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含电动汽车负荷的分布式风电源优化配置
引用本文:许珊,李扬.含电动汽车负荷的分布式风电源优化配置[J].电力需求侧管理,2019,21(1):11-15.
作者姓名:许珊  李扬
作者单位:东南大学 电气工程学院,南京,210096;东南大学 电气工程学院,南京,210096
基金项目:国家电网公司科技项目(XM2016020033815)
摘    要:分布式风电(distributed wind generation,DWG)出力、系统负荷功率以及电动汽车(electric vehicles,PEV)无序充电功率的随机性和时序性波动为配电网中DWG的优化配置带来更多的不确定性。为此,利用季节场景与时段划分法处理DWG出力与负荷大小的时序特性,并对PEV的随机性进行概率建模。对各时段采用机会约束规划方法建立了以年度综合成本为目标的DWG优化配置模型。利用蒙特卡洛模拟嵌入保留精英策略的遗传算法的方法对典型算例进行求解,结果验证了所提模型与方法的正确性和有效性。

关 键 词:时序特性  分布式风电源  电动汽车  优化配置
收稿时间:2018/4/16 0:00:00
修稿时间:2018/6/4 0:00:00

Optimal allocation of distributed wind generation including loads of electric vehicles
XU Shan and LI Yang.Optimal allocation of distributed wind generation including loads of electric vehicles[J].Power Demand Side Management,2019,21(1):11-15.
Authors:XU Shan and LI Yang
Affiliation:School of Electrical Engineering, Southeast University, Nanjing 210096, China and School of Electrical Engineering, Southeast University, Nanjing 210096, China
Abstract:The stochastic and timing characteristics of distributed wind generation output, load power and electric vehicles charging load have brought more uncertainties to the optimal allocation of distributed wind generation. Therefore, season-scenario and period-division method is adopted and the stochastic characteristic of plug-in electric vehicles is modeled. Taking annul comprehensive cost as objective function, a distributed wind generation planning model based on timing characteristics is presented using chance constrained programming method. A Monte Carlo simulation embedded genetic algorithm with elite strategy is adopted to solve a typical case and results verify the effectiveness of the proposed model.
Keywords:timing characteristics  distributed wind generation  electric vehicles  optimal allocation
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