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电网技术  2015 

计及电动汽车和可再生能源不确定因素的多目标分布式电源优化配置

DOI: 10.13335/j.1000-3673.pst.2015.08.019, PP. 2188-2194

Keywords: 分布式电源,电动汽车,不确定性,多目标规划,改进量子粒子群

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Abstract:

大规模电动汽车(plug-inelectricvehicle,PEV)和风光等可再生能源发电并网使配电网分布式电源(distributedgeneration,DG)定容选址需考虑更多的不确定因素,为此,利用机会约束规划方法建立了以环境效益、供电可靠性、DG总费用和有功损耗最优为目标的DG优化配置模型,并提出蒙特卡洛模拟嵌入改进量子粒子群(improvedquantumparticleswarmoptimizationalgorithm-MonteCarlosimulation,IQPSO-MCS)的方法进行求解。在优化配置中考虑了风电、光伏、微型燃气轮机3种DG的选址和定容;并针对输出功率不确定的风力发电、光伏发电和电动汽车建立了概率模型,利用蒙特卡洛模拟法将随机性问题转化为确定性问题,实现含不确定因素的配电网随机潮流计算;最后由带自适应变异机制的IQPSO算法全局寻优得到最优配置方案。以IEEE33节点测试配电系统为例,验证了所提模型和方法的有效性和实用性。

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