail.php?id=48136 [https://perma.cc/9LTD-9MTB].

      [358].     See Pac. Gas & Elec. Co v. Pub. Utils. Comm’n of Cal., 475 U.S. 1 (1986) (noting that “the State may not arbitrarily appropriate property for the use of third parties by stating that the public has ‘paid’ for the property by paying utility bills”).

      [359].     See generally Leo E. Strine Jr., The Dangers of Denial: The Need for a Clear-Eyed Understanding of the Power and Accountability Structure Established by the Delaware General Corporation Law, 50 Wake Forest L. Rev. 761 (2015) (explaining that under Delaware corporate law, the corporation’s priority is the welfare of the shareholder).

      [360].     See Consent to Disclose Utility Customer Data, U.S. Dept. of Energy, https://rpsc.energy.gov/sites/default/files/attachment/c-743_Consent%20to%20Disclose%20Utility%20Customer%20Data.pdf [https://perma.cc/2MA7-M5NK] (this DOE form allows utility customers to consent to use of their data); Moore v. Regents of the Univ. of Cal., 51 Cal. 3d 120, 126–27 (1990) (patient consented to abandon spleen with unique stem cells worth millions to the doctors). But see Borgesius, supra note 59, at 103 (arguing that “obtain[ing] individuals’ consent before using their data for certain goals . . . [is ineffective] as people tend to agree with almost any request they see”).

      [361].     Kugler & Hurley, supra note 11, at 499.

      [362].     See, e.g., Verizon Commc’ns, Inc. v. Trinko, 540 U.S. 398, 411 (2004) (acknowledging that a state has “effective power to compel sharing and to regulate its scope and terms”).

      [363].     Order 888, which mandated transmission access for non-incumbent electricity generators. FERC Order No. 888, 18 C.F.R. Part 35 (1996).

      [364].     See generally Eric Filipink, Serving the “Public Interest” – Traditional vs. Expansive Utility Regulation, Harrison Inst. Pub. L. (NRRI Report 10-02, Dec. 30, 2009) (exploring the contours of the “public interest” in relation to litigation surrounding regulators decisions); Emmett N. Ellis IV, Monica W. Sargent, & Steven C. Friend, The Evolving Public Interest – Recent Decisions in Utility Merger Proceedings, 55 ABA Infrastructure & Regul. Indus. 5 (2016) (analyzing how various public utility transactions were treated under the “in the public interest” requirement); Alexandra B. Klass & Gabriel Chan, Regulating for Energy Justice, 97 N.Y.U. L. Rev. 1426 (2022) (advocating for energy justice as a key part of utilities’ duty to act in the public interest).

      [365].     See generally Max Edelstein, We Need to Regulate Big Data as a Public Utility, Colum. Pol. Rev. (July 3, 2022) https://www.cpreview.org/blog/2022/7/we-need-to-regulate-big-data-as-a-public-utility [https://perma.cc/ADJ9-QRQA] (arguing that data collected by Big Tech companies should be treated as a public good and regulated like public utilities); Jennifer Shkabatur, The Global Commons of Data, 22 Stan. Tech. L. Rev. 354 (2019) (arguing that user generated data should be treated as a “global commons” and provided to independent stakeholders using the data for the benefit of society); David Deming, Balancing Privacy with Data Sharing for the Public Good, N.Y. Times (Feb. 19, 2021), https://www.nytimes.com/2021/02/19/business/privacy-open-data-public.html [https://perma.cc/P8LW-KETA] (reviewing examples where data was made public to improve private companies’ ability to serve the public interest); George Sawyer Springstein, Note, Government Regulation and Monopoly Power in the Electric Utility Industry, Case W. Reserve L. Rev. 240, 242, 260 (1983) (arguing that application of antitrust laws to public utilities is essential, and suggesting that not all functions of the electric utility industry possess the same characteristics to justify antitrust immunity and regulation).

      [366].     Am. Council for an Energy-Efficient Econ., supra note 181. The New Hampshire PUC has issued an order to create a “Multi-Use Energy Data Platform” to facilitate data sharing between regulated utilities, customers, and third parties. Order Approving Settlement and Establishing a Process for Developing a Statewide Data Platform, Docket No. DE 19-197 (N.H. Pub. Utils. Comm’n Mar. 2, 2022); Order Adopting a Data Access Framework and Establishing Further Process, Matter No. 20-00406 (N.Y. Pub. Serv. Comm’n Apr. 15, 2021).

