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基于纵横交叉-拉丁超立方采样蒙特卡洛模拟法的分布式电源优化配置

DOI: 10.13334/j.0258-8013.pcsee.2015.16.010, PP. 4077-4085

Keywords: 分布式电源,电动汽车,多目标规划,蒙特卡洛模拟,纵横交叉算法

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Abstract:

大规模的电动汽车(plug-inelectricvehicle,PEV)和风力、太阳能等可再生能源(renewableenergysources,RES)发电并网使未来智能配电网规划需考虑更多不确定因素。在考虑PEV充电随机性和RES出力间歇性的基础上,利用机会约束规划法建立了计及环境成本、DG总费用和有功损耗的多目标分布式电源优化配置模型,并提出一种考虑随机变量相关性的拉丁超立方采样蒙特卡洛模拟嵌入纵横交叉算法(crisscrossoptimizationalgorithm-correlationLatinhypercubesamplingMonteCarlosimulation,CSO-CLMCS)的方法对优化模型进行求解。该方法首先根据PEV和RES的概率模型及随机变量间的相关性,利用CLMCS概率潮流计算方法计算配电网概率潮流,并根据概率潮流结果检验约束条件及计算目标函数值,最后由CSO算法进行全局寻优得到最优配置方案。采用实际算例进行仿真,结果验证了所提模型和方法的可行性和有效性。

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