Yang Li
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Yang Li, Ph.D. |
Contact
Room 525, Power and Energy Building, Northeast Electric Power University, Jilin, China
Tel: (86) 159-4796-6691
Email: liyang@neepu.edu.cn
Chinese Homepage: http:ee.neepu.edu.cninfo1204/3846.htm
Openings for PhD/master students: I am looking for self-motivated Ph.D./Master students to work with me. If you are interested. Please feel free to drop me an email with your CV, transcript and publications (if any).
Research Interests
My research interests include
Wind and solar dispatch
Distributed generation planning and control
Uncertainty modeling and analysis
Energy storage/EV integration
Optimization of integrated energy systems
Integrated demand response
AI-driven power system analysis
Federated Learning
Find me on: Google Scholar Profile, ORCiD, ResearchGate, and Publons.
News & Updates
6/2023, our paper titled “Output voltage response improvement and ripple reduction control for input-parallel output-parallel high-power DC supply” was accepted by IEEE Transactions on Power Electronics.
6/2023, our paper titled “Renewable energy absorption oriented many-objective probabilistic optimal power flow” was accepted by IEEE Transactions on Network Science and Engineering.
6/2023, our paper titled “Collaborative optimization of multi-microgrids system with shared energy storage based on multi-agent stochastic game and reinforcement learning” was accepted by Energy.
6/2023, our paper titled “Editorial: Rising stars in energy research: 2022” was accepted by Frontiers Energy Research.
4/2023, our paper titled “Image encryption for offshore wind power based on 2D-LCLM and Zhou Yi Eight Trigrams” was accepted by International Journal of Bio-Inspired Computation.
4/2023, Our paper titled “Multi-microgrid collaborative optimization scheduling using an improved multi-agent soft actor-critic algorithm” was accepted by Energies.
3/2023, Dr. Li was named on the Highly Cited Chinese Researchers list of 2022 by Elsevier.
2/2023, Our paper titled “Demand response method considering multiple types of flexible loads in industrial parks” was accepted by Engineering Applications of Artificial Intelligence.
1/2023, Our paper titled “Data-Driven distributionally robust scheduling of community integrated energy systems with uncertain renewable generations considering integrated demand response” was accepted by Applied Energy.