Renewable Power System Optimization

Dr. Jiajia Chen received his B.E. degree in Mathematics and Applied Mathematics from Linyi University, Linyi, China, in 2010, and the Ph.D. degree in Electrical Engineering from South China University of Technology, Guangzhou, in 2015. Since Jan. 2016, Dr. Chen has been in School of Electrical and Electronic Engineering, Shandong University of Technology, as an Associate Professor.Dr. Chen focuses on the research of renewable power system operation and control. His recent research interests include key technologies and applications of energy storage, flexibility and resilience enhancement of smart grid, demand side management and power pricing, operation and control of agricultural network, etc. Since 2024, Dr. Chen has published 50 peer-reviewed technical papers in international journals and conferences. He is a member of IEEE, Deputy Secretary-General of Shandong Electrical Technology Society and the Young Editorial Board of 'Electric Power Construction' Journal, and served as a reviewer of several international journals. He was One Best Paper Awards at the IEEE 6th International Conference on Energy, Electrical and Power Engineering in 2023. Dr. Yuanzheng Li received the M.S. degree in electrical engineering from the Huazhong University of Science and Technology, Wuhan, China, in 2011, and the Ph.D. degree in Electrical Engineering from the South China University of Technology, Guangzhou, China, in 2015. Since Sep. 2015, Dr. Li has been in School of Artificial Intelligence and Automation, Huazhong University of Science and Technology, as an Associate Professor.Dr. Li focuses on deep learning, reinforcement learning, smart grid operations, optimal power system/microgrid scheduling and decision-making, stochastic optimization considering large-scale integration of renewable energy into the power system, and multiobjective optimization. Since 2024, Dr. Li has published more than 100 peer-reviewed technical papers in international journals and conferences. He is a Senior Member of IEEE.

• Introduction for renewable power system optimization.- Distributionally Robust Unit Commitment with Enhanced Sisjointed Layered Ambiguity Set.- Downside Risk to Low-carbon Multi-energy System Optimization.- Multi-step Reconfiguration with Many-objective Reduction for Renewable Distribution System.- Credibility Theory Based Fuzzy Chance Constrained AC OPF for Renewable Power System.- Multi-energy Hub Optimization to Enhance Resilience of Renewable Agricultural Microgrid.- Continuous-time Optimization to Improve Demand Defense of Renewable Industrial Park.- Random Clustering and Dynamic Recognition Strategy for Energy Storage System Optimization.- Mobile Energy Storage System Optimization with Peer-to-peer for Resilience Improvement.