Humanity’s reliance on the power grid is increasing with each passing year.  As a society, we are lulled into a sense that things will work simply by paying the monthly bill, and when these massive systems break down – as they have after numerous recent natural disasters -- we realize how much being connected to the grid shapes our lives.  In the aftermath of repair efforts, we also realize how much work it actually takes to keep the power on.

Addressing the critical need for more reliable and secure power, a multidisciplinary research team at Stony Brook led by Peng Zhang, SUNY Empire Innovation Professor in the Department of Electrical and Computer Engineering, is working to develop and demonstrate techniques for AI-enabled resilient network microgrids (AI-Grids) that will help improve the day-to-day reliability of the power grid and enable easier and faster power restoration after outages.  AI-Grid has the potential to transform today’s community power infrastructures into tomorrow’s autonomic microgrids and flexible services immune to cyber-attacks and other disastrous events. AI-Grid also has the potential to benefit various commercial sectors as well as the military. 

“Building on prior work, this project aims to develop AI-Grid which will address key barriers to enable coordinated scalable distributed energy systems,” said Zhang. “The team has a unique opportunity to deploy a field demonstration at the Energy & Information Park (EIP) in New Britain, CT.

The project is funded by a $1 million grant from the National Science Foundation (NSF) Convergence Accelerator program, which supports use-inspired, team-based, multidisciplinary efforts that address challenges of national importance and will produce deliverables of value to society in the near future. The broader impact and potential societal benefit of this Convergence Accelerator project is to develop coordinated networked microgrids (NM) that have the potential to help restore neighboring distribution grids after a major blackout.  The collaboration among faculty in Stony Brook’s College of Engineering and Applied Sciences will develop techniques for AI-enabled resilient NMs that will be tested at the EIP.

The project integrates several important AI directions into current networked microgrids research and includes experts from multiple disciplines. The team will build a programmable platform to enable scalable, self-protecting, autonomic and resilient networked microgrids to coordinate scalable distributed energy systems. Research areas cover continuous-depth deep neural networks, reachability analysis, formal control, and cybersecurity technologies. The proposed AI-Grid will be built on top of smart programmable microgrid technologies funded by four NSF programs.

In addition to Zhang, co-Principal Investigators include Scott Smolka and Scott Stoller in the Department of Computer Science, and  Xin Wang in the Department of Electrical and Computer Engineering. The four PIs will team with experts from Brookhaven National Lab (BNL), EIP, RTDS, Eversource, CCAT, ISO New England, New York Power Authority (NYPA), PSEG Long Island, and Worcester Polytechnic Institute (WPI) on the project. Multiple state and industry partners will also participate.

“The team has the breath and expertise to  lead transformational work on a technology that will benefit all of us in the near future,” said Robert Kukta, Acting Dean, College of Engineering and Applied Sciences. “I congratulate Peng Zhang for assembling an extraordinary multidisciplinary team and look forward to great things to come.”

Zhang said the end-goal of this project is to achieve cyber-physical resilience with AI-Grid. 

“This project demonstrates the convergence of power engineering, artificial intelligence, formal methods, and wireless networks and mobile computing communities,” he said. “Improvement on power systems can significantly and equally benefit both science and society.”