JIN Yizhou, ZHANG Liping, WU Peng, et al. Application of improved GA in distribution network reconfiguration with DG[J]. 2020, (10): 153-156. DOI: 10.13873/J.1000-9787(2020)10-0153-04.
改进遗传算法在含DG配电网重构中的应用
摘要
计及分布式电源(DG)出力和负荷不确定性对配电网的影响
提出一种适用于不确定性配电网重构的改进遗传算法。首先
基于DG出力概率模型
给出考虑多种不确定性的供电能力机会约束模型
建立了考虑供电能力机会约束条件的配电网重构模型;然后
改进遗传算法中生成初始种群与交叉操作的方式
使其适用于所建配电网重构模型;最后
使用改进遗传算法求解配电网重构模型
给出基于蒙特卡罗模拟的随机机会约束检验方法。IEEE 33节点算例的计算结果表明
本文方法能计及DG出力和负荷的不确定性
所得方案可满足设定的供电能力
提升配电网重构方案的抗风险能力。
Abstract
The impact of distributed generation( DG) access on distribution network is taken into account
an improved genetic algorithm for uncertain distribution network reconfiguration is proposed. Firstly
based on DG output probability model
a power supply capability index opportunity constraint model considering uncertainty is presented
and the distribution network reconfiguration model considering chance constrained condition is established; then
the initial population generation and crossover operation of genetic algorithm is improved to make it suitable for the uncertain distribution network reconfiguration model. Finally
a simulation method for calculating the chance constrained of power supply capability index is presented. The 33-node example shows that the method is able to take the uncertainty of DG output and distribution network load into account on the basis of traditional genetic algorithm
The reconfiguration scheme can meet the index of power supply capability and improve the antirisk capability of the reconfiguration scheme.