Data Analytics, Forecasting, and Optimization of Smart Power and Energy Systems

报告人:Dr. Yi Wang
主持人:侍乐媛 教授



To tackle the challenges of global warming, countries all around the world set aggressive goals to reduce carbon emission in different industries. As a major carbon emitter, the power and energy industry plays a vital role in decarbonization, where increasing renewable energy integration and improve energy efficiency are two effective approaches. However, high penetration of renewable energy integration challenges the reliability, economy, and flexibility of the power and energy systems. Fortunately, these challenges have come hand-in-hand with the advancements of Internet of Things (IoT), communication technology, and data science, which helps build the smart power and energy systems.

This talk will discuss three approaches to explore the flexibility and boost the efficiency of the power and energy systems. In the first part, this talk will introduce the concept of electricity consumer behavior model and then discuss how to make the best use of the fine-grained smart meter data available to process and translate them into actual information and incorporate into consumer behavior modeling and distribution system operations. In the second part, a systematic research on probabilistic load forecasting will be introduced by investigating how to model the uncertainties of the electrical load. In the third part, the talk will discuss how to model and optimize the gas, heat, and power integrated energy systems as whole so that the flexibility beyond power systems can be exploited. Future works for smart power and energy systems will be prospected.



Yi Wang is a postdoctoral researcher in the Power Systems Laboratory, ETH Zurich. He received his Bachelors degree in electrical engineering from Huazhong University of Science and Technology (HUST) in June 2014 and a Ph.D. degree in electrical engineering at Tsinghua University in Jan. 2019. From March 2017 to April 2018, he was an exchange student at the University of Washington. His research interests include big data applications in the smart grid, multiple energy systems, and cyber-physical power distribution systems. He has published over 20 SCI-indexed journal papers and has over 1000 citations in 谷歌 Scholar. His doctoral thesis was selected as Excellent Doctoral Thesis of Tsinghua University. He was awarded as Excellent Graduate Student of Tsinghua University and Siebel Scholar. He currently serves as the secretary of IEEE PES Working Group on Energy Forecasting and Analytics. He is the reviewer of over 20 journals and has been awarded as best reviewer of IEEE Transactions several times. He also serves as the associate editor for several international journals, including IET Renewable Power Generation, IET Smart Grid, and International Transactions on Electrical Energy Systems.





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