EPRI-led Open Power AI Coalition Aims to Drive Grid Modernization through Data Sharing

The combination of power system modernization and artificial intelligence (AI) is being hindered by a lack of system data available for AI training—a judgment that has reached consensus among experts in the technology and power industry.

"Data is to AI what oil, natural gas, wind, and solar energy are combined." Alexandr Wang, founder and CEO of Scale AI, a leader in the technology market, testified before the U.S. House Energy and Commerce Committee on April 9, "Every major AI advancement is built on data shaped by human expertise," and "to win in AI, you must turn data assets into an advantage."

Power industry executives and analysts also agree that utilities want to gain an edge with AI.

"The grid is one of the most complex machines on Earth," and "it is already ready for digitalization," said Shinjini Menon, senior vice president of system planning and engineering at Southern California Edison. She added that because "there is not enough time, money, or resources on Earth" to continue with past practices, the data supporting digitalization is crucial.

To break down data accessibility barriers, the power and technology industries have joined forces to establish the "Open Power AI Consortium," led by the Electric Power Research Institute (EPRI). Meanwhile, regulation and technological innovation are opening the door to data access. But experts told Utility Dive that serious disagreements over cybersecurity and utility customer rights remain to be resolved.

What data, and why it is needed

Many stakeholders view new AI capabilities as tools to address the vast scope and complexity of the power system.

"This is not your grandfather's AI—it is not just machine learning, but it still needs data to learn," said Arshad Mansoor, president and CEO of EPRI. He added that this data "comes from diverse sources, including regional system operators, utilities, research institutions, private equipment manufacturers, third-party analytics firms, and cloud and software providers."

"It is estimated that 95% of data is locked behind utilities' cybersecurity and customer privacy barriers," added Swati Daji, executive vice president and chief financial, risk, and operations officer at EPRI. EPRI's Open Power AI initiative will "create, develop, and curate datasets as an open solution repository for the entire industry."

The initiative will also establish "sandboxes for testing and validating use cases," and "feedback loops for sharing lessons learned," said Swati. Data in the open repository can be integrated with utility protected data for further AI modeling; as grid modernization advances, utilities will be better able to manage the rare peak demands that drive huge expenditures, she added.

Another initiative is the "One Digital Grid Platform," developed by component manufacturer Schneider Electric in collaboration with Microsoft and data provider Esri, serving as a "grid data hub," said Ruben Llanes, CEO of Digital Grid at Schneider Electric. The platform will "ingest data from utility smart devices" and "enable real-time insights, predictive analytics, and automation," he added.

Both initiatives will enhance utilities' ability to use AI-driven data from grid-edge intelligence to "break down customer energy usage behavior and coordinate flexible consumption," said Menon. But this will require "distribution system investments in lines, software, and communication technologies," she added.

If planned holistically, "incremental investments in control room and system edge technologies can keep upgrade costs affordable," said Menon. AI-enabled utility systems "might be able to complete 10 million calculations in the time it currently takes to complete 10,000," which would support "more comprehensive planning and more granular real-time system operations," she added.

Even with an expected 15 million customer-owned smart devices on Southern California Edison's system by 2045, AI tools can monitor system data "and flag where critical decisions are needed to human operators," said Menon.

Policy is accelerating to promote greater data access for all power system stakeholders.

Policies driving data access

Data access has become the subject of recent federal, state, and utility policy initiatives.

At the federal level, a bipartisan AI framework proposed in 2023 by Senators Richard Blumenthal (D-CT) and Josh Hawley (R-MO), and the PREPARED for AI Act introduced last year by Senators Gary Peters (D-MI) and Thom Tillis (R-NC), both include data protection and sharing provisions, but neither has passed.

However, according to the latest state policy action update from the North Carolina Clean Energy Technology Center, in 2024 utilities and regulators continued to address customer data access issues for advanced metering infrastructure (AMI) at the state level.

According to the 2023 National Association of Regulatory Utility Commissioners (NARUC) Grid Data Sharing Playbook, all power system data can be shared, but personally identifiable customer data, demographic data, or program participation data cannot be shared. The playbook adds that data access can yield system benefits, limit negative impacts, and clarify the distinction between "essential data" and "nice-to-have data."

Both grid data and customer data access are problematic, said Chris Villarreal, founder and president of consulting firm Plugged-In Strategies and co-author of the playbook. The practices in the playbook can accelerate distributed energy resource (DER) interconnection and drive economy-wide electrification by speeding up data access, providing transparency, and necessary customer data protections, he added.

Several states are undertaking significant data sharing policy work.

