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出 处:《电力系统及其自动化学报》2012年第4期130-133,共4页Proceedings of the CSU-EPSA
摘 要:该文提出了一种基于非支配性遗传算法NSGA-Ⅱ的分布式电源(DG)优化配置算法,对DG接入配电网的位置和容量进行优化配置。采用了十进制的编码方式使得DG接入位置和容量的优化可以同时进行,运用前推回代法对接入DG的配电网络进行潮流计算,选择了总电压偏差最小,有功损耗最小和CO2排放量最小三个目标函数进行优化,该算法一次运行可以获得一组Pareto最优解,决策者可以根据系统的实际需要选择最终的满意解,为各目标函数的权衡分析提供了有效的工具。最后应用该算法对IEEE33节点进行DG的优化配置,结果证明了算法的有效性。In this paper, an optimal allocation of the distributed generation (DG) based on non-dominated sor- ting genetic algorithm (NSGA-Ⅱ ) is proposed to optimize the location and capacity of DG connected to the distribution network. The decimal encoding is used to optimize the location and capacity of DG at the same time, and the back/forward sweep method is used for power flow calculation of distribution network connected with DG. The objective functions are respectively the least total voltage deviation, the least power loss and the least COs emission. Each operation of the algorithm can produces a series of Pareto-optimal solutions. The satisfac- tory solution can be selected by decision-maker according to the system's actual requirement, which provides an effective tool for measuring the performance of the different objective functions. The presented method is ap- plied to the optimal allocation of IEEE 33 nodes system with DG and the solutionshows the validity of the method.
关 键 词:非支配性排序遗传算法 分布式电源 潮流计算 目标函数 优化
分 类 号:TM71[电气工程—电力系统及自动化]
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