      [367].     66 Pa. Stat. and Const. Stat. § 2807(f)(3) (West 2008). The provision reads, “Electric distribution companies shall, with customer consent, make available direct meter access and electronic access to customer meter data to third parties, including electric generation suppliers and providers of conservation and load management services.”

      [368].     Final Order for Submission of the Electronic Data Exchange Working Group’s Web Portal Working Group’s Solution Framework for Historical Interval Usage and Billing Quality Interval Use, No. M-2009-2092655 (Pa. Pub. Util. Comm’n June 30, 2016).

      [369].     Id. By coupling this requirement with broader state privacy legislation that require anonymity or otherwise address the PUC’s privacy concerns, mandated data sharing could reach even broader constituents like the Mission:data entities of the world.

      [370].     See, e.g., Povacz v. Pa. Pub. Util. Comm’n, 280 A.3d 975, 998, 1014 (Pa. 2022) (recognizing that Pennsylvania’s Public Utility Code mandates the installation of smart meters, which are necessary because they “provide customers with accurate usage and pricing information” and “support the automatic control of a customer’s consumption” by a utility).

      [371].     Jim Lazar, Electricity Regulation in the US: A Guide, the Regulatory Assistance Project 50 (2d ed. July 12, 2016) (explaining the inclusion of these investments in the rate base and the rate of return provided for utilities).

      [372].     Id.

      [373].     Guide to Smart Meters and Opt-Out Fees, Maryland.gov, https://opc.maryland.gov/Consumer-Learning/Electricity/Smart-Meters [https://perma.cc/DSJ9-FFTP] (last visited Mar. 20, 2024).

      [374].     DuckDuckGo is a web browser that advertises never collecting or sharing personal information. See DuckDuckGo, https://duckduckgo.com [https://perma.cc/VA9J-DEET] (last visited Oct. 27, 2023).

      [375].     Individual states grant monopolies to each utility by providing exclusive service territories. State-by-State Information, Am. Coal. of Competitive Energy Suppliers, https://competitiveenergy.org/consumer-tools/state-by-state-links/ [https://perma.cc/3FG8-YG2Z] (last visited Oct. 22, 2023); see also Ben Ho, The Conservative Case for Solar Subsidies, N.Y. Times (Jan. 5, 2016), https://www.nytimes.com/2016/01/05/opinion/the-conservative-case-for-solar-subsidies.html [https://perma.cc/3FG8-YG2Z ] (“[I]n most markets around the country, electricity is still one of the few areas where [consumers] have virtually no choice over [their] supplier.”); Katherine Tweed, Customers Spend 8 Minutes Per Year Interacting Online with Their Utility, Greentech Media (Oct. 27, 2016), https://www.greentechmedia.com/articles/read/customers-spend-8-minutes-a-year-interacting-online-with-their-utility [https://perma.cc/D6SJ-S2YP] (reporting 76 percent of surveyed individuals would consider alternative electricity providers if given the choice).

      [376].     Retail choice is available for both non-residential and residential electric utility customers in the District of Columbia, California, Connecticut, Delaware, Illinois, Maine, Maryland, Massachusetts, Michigan, New Hampshire, New Jersey, New York, Ohio, Pennsylvania, Rhode Island, and Texas. See Can Electric Utility Customers Choose Their Electricity Supplier?, Energy Info. Admin. (Feb. 6, 2024), https://www.eia.gov/tools/faqs/faq.php?id=627&t=3#:~:text=In%202021%2C%20retail%20choice%20was,%2C%20Pennsylvania%2C%20Rhode%20Island%2C%20and [https://perma.cc/N28W-SU9C].

      [377].     See Nat’l Renewable Energy Lab., supra note 160.

      [378].     See, e.g., Povacz v. Pa. Pub. Util. Comm’n, 280 A.3d 975 (upholding PUC denial of consumers’ requests to be exempted from smart meter installations).

