内容摘要：

Microgrids are electricity customers thatalso produce power to meet their own demand. They are now widely recognized asa clear opportunity towards distributed renewable integration. Despite apparentbenefits of incorporating renewable sources in a microgrid, uncertainty inrenewable generation can impose unprecedented challenges in efficient operationof the existing deregulated electricity supply chain, which is designed tooperate with no or little uncertainty in both supply and demand. While mostprevious studies focused on the impact of renewables on the supply side of thesupply chain, we investigate the impact of distributed renewable generation onthe demand side. In particular, we study how the uncertainty from distributedrenewable generation in a microgrid affects the average buying cost ofutilities and the cost-saving of the microgrid. Our analysis shows that therenewable uncertainty in a microgrid can (i) increase the average buying costof the utility serving the microgrid, termed as local impact, and (ii) somewhatsurprisingly, reduce the average buying cost of other utilities participatingin the same electricity market, termed as global impact. Moreover, the localimpact will lead to an increase in the electricity retail price of microgrid,resulting in a cost-saving less than the case without renewable uncertainty.These observations reveal an inherent economic incentive for utilities toimprove their load forecasting accuracy, in order to avoid economy loss andeven extract economic benefit in the electricity market. We verify ourtheoretical results by extensive experiments using real-world traces. Ourexperimental results show that a 9% increase in load forecasting error (modeledby the standard deviation of the mismatch between real-time actual demand andday-ahead purchased supply) will increase the average buying cost of the utilityby 10%.

主讲人简介：

MinghuaChen received his B.Eng. and M.S. degrees from the Department of ElectronicEngineering at Tsinghua University in 1999 and 2001, respectively. He receivedhis Ph.D. degree from the Department of Electrical Engineering and ComputerSciences at University of California at Berkeley in 2006. He spent one yearvisiting Microsoft Research Redmond as a Postdoc Researcher. He joined theDepartment of Information Engineering, the Chinese University of Hong Kong, in2007, where he currently is an Associate Professor. He is also currently anAdjunct Associate Professor in Tsinghua University, Institute ofInterdisciplinary Information Sciences. He received the Eli Jury award from UCBerkeley in 2007 (presented to a graduate student or recent alumnus foroutstanding achievement in the area of Systems, Communications, Control, orSignal Processing) and The Chinese University of Hong Kong Young Researcher Awardin 2013. He also received several best paper awards, including the IEEE ICMEBest Paper Award in 2009, the IEEE Transactions on Multimedia Prize Paper Awardin 2009, and the ACM Multimedia Best Paper Award in 2012. He serves as TPCCo-Chair of ACM e-Energy 2016 and General Chair of ACM e-Energy 2017. He iscurrently an Associate Editor of the IEEE/ACM Transactions on Networking. His recent research interests include energy systems (e.g., smartpower grids and energy-efficient data centers), intelligent transportation, distributedoptimization, multimedia networking, wireless networking, network coding, and delay-constrainednetwork information flow.