According to a recent Brattle Group assessment for New York's "Future Grid" proceeding, New York's 2040 grid flexibility potential could avoid nearly $3 billion in annual power system costs. But realizing this flexibility potential "will require massive amounts of data, some of which is not currently measured or available," said Akhilesh Ramakrishnan, associate director of energy management at Brattle and co-author of the study.

Utilities must invest to "measure and collect" data and establish "a single point of interaction and unified data formats" to simplify access, Ramakrishnan added.

In the first phase of the California Public Utilities Commission's R. 22-11-013 planning proceeding (for DER growth), a data working group has been established to improve data access. The working group will "develop rules and requirements for data access," including accuracy standards, customer privacy, and utility compliance with regulatory requirements, the working group said.

Accessible real-time data will enable all available resources "to be used to balance supply and demand without spending hundreds of billions of dollars on system upgrades," said Jon M. Williams, CEO of distributed battery provider Viridi.

In Massachusetts, lawmakers recently passed Senate Bill 2967, which requires "implementation of advanced metering data access protocols." DER advocates support the law, but utilities want regulatory adjustments.

Eversource Energy "fully supports" data access and recommends "a common statewide portal using a virtual central data repository" rather than "legacy databases" that could "duplicate costs" and create "security vulnerabilities," said Jared Lawrence, senior vice president of customer operations and digital strategy and chief customer officer at Eversource.

In Minnesota, regulators approved "open data access standards" and approved a $563.7 million grant for Xcel Energy to deploy smart meters and supporting wireless communications, said Annie Levenson-Falk, executive director of the Citizens Utility Board.

Utilities are also required to "collect and share aggregated or anonymized, disaggregated customer energy usage data," said Levenson-Falk. But Xcel rejected the first such data request, citing potential threats to customer privacy or security, and that rejection is currently being challenged, she added.

Other key state efforts are advancing in New Jersey, Arkansas, Illinois, and the District of Columbia.

A common focus of these proceedings is using AI-managed distribution system data to integrate aggregated DERs and virtual power plants (VPPs) into system operations.

Distribution system data is key

Stakeholders increasingly agree that investments in DER management systems (DERMS) are essential to access, share, and use distribution system data.

According to a white paper released by the Smart Electric Power Alliance (SEPA) in April, each of the two types of DERMS is "a collection of multiple software systems that interact with utility operations and information technology systems and business processes." Combined, they can "enable a new paradigm of grid operations," and "no single software system can provide this capability," the white paper said.

Edge DERMS "manage a large number of behind-the-meter DERs of various types from multiple DER manufacturers, such as batteries, thermostats, and electric vehicles," said SEPA. Grid DERMS "are tightly interconnected with utility distribution operations systems, focusing on managing larger front-of-the-meter DERs and aggregated customer-owned DERs," it added.

"More actively managing and integrating DERs can improve grid reliability, power quality, and system resilience, and create economic value for utilities and customers," said SEPA. And "uncoordinated DERs can increase system peak demand, cause distribution system overloads or voltage violations, and increase the risk of cascading outages," it added.

Grid DERMS costs can range from approximately $10 million to $20 million, while edge DERMS are typically under $10 million, depending on the complexity of the utility system, said Lakin Garth, senior director of grid strategy at SEPA and co-author of the white paper.

If DERMS can provide compelling system data, utilities will be able to use DER aggregation and VPPs to provide the same flexible system services as other dispatchable resources—utilities, DER advocates, and analysts agree.

Edge DERMS are already disaggregating behind-the-meter customer energy usage to address peak demand challenges and alleviate distribution system upgrade needs, said Jesse Demmel, chief technology officer at Uplight, a DER aggregator and edge DERMS provider.

"The data needed to provide more services is available, but it is siloed across utility planning, operations, and customer service departments, making it difficult to integrate into a single platform," Demmel added.

By investing in DERMS, emerging AI modeling can integrate "single-pane" platforms that provide visibility connecting customers and utility control rooms, said Demmel. These investments will pay for themselves by using data to identify the most cost-effective upgrades, he added.

"DERMS investments are absolutely necessary, along with investments in hardware, operations, and measurement technologies," and "DERs will benefit the system," agreed Brattle's Ramakrishnan. However, AI may not fully resolve utility concerns about safety or reliability, because blaming operator decisions on AI recommendations "will not satisfy regulators or customers," he added.

Plugged In Strategies' Villarreal agreed. AI "may enhance system modeling capabilities, but integrating all resources into a single one will be expensive and computationally complex," he said.

However, AI operating at the distribution system level might eliminate data sharing concerns because "it will follow the power flow to the data it needs to optimize system resources and demonstrate why that data should be accessible," Villarreal added.