基于遗传量子粒子群法的含DG配电网无功优化  

Reactive Power Optimization of DG Distribution Network Based on Genetic Quantum Particle Swarm Optimization Method

作　　者：武晓朦[1] 张钦凯 李飞 WU Xiao-meng;ZHANG Qin-kai;LI Fei(School of Electronic Engineering,Xi'an Shiyou University,Xi'an Shaanxi 710065,China)

机构地区：[1]西安石油大学电子工程学院,陕西西安710065

出　　处：《计算机仿真》2025年第2期107-112,127,共7页Computer Simulation

基　　金：国家自然科学基金企业创新发展联合基金重点项目(U20B2029);陕西省科技计划基础研究项目(2021JM-404);陕西省教育厅科研计划项目(21JK0843);西安石油大学研究生创新与实践能力培养项目(YCS22214242)。

摘　　要：为解决分布式电源接人配电网造成的电网可靠性和电能质量降低等问题,提出一种结合量子粒子群法和遗传算法的配电网无功优化方案。选取含DG配电网网损最小作为目标函数,以节点电压幅值和投切电容器容量为约束条件,采用牛顿拉夫逊法进行潮流计算;以节点网损-无功功率灵敏度为依据,对含DG配电网节点进行灵敏度分析排序,选择出最佳无功补偿节点;采用遗传量子粒子群混合算法对选择出的无功补偿节点进行补偿容量的寻优。节点无功补偿容量作为决策变量,无功补偿容量范围为量子空间中粒子边界,在粒子种群中引人自适应交叉、变异操作,最后通过蒙特卡洛随机模拟完成粒子进化更新。以含DG的IEEE33和IEEE69节点配电网作为算例进行验证,并对DG出力的不确定性进行仿真讨论。结果表明,所提出的算法是可行的,在降低配电网网损的同时可提高节点电压幅值。To solve the problems of reduced power grid reliability and power quality caused by the integration of distributed power sources into the distribution network,a reactive power optimization scheme for the distribution network combining quantum particle swarm optimization and genetic algorithm is proposed.The minimum loss of distribution containing DG is selected as the objective function,and the nodal voltage amplitude and the capacitor capacity are used as constraints for the tide calculation by the Newton-Raphson method.Based on the network loss-reactive power sensitivity of nodes,the DG-containing distribution network nodes were sorted by sensitivity analysis,and the best reactive power compensation nodes were selected.The mixed genetic quantum-behaved particle swarm optimization is used to select the optimization of reactive power compensation volume and nodes.The nodal reactive volume was taken as the decision-making parameter,and the reactive volume range is the particle boundary in the quantum space,self-adaptive crossover and mutation actions are applied in the particle species,and the particle evolution update is completed by Monte Carlo stochastic simulation.Taking the IEEE33 and IEEE69 node distribution networks containing distributed power as examples for verification,and the uncertainty of DG output is simulated and discussed.The results show that the proposed algorithm is feasible,which can reduce the network loss and improve the node voltage amplitude of DG-containing distribution networks.

关 键 词：分布式电源 灵敏度 无功优化 遗传量子粒子群优化 配电网 

分 类 号：TM713.4[电气工程—电力系统及自动化]