      [379].     See, e.g., Paul M. Schwartz & Daniel J. Solove, The PII Problem: Privacy and a New Concept of Personally Identifiable Information, 86 N.Y.U. L. Rev. 1814, 1854 (2011) (“[T]he lack of transparency regarding practices of data collection and tracking creates an asymmetry of knowledge about existing information collection practices between consumers and the organizations that collect information about them. This information asymmetry places consumers at a profound disadvantage.”). One timely example of information asymmetries at work is the family of applications termed “menstruapps.” Menstruapps are smartphone applications that track a user’s reproductive cycle, sexual activity, and health in return for the app’s insights into the user’s body. See Laura Shipp & Jorge Blasco, How Private is your Period?: A Systematic Analysis of Menstrual App Privacy Policies, 4 Proceedings on Priv. Enhancing Tech. 491 (2020), https://petsymposium.org/2020/files/papers/issue4/popets-2020-0081.pdf [https://perma.cc/M5WK-PV8Q]; Leah R. Fowler & Michael R. Ulrich, Femtechnodystopia, 75 Stan. L. Rev. 1233 (2023). As of 2020, there were over 200 million downloads of such apps, with one of the most popular companies projected to be worth $50 billion in 2025.

      [380].     See, e.g., Complaint for Permanent Injunction and Other Relief at 9, Fed. Trade Comm’n v. Kochava, Inc., 671 F. Supp. 3d 1161 (D. Idaho 2022); Borgesius, supra note 59, at 104 (“People rarely know what a company does with their personal data, and it’s difficult to predict the consequence of future data usage.”).

      [381].     Peter J. van de Waerdt, Information Asymmetries: Recognizing the Limits of the GDPR on the Data-Driven Market, 38 Comput. L. & Sec. Rev. 1, 2 (2020); Kugler & Hurley, supra note 11, at 499 (“Most people do not want to read long privacy policies or actively manage their privacy in the consumer sphere.”). In practice, data privacy laws do not solve the information asymmetry problem. See Borgesius, supra note 59, at 105 (“Many people find it hard to stick with a diet or save money due to the immediate gratification. . . . Likewise, if a website has a tracking wall and users can visit the site only if they agree to behavioral targeting, they’re likely to consent, ignoring the risk of future privacy infringement.”).

      [382].     597 U.S. 215 (2022). For example, the Missouri Department of Health and Senior Services was found to keep spreadsheets of women’s periods with the goal of determining if an abortion took place. Katie Reilly, Missouri’s State Health Department Kept Spreadsheet Tracking Menstrual Periods of Planned Parenthood Patients, Time Mag. (Oct. 31, 2019), https://time.com/5713804/missouri-health-official-planned-parenthood-periods [https://perma.cc/CK68-CQPE].

      [383].     Darragh Roche, Why Delete Period Tracking App? Roe v. Wade Ruling Sparks Panic Over Data, Newsweek (June 25, 2022), https://www.newsweek.com/why-delete-period-tracking-app-roe-v-wade-ruling-sparks-panic-data-1719167 [https://perma.cc/B563-5WZR]. The collection of the intimate and personally identifiable information poses monumental autonomy and privacy concerns during a tense political climate.

      [384].     Kari Lydersen, Report: Illinois Utility Fails to Deliver on Smart Meter Benefits, Energy News Network (Dec. 1, 2020), https://energynews.us/2020/12/01/report-illinois-customers-have-not-benefited-from-smart-meters/ [https://perma.cc/93FG-5V23]; Herman K. Trabish, 97% of Smart Meters Fail to Provide Promised Customer Benefits, Util. Dive (Oct. 5, 2022), https://www.utilitydive.com/news/97-of-smart-meters-fail-to-provide-promised-customer-benefits-can-3b-in/632662 [https://perma.cc/PM7L-DGSZ]; see Mission:data, Deactivated: How Electric Utilities Turned Off the Data-Sharing Feature of 14 Million Smart Meters 3 (Sept. 2022), https://static1.squarespace.com/static/52d5c817e4b062861277ea97/t/631253069bdd82629d3ea079/1662145291709/Deactivated_white_paper.pdf [https://perma.cc/Z9T2-AWSM] (“[A]dvanced meters promised to empower consumers in two ways: (1) with access to real-time electric usage information and (2) with access to new energy management tools that analyze interval usage data. . . . However . . . [d]espite 89.7% of federally-funded meters having real-time access capabilities, today only 2.9% are enabled. . . . Furthermore, only 14.3% of customers are offered [the advanced energy management tools].”).

