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Impact of the Uncertainty of Distributed Renewable Generation on Deregulated Electricity Supply Chain


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Date:  Thu, November 01, 2018
Time:  11:15am
Location:  Holmes Hall 389
Speaker:  Dr. Minghua Chen, Chinese University of Hong Kong

Abstract:

Microgrids are electricity customers that also produce power to meet their own demand. They are now widely recognized as a clear opportunity towards distributed renewable integration.

Meanwhile, uncertainty in renewable generation can impose unprecedented challenges in efficient operation of the existing deregulated electricity supply chain. While most previous studies focused on the impact of renewables on the supply side of the supply chain, we investigate the impact of distributed renewable generation on the demand side. In particular, we study how the uncertainty from distributed renewable generation in a microgrid affects the average buying cost of utilities and the cost-saving of the microgrid. We show that the renewable uncertainty in a microgrid can (i) increase the average buying cost of the utility serving the microgrid, termed as local impact, and (ii) somewhat surprisingly, reduce the average buying cost of other utilities participating in the same electricity market, termed as global impact. These observations reveal an inherent economic incentive for utilities to improve their load forecasting accuracy. our simulations based on real world traces verify our theoretical results and show that a 9% increase in load forecasting error will increase the average buying cost of the utility by 10%. This is a joint work with Hanling Yi, Mohammad H. Hajiesmaili, and Ying Zhang in CUHK and Xiaojun Lin in Purdue University.


Bio:

Minghua Chen received his Ph.D. degree from the Department of Electrical Engineering and Computer Sciences at University of California at Berkeley. He is now an Associate professor in Department of Information Engineering, the Chinese University of Hong Kong. He received the Eli Jury award from UC Berkeley in 2007 and the Chinese University of Hong Kong Young Researcher Award in 2013. He also received IEEE Transcations on Multimedia Prize Paper Award in 2009, and ACM Multimedia Best Paper Award in 2012. His recent research interests include energy systems, intelligent transportation systems, optimization, algorithms, and understanding the benefit of prediction in system design.


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