On September 5, "Deep Reinforcement Learning for Smart Grid Operations: Algorithms, Applications, and Prospects", the research finding jointly achieved by Professor Yang Tao of NEU and Academician Chai Tianyou in cooperation with Fellow Mohammad Shahidehpour of Illinois Institute of Technology, Professor Zeng Zhigang, Associate Professors Li Yuanzheng and Yu Chaofan of Huazhong University of Science and Technology has been accepted and published by Proceedings of IEEE, a top journal in the field of engineering. It is learned that this is the first paper accepted by Proceedings of IEEE in our university.
Proceedings of IEEE provides in-depth reviews, overviews, and outlooks on technical developments in electrical engineering, electronics, and computer engineering and computer science. The journal excels in metrics such as Impact Factor and Article Impact Score, and is a top journal in the field of engineering, trusted by researchers and engineers around the globe, publishing only about 100 papers per year.
The paper provides a comprehensive review and outlook of deep reinforcement learning and its applications in smart grid operations, providing a detailed overview of deep reinforcement learning from basic concepts to advanced models, and reviewing various deep reinforcement learning techniques and their extensions to address problems arising in smart grids, including optimal scheduling, operation and control, power markets, and other emerging areas; application-oriented research on deep reinforcement learning in smart grids is conducted, and the focus and difficulties of future research are pointed out; the main challenges, possible solutions, and future research directions for deep reinforcement learning applications in smart grids are discussed.
