On April 23, Professor Pierre Pinson from Imperial College London was invited to deliver a special academic lecture at the Department of Electrical Engineering and Applied Electronics (EEA), Tsinghua University. The lecture was titled “AI/Machine Learning as the Core of Future Power Markets.” Attendees included Professor Kang Chongqing, Dean of the Department, Associate Professors Hu Zechun and Zhong Haiwang, Associate Researcher Guo Hongye, Assistant Researcher Dai Jing from the Tsinghua Energy Internet Research Institute, among others. The event was hosted by Associate Researcher Guo Hongye. In addition to faculty and students from Tsinghua EEA, participants also included scholars and students from North China Electric Power University, Imperial College London, and the University of Hong Kong.
Professor Pierre Pinson Delivering the Lecture
Professor Pierre Pinson offered an in-depth analysis of the transformative impact of AI and machine learning on the energy sector. He began by highlighting that weather forecasting models based on deep learning have already surpassed traditional numerical methods in accuracy, providing crucial support for renewable energy scheduling. Next, in the area of electricity market design and operation, given new developments such as the increasing frequency of negative electricity prices and the widespread integration of distributed resources and energy storage, future market mechanisms must balance efficiency and fairness while meeting physical constraints and integrating environmental, social, and governance considerations. In response, technological solutions combining machine learning and mathematical optimization are opening new possibilities for changes in market structures and operational models. Moreover, under these new mechanisms and technologies, the value of data must be comprehensively reassessed, and there is an urgent need to design and improve incentive mechanisms for data sharing, taking into account data exclusivity and timeliness.
Academic Lecture Venue
Following the lecture, attendees engaged in a lively exchange and discussion on topics such as the specific roles of AI in solving distributed optimization problems, the coupling between data markets and power markets, and architectural shifts brought about by the participation of distributed resources in the electricity market. Professor Pierre Pinson addressed each question in detail.
Professor Pierre Pinson Engaging in Discussion with Faculty and Students
During the event, an appointment ceremony was held, and Professor Kang Chongqing presented Pierre Pinson with a certificate officially appointing him as a Distinguished Visiting Scholar of the Tsinghua Energy Internet Innovation Institute.
Professor Kang Chongqing Presenting Appointment Certificate to Professor Pierre Pinson
Before the lecture, Professor Pinson also joined selected faculty and students from the Department in a thematic seminar. The seminar featured an introduction to the Tsinghua Energy Internet Innovation Institute’s think tank by Assistant Researcher Dai Jing, an overview of China’s electricity market development by Associate Researcher Guo Hongye, and presentations by four PhD students on their research in areas including the application of machine learning in optimization, generation expansion planning, capacity cost allocation mechanisms, and multi-market bidding strategies for energy storage. The discussions were thorough and engaging.
Professor Pierre Pinson in a Thematic Seminar with Faculty and Students
Group Photo of Professor Pierre Pinson with All Participants
Guest Biography:
Professor Pierre Pinson is a faculty member and Associate Dean at the Dyson School of Design Engineering, Imperial College London (ICL), Chief Scientist at Halfspace, Adjunct Professor at the Technical University of Denmark (DTU), and Associate Researcher at CoRE, Aarhus University. He serves as Editor-in-Chief of the International Journal of Forecasting, is an IEEE Fellow, a member of INFORMS, and a board member of the International Institute of Forecasters (IIF). From 2019 to 2023, he was consistently listed as a Clarivate Highly Cited Researcher in the cross-field category for his influential work across statistics, meteorology, economics, and power/energy engineering. Recognized as a global leader in predictive analytics, Professor Pinson was awarded the 2024 INFORMS Franz Edelman Award for his outstanding contributions to operations research, analytics, and management science.
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