Scholars propose policies to improve transparency and accountability in the energy system.
Imagine that a data center seeks to connect to the energy grid. The center’s developer, seeking the lowest rate for its electricity needs, canvasses multiple electric utilities to find the best possible deal. But utilities often keep the terms of those deals private, leaving ratepayers such as homeowners, communities, and schools to pay more for their electricity.
In a recent article, Heather E. Payne and Joel B. Eisen argue that utilities and regulators consistently withhold—or even deliberately obscure—critical energy data. They explain that this obstruction can reduce public participation, undermine procedural fairness, and reinforce structural inequalities in the energy system. Payne and Eisen suggest that, with smart policy choices, energy data can instead serve as a tool to promote equality and empower ratepayers.
What exactly is energy data? According to Payne and Eisen, the term refers to a massive conglomerate of data that includes energy consumption data for individual consumers, utility operating costs, grid performance information, developer contracts, and reliability details, among other data. Payne and Eisen identify two separate categories of energy data: personal data, which is data that individuals can currently access and monitor, and system data, which is data that supports the broader grid’s functioning and is often hidden from consumers.
Although utilities, agencies, and third parties are constantly harvesting and using this “tsunami” of energy data, Payne and Eisen note that policymakers rarely view such energy system actors as data powerhouses. They challenge the prevailing view that amassing energy data is apolitical and impersonal. Instead, they argue that utilities and service providers often use energy data to seize market advantages by leveraging algorithms and creating barriers that minimize accessibility and accountability.
To illustrate the shortcomings of energy data management, Payne and Eisen analyze four individual use cases that focus on different types of energy data.
First, Payne and Eisen identify the increasing use of algorithms by utilities to determine customer offers and to make decisions about blackouts and events requiring a reduction in energy demand from customers to maintain power to the grid. Utilities hide these algorithms from customers and select algorithms without regulatory oversight or public input. Payne and Eisen suggest that this type of governance reinforces structural inequalities and has potentially life-threatening consequences for vulnerable populations.
Second, Payne and Eisen observe that virtual energy resources—resources outside a utility’s direct control, such as community solar installations—generate significant amounts of energy data that disproportionately benefits utilities. As an example, Payne and Eisen scrutinize demand response programs, which involve managing electricity consumption by shifting or reducing use during high-demand periods. Customers can receive bill credits by participating in these demand response programs, usually by curtailing their energy use during high-demand periods. Payne and Eisen argue, however, that because utilities retain exclusive access to demand response data, consumers are unaware that their curtailment provides much more value to the utility than they receive back in credits.
Third, utility rate cases—in which utilities determine how much they should charge customers—rely on a “mammoth” amount of usage data to determine the appropriate rates, explain Payne and Eisen. They note that utilities often present usage data in the aggregate or protect data as confidential or highly sensitive information, limiting scrutiny. Payne and Eisen suggest that this practice enables utilities to control the narrative in rate cases, limiting advocates’ and consumers’ ability to determine whether rates are just and reasonable.
Finally, Payne and Eisen evaluate environmental data associated with electricity generation, including power plant emissions. These data are critical for addressing the impacts of air pollution in low-income and minority neighborhoods, yet such communities frequently lack access, as Payne and Eisen observe. The resulting emissions, which utilities justify as necessary to maintain grid reliability and support the economy, carry serious health and climate consequences that are hidden from the general public.
Payne and Eisen posit that, to ensure that the benefits of energy data are equitably distributed and that consumers have greater control over their data, regulators must prioritize meeting two core conditions. First, consumers must have greater access to utility data, especially utility data that ratepayers are already paying for. Second, consumers must be able to scrutinize and contest the quality and application of data.
To achieve these conditions, Payne and Eisen offer two major policy proposals to improve public visibility and utility accountability.
To start, Payne and Eisen propose making all utility data public. They explain that investor-owned utilities are paradoxical—they are supposedly organized and operated in the public interest but must chase profits for their shareholders. By requiring utilities to disclose their energy data, community groups and advocates can better participate in regulatory processes that affect rates, set air pollution levels, and manage climate change impacts.
Several states have begun implementing legislation to require utilities to provide additional reporting and to limit improper lobbying. Yet Payne and Eisen argue that states and utility commissions must go further and presume that all data that could affect a customer’s rate must be made public and accessible.
Payne and Eisen next propose creating neutral, stand-alone entities that they call “independent distribution system operators (IDSOs).” Payne and Eisen note that these entities can serve as neutral coordinators between aggregated virtual energy resources and the broader grid. Although utilities would continue to own the physical infrastructure, an IDSO would handle the day-to-day operations, planning, and updates for the electricity grid as a whole. In Payne and Eisen’s view, the IDSO framework would enable a centralized intermediary to aggregate and standardize electricity distribution data, ensuring transparency and accountability.
Payne and Eisen conclude by reinforcing the urgent need to achieve energy data justice through institutional reform. They envision a “more inclusive and accountable energy future,” achievable through the democratization of energy data to support a transition to clean energy and improve consumer participation in energy markets.
