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为减少分布式发电(DG)对配电网电压和网络损耗的影响,在考虑DG的接入位置、接入容量及接入方法等因素对配电网影响的基础上,建立了以潮流方程及DG接入容量为约束、以配电网中电压偏差和网络损耗同时最小、以DG接入容量最大为优化目标的多目标优化模型。在此基础上,提出了一种多群体自学习群搜索算法(MSLGSO),并将其应用于求解DG优化问题。通过对IEEE33节点的标准配电网算例仿真分析,表明DG的合理配置可使配电网电压水平提升和减少有功网损,且所提算法具有良好的实用性和适应性。
In order to reduce the impact of distributed generation (DG) on distribution network voltage and network loss, based on the influence of DG access location, access capacity and access method on distribution network, And DG access capacity as a constraint to the distribution network voltage deviation and network loss while minimizing DG access capacity for the optimization of multi-objective optimization model. On this basis, a multi-group self-learning group search algorithm (MSLGSO) is proposed and applied to solving DG optimization problems. The simulation analysis of the IEEE33 node standard distribution network shows that the reasonable configuration of DG can increase the distribution network voltage level and reduce the active power loss. The proposed algorithm has good practicability and adaptability.