CAR Research Seminar with Dr. Zongjie Wang, University of Connecticut

Enabling Sustainable Power Systems Through Innovations in Optimal System Dispatch 

Renewable energy sources including wind farms and solar sites, have been rapidly integrated into power systems for both economic and environmental reasons. Unfortunately, many renewable energy sources suffer from variability and uncertainty, which may jeopardize real-time power balancing as well as the security and stability of the power system. It is therefore necessary to develop new solutions to manage the increasing supply-side uncertainty within operational strategies. In current advanced power system operations, the optimal power flow (OPF) is essential to all stages of the system operational horizon, underlying both day-ahead scheduling and real-time dispatch decisions. The dispatch levels determined are then implemented for the duration of the dispatch interval, with the expectation that frequency response and balancing reserves are sufficient to manage intra-interval deviations. To achieve more accurate generation schedules and better reliability with increasing renewable resources, the OPF must be solved faster and with better accuracy within time intervals. In answer to this need, this work proposes a progressive period optimal power flow framework (PPOPF) that is integrated into an overall dispatch control hierarchy. Simulation case studies on a practical PEGASE 13,659-bus practical system in Europe demonstrate the effectiveness of the proposed PPOPF approach within multi-stage power system operations.    

Dr. Zongjie Wan

Dr. Zongjie Wang is a research associate in Systems Engineering at Cornell University. She earned her Bachelors, Masters, and Ph.D. degrees in Electrical and Computer Engineering at Harbin Institute of Technology (HIT), China. She received her Ph.D. training through a joint program provided by Electrical and Computer Engineering at both Cornell University and HIT. Dr. Wang’s research interests focus on problems in modern power systems and renewable energy through leveraging data analytics, optimization and simulation techniques. Her projects include development of new algorithms for optimal power flow in power systems with high penetration of renewable energy sources; bi-level optimization between transmission and distribution systems; comprehensive modeling of distributed generators in active distribution systems; network equivalent modeling of New York state power system topology; feasible power flow solutions in weakly-meshed active distribution systems, sensitivity analysis of new extended bus types in power systems. Dr. Wang has a patent “online multi-period power dispatch problems” filed by U.S. in 2020. As an invited speaker, she gave one of her talks at the headquarter of US Federal Energy Regulatory Commission (FERC)’s Technical Meeting in DC. She is also a member of PSERC committee and has collaborations with power system operators in the industries and other institutions, for example, New England ISO, New York ISO, MIT, Ohio State University, Technical University of Denmark.  

Dr. Wang teaches graduate-level courses in the department of Civil and Environmental Engineering at Cornell University. Her teaching approach is hands-on and interactive, using case-based model development. Dr. Wang’s courses are CEE5930 Data Analytics for Engineering Management and CEE6020 Energy and Water Resources Systems Seminar.