      [385].     Bill LeBlanc, Do Customers Understand Their Utility Bill? Do They Care? What Utilities Need to Know, E Source (Jan. 21, 2016), https://www.esource.com/email/ENEWS/2016/Billing [https://perma.cc/L6SS-YAH8] (reviewing a market research study revealing that customers displayed a low level of understanding of even basic building blocks of their energy bills, despite showing high interest in understanding their data).

      [386].     But see Inst. for Elec. Efficiency, The Costs and Benefits of Smart Meters for Residential Customers 5 (2011), https://www.edisonfoundation.net/-/media/Files/IEI/publications/IEE_BenefitsofSmartMeters_Final.ash [https://perma.cc/YR4G-9B54] (indicating that utility-provided technology, such as smart meters, may provide consumers cost savings).

      [387].     Nat’l Ass’n of Regul. Util. Comm’rs, Value of Customer Data Access: Market Trends, Challenges, and Opportunities 16 (Apr. 2015), https://pubs.naruc.org/pub/536E2D7C-2354-D714-5129-435231D889E0 [https://perma.cc/4QDB-M35T] (identifying operational benefits for utilities and customer benefits such as the ability to avoid peak pricing and take advantage of demand response programs); McChalicher, supra note 192 (explaining how detailed energy data can help with demand side resource program planning, grid planning, and energy forecasting).

      [388].     Utility solicitation for access to more customer data.

      [389].     See, e.g., Smart Meter Texas, https://www.smartmetertexas.com/home [https://perma.cc/94P6-YVCH].

      [390].     Chris Heck, Digital Transformation at Duke Energy (Apr. 24, 2018), https://cdn.osisoft.com/osi/presentations/2018-uc-san-francisco/UC18NA-D1KY07-Duke-Energy-Heck-Duke-Energys-Journey-of-Digital-Transformation.pdf?_ga=2.94888030.330807852.1551196158-1578253251.1454392503 [https://perma.cc/N4QM-FUDB].

      [391].     Duke Energy Progress South Carolina Rate Review Request, Duke Energy, https://www.duke-energy.com/home/billing/de-progress-rates [https://perma.cc/FP8E-P72W].

      [392].     See Payne, supra note 8, at 1006 (emphasizing that the electricity consumer price index is rising faster than the consumer price index for all items, and consumers are being asked to pay for record rates of capital spend for the utilities).

      [393].     Arcadia receives utility data without paying the utilities; instead, it uses customer logins to access the utility website. This is the concept of adversarial interoperability.

      [394].     Cf. Trabish, supra note 384 (“[U]tilities benefited from returns on capital expenditures and reduced operational costs but did not deliver those customer benefits [“in the form of customer savings].”).

      [395].     Arcadia, https://www.arcadia.com/ [https://perma.cc/JZM8-9XT7].

      [396].     See, e.g., Paul Sawers, Arcadia Aggregates Energy Companies to Build Climate-Friendly Products, Raises $200M, VentureBeat (May 10, 2022), https://venturebeat.com/big-data/arcadia-which-aggregates-energy-data-for-companies-to-build-climate-friendly-products-raises-200m [https://perma.cc/BPK9-R9NK].

      [397].     See, e.g., What is Time-of-Use, Silicon Valley Clean Energy, https://svcleanenergy.org/time-of-use/ [https://perma.cc/BMC4-NH3X].

      [398].     See Lydersen, supra note 384 (showing that Illinois utility ComEd garnered $4.7 billion dollars from smart meters while customers paid $1.6 billion more in delivery charges and did not benefit from lower bills).

