Prof. Huaiguang Jiang
Institute Southern University of Science and Technology Date & Time Date: 29 Oct. 2024 Time: 13:30-14:20 Zoom ID: 979 6747 7915 Passcode: 123456
The modern energy system breaks through the dependence on traditional fossil fuel, integrates various forms of renewable energy such as solar and wind energy, and is equipped with other infrastructures like advanced energy storage systems, sensing, and communication equipment. These elements make all these aspects of the generation, grid, load and storage organic integration and collaborative operation. However, the intermittent generation characteristic of renewable energy, the close coupling of various heterogeneous energy sources, and the access of random terminal loads such as electric vehicles pose challenges to the secure and optimal scheduling of energy system. Traditional model-based solutions require precise system parameters, which is hard to obtain in practice. To address the above challenges, this report will introduce the intelligent optimization algorithm based on deep reinforcement learning, and innovatively propose a deep reinforcement learning algorithm based on diffusion strategy and a multi-agent deep reinforcement learning algorithm based on interior point policy optimization, which show the characteristics of low-carbon, stable, and low variance, and secure optimal scheduling respectively. The application potential of artificial intelligence technology in modern energy and power systems will be exhibited, and the effectiveness of the proposed method is then illustrated in combination with classic cases.
Dr. Huaiguang Jiang, a tenured Professor of the School of Future Technology, South China University of Technology. He is now a standing committee member of Guangzhou Youth Federation and deputy director of Science and Technology Field, his research attention focuses on low-carbon intelligent energy and unmanned automation . He was selected as a National-level young talent, and has undertaken and participated in scientific research projects at national and other levels for many times, with a total project fund of more than 10 million RMB. As a senior member of IEEE, he has published more than 50 Chinese and English papers and works in related fields, with a total impact factor of more than 100, invited to publish 2 English academic monographs, participated in, chaired and organized the top Chinese and English conferences for many times, and was invited to review more than 20 top journals and top conferences in the industry.
来源：智能交通学域
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