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计及电动汽车充放电的微电网多目标分级经济调度
引用本文:侯慧,薛梦雅,陈国炎,唐金锐,徐焘,刘鹏. 计及电动汽车充放电的微电网多目标分级经济调度[J]. 电力系统自动化, 2019, 43(17): 55-62
作者姓名:侯慧  薛梦雅  陈国炎  唐金锐  徐焘  刘鹏
作者单位:武汉理工大学自动化学院,湖北省武汉市,430070;广州供电局有限公司,广东省广州市,510000
基金项目:国家自然科学基金青年基金资助项目(51707139)
摘    要:根据各调度单元的运行特性,提出一种含有负荷级、源荷级以及源网荷级的多目标分级微电网经济调度策略。首先,负荷级依据用户行驶习惯利用电动汽车的储能特性调控微电网原始负荷波动;其次,源荷级优先使用风、光出力支持微电网负荷用电,同时通过多目标粒子群优化算法,利用储能、完全可调度电动汽车最大化消纳可再生能源及最小化源荷级的综合运行成本;最后,源网荷级利用柴油机和主网联络线消纳来自源荷级剩余的微电网“净负荷”,并且将富余的风、光功率入网获得收益,使电动汽车群、微电网与主网达到经济性、高效性以及安全性的统一效果。以某具体的算例对所提策略进行仿真分析,并与电动汽车随机充电运行及不分级调度运行的情况进行对比,验证了所提策略的科学性及有效性。

关 键 词:电动汽车  分级  微电网(微网)  经济调度策略
收稿时间:2018-09-30
修稿时间:2019-07-04

Multi-objective Hierarchical Economic Dispatch for Microgrid Considering Charging and Discharging of Electric Vehicles
HOU Hui,XUE Mengy,CHEN Guoyan,TANG Jinrui,XU Tao and LIU Peng. Multi-objective Hierarchical Economic Dispatch for Microgrid Considering Charging and Discharging of Electric Vehicles[J]. Automation of Electric Power Systems, 2019, 43(17): 55-62
Authors:HOU Hui  XUE Mengy  CHEN Guoyan  TANG Jinrui  XU Tao  LIU Peng
Affiliation:School of Automation, Wuhan University of Technology, Wuhan 430070, China,School of Automation, Wuhan University of Technology, Wuhan 430070, China,Guangzhou Power Supply Co., Ltd., Guangzhou 510000, China,School of Automation, Wuhan University of Technology, Wuhan 430070, China,School of Automation, Wuhan University of Technology, Wuhan 430070, China and School of Automation, Wuhan University of Technology, Wuhan 430070, China
Abstract:According to the operation characteristics of each dispatch unit, a multi-objective hierarchical economic dispatch strategy for microgrid(MG)with load level, source-load level and source-grid-load level is proposed. Firstly, considering the driving habits of the electric vehicle(EV)users, the energy storage characteristics of EVs is used at the load level to adjust the original load fluctuation of the MG. Then the wind and solar power is preferentially used at the source-load level to support the load consumption of MG. Meanwhile, multi-objective particle swarm optimization(MPSO)algorithm is adopted to maximize the absorption of renewable energy and minimize the integrated operation cost of the source-load level by using energy storage unit and fully controllable EVs. Finally, the net load from the source-load level is absorbed at the source-grid-load level by the diesel engines and connection lines of the main grid, while the surplus wind and solar power is sold to the main grid to gain benefits, which has achieved the unification of the economy, efficiency and security benefits of the MG system and the main grid. A specific example is given to simulate and analyze the proposed strategy, and compared with random charging operation and non-hierarchical dispatching operation of EVs, which verifies the scientificity and effectiveness of the proposed strategy.
Keywords:electric vehicle   hierarchical   microgrid   economic dispatch strategy
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