      [399].     See generally, e.g., Felix Mormann, Clean Energy Equity, 2019 Utah L. Rev. 335 (2019) (arguing for the inclusion of equity considerations in energy policymaking); Shelley Welton & Joel Eisen, Clean Energy Justice: Charting an Emerging Agenda, 43 Harv. Env’t. L. Rev. 307 (2019) (explaining how equity-focused policymaking can prevent clean energy developments from widening societal inequities); Shalanda H. Baker, Anti-Resilience: A Roadmap for Transformational Justice within the Energy System, 54 Harv. C.R.-C.L. L. Rev. 1 (2019) (illustrating policy tools necessary to include people of color and low-income communities in the renewable energy transition).

      [400].     In 2020, 27% of U.S. Households had Difficulty Meeting their Energy Needs, Energy Info. Admin. (Apr. 11, 2022), https://www.eia.gov/todayinenergy/detail.php?id=51979#:~:text=Five%20million%20households%20reported%20that,kept%20at%20an%20unsafe%20temperature [https://perma.cc/4WNE-969A] (stating that in 2020, 27 percent of U.S. households reported insecurity about their energy bill).

      [401].     Short-Term Energy Outlook: Electricity, Coal, and Renewables, Energy Info. Admin. (Mar. 12, 2024), https://www.eia.gov/outlooks/steo/report/electricity.php [https://perma.cc/M4DE-MKK3].

      [402].     Jamal Lewis, Diane Hernández & Arline Geronimus, Energy Efficiency as Energy Justice: Addressing Racial Inequities Through Investments in People and Places, 13 Energy Efficiency 419, 419–32 (2020) (“[According to the U.S. Energy Information Administration, o]ne in three households in the United States is energy insecure . . . . Energy insecurity is defined as the ‘inability to meet basic household energy needs.’”).

      [403].     Chinelo Agbim, Felipe Araya, Kasey M. Faust & Dana Harmon, Subjective Versus Objective Energy Burden: A Look at Drivers of Different Metrics and Regional Variation of Energy Poor Populations, 144 Energy Pol’y 1 (2020) (“In 2015, nearly one-third of households (31%) reported struggling to pay their bills.”); Lewis, supra note 120.

      [404].     See generally Read & Campopiano, supra note 28 (explaining the need for flexibility in public utility regulation to accommodate new technology and environmental changes); William Boyd, Public Utility and the Low-Carbon Future, 61 UCLA L. Rev. 1614, 1632–33, 1698–99 (2014) (discussing the pivotal importance of informed regulatory planning and coordination mechanisms to organize and integrate utility-scale renewables and to improve demand response efficiency, in order to create a “realistic pathway to a low-carbon future” as the technological complexity of the grid increases).

      [405].     See Munn v. Illinois, 941 U.S. 113, 127–30 (1876); see also Fed. Power Comm’n v. Hope Nat. Gas Co., 320 U.S. 591, 611 (1944).

      [406].     Hope Nat. Gas, 320 U.S. at 598.

      [407].     This follows the inverse of the cost-causation principle applied by courts in disputes surrounding the allocation of costs for transmission line projects. In those situations, courts ensure that the “burden is matched with the benefit.” Entergy Ark., LLC v. Fed. Energy Reg. Comm’n, 40 F.4th 689, 692–93 (D.C. Cir. 2022). Here, regulators should ensure that the benefit is matched with its source (ratepayers).

      [408].     See 7 U.S.C. § 3(c)(1)(f). It could even follow another aspect of this program that allows the original data party to have an exclusive-use period of fifteen years before it is required to open its data to competitors.

      [409].     William Lazonick, Profits Without Prosperity, Harv. Bus. Rev. Mag. (Sept. 2014), https://hbr.org/2014/09/profits-without-prosperity [https://perma.cc/PGY4-YKZM].

      [410].     See, e.g., time-of-use pricing and performance-based rates.

      [411].     For example, the federally funded Low Income Home Energy Assistance Program (LIHEAP) provides funds to support direct payments or credit to low-income customers’ energy accounts via the utility. See, e.g., Low Income Home Energy Assistance Program (LIHEAP), Off. of Cmty. Servs. (2023), https://www.acf.hhs.gov/ocs/programs/liheap [https://perma.cc/LX7X-G2Q3]; Utility Bill Help Program, Col. Pub. Util. Comm’n (2023), https://puc.colorado.gov/utilitybillhelp [https://perma.cc/29AQ-7SGR]. Additionally, utilities have long offered rebates for the installation of energy-efficient equipment in a residence or business. Utility Rebates and Incentive Programs, U.S. Dept. of Energy (2009), https://www.nrel.gov/docs/fy09osti/46311.pdf [https://perma.cc/KG9B-A4VY]. These rebates will continue to expand, with $8.8 billion set aside for energy efficiency rebates by the Inflation Reduction Act. About the Home Energy Rebates, Dept. of Energy, https://www.energy.gov/scep/home-energy-rebate-program [https://perma.cc/844X-A8RS].

