Creating a More Resilient Energy Grid Through Artificial Intelligence

An AI-Grid prototype that is being built by the research team. Credit: Stony Brook Power Lab

Stony Brook University professor Peng Zhang, a SUNY Empire Innovation professor in the Department of Electrical and Computer Engineering, is leading a statewide team of collaborators in developing “AI-Grid,” an artificial intelligence-enabled, autonomous grid designed to keep power infrastructure resilient from cyberattacks, faults and disastrous accidents.

The work is part of the National Science Foundation’s (NSF) Convergence Accelerator Program, which supports and builds upon basic research and discovery that involves multidisciplinary work to accelerate solutions toward societal impact.

In September 2020, the program launched the 2020 cohort, which included AI-Grid as a phase 1 awardee and grant funding of a $1 million to further AI-Grid research from an idea to a low-fidelity prototype. The Convergence Accelerator recently selected teams for phase 2, to focus on expanding the solution prototype and to build a sustainability plan beyond the NSF funding. Under phase 2, a new $5 million NSF cooperative agreement will fund the AI-Grid project.

“This project led by Professor Zhang is a great example demonstrating the impact of this novel research on essential infrastructure that we rely on daily, and defines a pathway for enhancing the resiliency and security of our electrical grid systems,” said Stony Brook University Vice President for Research Richard J. Reeder.

“We expect to show that our AI-Grid solution is affordable, lightweight, secure and replicable, thus offering what could be unprecedented flexibility for an approach to transform today’s infrastructures into tomorrow’s autonomous AI-Grid,” said Zhang, the project’s principal investigator. “This project will demonstrate AI-Grid’s capability to empower our nation’s digital economic engines, relieve the pains of those communities suffering from high electricity costs, and knock out low energy reliability and poor resilience.”

Peng Zhang

According to Zhang, the program includes a broad multidisciplinary team of researchers and many academic and industry partnerships key to its success. The AI-Grid team has established more than 30 partnerships that include power utilities, independent system operators, local and state government, industry and university researchers. Zhang said these partnerships have significantly advanced the technology involved in the work that now includes various deep learning methods, online distribution control, encrypted control, active fault management, and a fully programmable microgrid platform.

“The technologies that Peng and his team are developing come at a critical time as the nation pivots toward renewable energy and the inevitable impact it will have on the grid in the coming decade,” said College of Engineering and Applied Sciences (CEAS) Interim Dean Jon Longtin. “This kind of multidisciplinary collaboration strengthens our research enterprise, while demonstrating to our students how complicated problems are solved in the modern world.”

Collaborative work at Stony Brook includes faculty and students in the Department of Electrical and Computer Engineering and the Department of Computer Science, in conjunction with scientists, engineers and stakeholders affiliated with the Advanced Energy Research and Technology Center (AERTC), and with those from Brookhaven National Laboratory, EIP, RTDS, Hitachi America, Eversource, CCAT, ISO New England, New York Power Authority, PSEG Long Island and Worcester Polytechnic Institute.

Stony Brook co-investigators include Scott Smolka, Scott Stoller, Xin Wang and Yifan Zhou. They will work with Zhang to deploy AI-Grid in the field and verify its replicability and universality at three of the most representative networked microgrid sites in the U.S.

“A convergence approach is essential to solving large-scale societal challenges, which is why the NSF Convergence Accelerator requires our funded teams to include a wide-range of expertise from academia, non-profits, industry, government and other communities,” said Douglas Maughan, head of the NSF Convergence Accelerator program. “The merging of ideas, techniques and approaches combined with human-center design concepts assists our teams in accelerating their ideas toward solutions within three years.”

Most recently, the AI-Grid team established end-user partnerships with Energy and Innovation Park, a fuel cell grid-connected energy project in Connecticut; Epic Institute, a global climate solutions organization that also manages The Plant — an old coal power plant being redeveloped into a global climate exhibition and convention center in New York City; and the Commonwealth Edison (ComEd) owned Bronzeville Community Microgrid (BCM) in Chicago.

These end-users will test, demonstrate and ideally implement the technology. The team will develop an open-access AI-grid technology platform with industry partners.