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发布日期:2017-11-28 11:17:00
时 间:2017 年11月29 日,上午10点30
地 点:电气楼313会议室

美国韦恩州立大学工程学院电气与计算机工程系教授。1994年和1997年分别获得重庆大学电气工程学士和硕士学位。1997年至2002年,在浙江电力研究所先后担任研究工程师和副主任。2006年获美国蒙大拿州立大学电气工程博士学位,IEEE高级会员,IEEE PES/PELS/IAS会员,担任Electric Power Components and Systems、Autosoft Journal-Intelligent automation & Soft Computing、SAE Journal of Electronic & Electrical Sys for Passenger Cars等期刊的副主编,是美国国家科学基金和20余种国际期刊的审稿人,先后获得2007 IEEE EDPG优秀论文奖,2009、2010年度韦恩州立大学杰出教学奖,2009年韦恩州立大学研究生指导奖等奖项。先后发表学术论文130余篇,撰写出版专著4部。主要研究方向为:电力系统、分布式发电与智能电网;可再生能源和系统集成;电动车辆和能量存储装置;电力电子装置与电机。
The attractive features of natural gas as well as the growing electric power demand worldwide have created increasing interest in natural-gas-based distributed generation applications for electric distribution networks. This paper investigates the interdependency between a residential natural gas network and an electric distribution network that are linked together via fuel cells. The modeling of the natural gas network is introduced first, and then the algorithm for gas flow study is presented. The optimal placement and sizing of fuel cells based distributed generation systems is formulated to minimize the losses in both the natural gas network and the electric distribution grid, subject to the constraints imposed by both networks.  In addition, a probabilistic model for both gas and electricity demands is developed based on historical electricity and natural gas demand data. A K-means clustering method is used to determine the hourly load states to solve the joint probabilistic optimization problem. Simulation studies are carried out on an integrated system consisting of the IEEE 69-bus distribution network and a radial 27-node natural gas network to verify the developed optimization model and the proposed method.