The increasing penetration of distributed energy resources (DERs) brings opportunities and challenges to the operation of power distribution systems. Conventionally, the DER hosting capacity of a local electric power system is commonly represented as a static value that is determined by evaluating DER’s impacts on grid reliability considering “worst-case” conditions, resulting in a conservative DER integration and  underutilization of grid infrastructure. However, hosting capacity is not a static value as it is dependent on the coincidence of DER generation and load demand that vary over time. Dynamic Operating Envelopes (DOEs) establish upper and lower operational bounds for DERs over a given time period, within which they can operate without adverse grid impacts, thus unleashing the full potential of grid infrastructure and maximizing the DER integration. This talk will introduce an industry-accepted model to optimize DOEs, which has been integrated into major distribution system management software. Due to the non-convex nature of power flow model, the optimization of DOEs faces a challenge of balancing solution accuracy and computational efficiency. We propose an AI-assisted constraint embedding method that convexifies the problem by replacing power flow equations with trained input convex neural networks (ICNNs). We compare its performance with two conventional optimization methods, i.e., gradient descents and linearization, under various operating scenarios.

Bio

Zhaoyu Wang received the BS degree in electrical engineering from Shanghai Jiao Tong University, & PhD degree in electrical and computer engineering from Georgia Institute of Technology. Since 2015, he has been assistant, associate, and full Professor at Iowa State University. Dr. Wang is a Fellow of IEEE and an IEEE Power and Energy Society (PES) Distinguished Lecturer. He was the recipient of the National Science Foundation CAREER Award and the IEEE PES Outstanding Young Engineer Award. He was listed as a Highly Cited Researcher by Clarivate (Web of Science). Dr. Wang’s research interests include optimization and data analytics in power distribution systems and microgrids. He has been the lead Principal Investigator for over $24M projects funded by multiple federal agencies. He is leading an Energy Department-funded project that converts the entire City of Montezuma to be the very first utility-scale microgrid in the State of Iowa. He has published more than 135 papers in top-notch journals and has won 10 best paper awards. Dr. Wang is the Vice Chair of IEEE Power System Operation, Planning and Economics (PSOPE) Committee and the Chair of IEEE Distribution System Operation and Planning Subcommittee. He has been an Associate Editor of IEEE Transactions on Sustainable Energy, IEEE Transactions on Power Systems, IEEE Transactions on Smart Grid, and IEEE Power Engineering Letters.