Dr. Runjia SUN | Author
He is currently an associate research fellow in the Key Laboratory of Power System Intelligent Dispatch and Control of Ministry of Education, Shandong University, Jinan, China.
He is currently an associate research fellow in the Key Laboratory of Power System Intelligent Dispatch and Control of Ministry of Education, Shandong University, Jinan, China.
The rapid growth of photovoltaic (PV) power generation is recognized as a key solution for climate mitigation and future energy demands.
A high-quality set of typical scenarios is significant for power grid planning. Existing construction methods for typical scenarios do not account for the spatiotemporal correlations among renewable
Runjia SUN has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States
Runjia Sun (S''18) received the B.E. degree in electrical engineering in 2015 from Shandong University, Jinan, China, where he is currently working toward the Ph.D. degree with the School of Electrical
A hybrid reinforcement learning (HRL) method combining offline self-learning with online Monte Carlo tree search (MCTS) is designed to deal with the strong uncertainty induced by wind power
A network reconfiguration approach for power system restoration based on preference-based multiobjective optimization Runjia Sun Key Laboratory of Power System Intelligent Dispatch
He is currently an Associate Research Fellow with the School of Electrical Engineering, Shandong University. His research interests include power system restoration and artificial intelligence
My research interest lies in consistent, physically-plausible, and interactive video generation. Thank Jon Barron for sharing his website''s source code.
Runjia Sun, Yutian Liu, Hainan Zhu, Rasoul Azizipanah-Abarghooee, Vladimir V. Terzija: A network reconfiguration approach for power system restoration based on preference-based multiobjective
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