      [412].     Demand Response Programs, San Diego Gas & Elec., https://www.sdge.com/residential/savings-center/energy-saving-programs/reduce-your-use/demand-response-residential-programs [https://perma.cc/85EN-6EDC].

      [413].     Nat’l Ass’n of Regul. Util. Comm’rs, supra note 387.

      [414].     See, e.g., The Potential of Behavioural Interventions for Optimising Energy Use at Home, Int’l Energy Agency (June 4, 2021), https://www.iea.org/articles/the-potential-of-behavioural-interventions-for-optimising-energy-use-at-home [https://perma.cc/8H34-ZRMW] (explaining how usage data can help energy customers alter habits to reduce consumption).

      [415].     Id.

      [416].     Maria Gallucci, Time-of-Use Electricity Rates May Hit Vulnerable Groups Harder, Study Finds, Inst. of Elec. & Electronics Eng’gs (Dec. 16, 2019), https://spectrum.ieee.org/time-of-use-rates-may-hit-vulnerable-groups-harder [https://perma.cc/3LMN-84Z2].

      [417].     Puget Sound Energy (PSE) in Washington State launched an education-and-outreach program to increase consumer awareness of electric vehicle options and to drive adoption in the state. Patty Durand, Three Utility Programs That Are Empowering Consumers, Energy Cent. (Apr. 27, 2020), https://energycentral.com/c/cc/three-utility-programs-are-empowering-consumers [https://perma.cc/ESZ7-8GMC].

      [418].     See, e.g., Colo. Rev. Stat. Ann. §§ 40-3-106(c)-(d) (West 2023) (allowing Colorado PUCs to grant lower rates to low-income households and to approve classifications that would grant a preference to low-income customers); Or. Rev. Stat. Ann. § 757.072 (West 2023) (permitting Oregon’s public utilities to enter agreements with PUC-authorized organizations and offer reduced rates to low-income customers or environmental justice community members).

      [419].     See, e.g., Letter by Matthew J. Christofferson, Advice Letter No. 20, Black Hills Energy (May 31, 2022), https://www.blackhillsenergy.com/sites/blackhillsenergy.com/files/cog_22_advice_20.pdf [https://perma.cc/58WY-7VRT] (filings to decrease its demand-side management cost adjustment for retail customers in 2019, which would decrease its “annualized revenues by $1.542 million” while increasing it for nonresidential customers). Eversource Energy decreased its energy service rates in 2022, with approval of the New Hampshire PUC. Order Approving Adjustment to the Energy Service Rate For Effect on February 1, 2023, Order No. 26,747 (N.H. Pub. Util. Comm’n Dec. 14, 2022), https://www.puc.nh.gov/Regulatory/Orders/2022orders/Documents/22-021_2022-12-14_nhpuc_order-26747.pdf [https://perma.cc/C8E2-WGBZ].

      [420].     For instance, without sufficient anonymization, such a proposal could backfire if lower income ratepayers do not appreciate the value of their data and more willingly share it without sufficient privacy protections for much less than it is worth.

      [421].     See H. Hovenkamp, Antitrust and Platform Monopoly, supra note 10, at 2006.

      [422].     See, e.g., Joshua Partow, Arizona City Cuts Off a Neighborhood’s Supply Amid Drought, Wash. Post (Jan. 16, 2023), https://www.washingtonpost.com/climate-environment/2023/01/16/rio-verde-foothills-water-scottsdale-arizona/ [https://perma.cc/H9NR-2NXQ].

      [423].     Based on Data Access, Am. Council for Energy Efficiency, https://database.aceee.org/state/data-access [https://perma.cc/BT7K-T5DD].