基于改进自适应遗传算法的分布式电源优化配置  

Optimal allocation of distributed generation based on improved self-adaptive genetic algorithm

作　　者：王振浩[1] 李文文[1] 陈继开 李国庆[1] 

机构地区：[1]东北电力大学,吉林吉林132012 [2]黑龙江省电力科学研究院,哈尔滨150030

出　　处：《电测与仪表》2015年第5期30-34,共5页Electrical Measurement & Instrumentation

基　　金：国家电网公司科技项目(2012515);吉林省科技发展计划(20130206038GX)

摘　　要：分布式电源接入配电网对系统电压、网损等有一定的影响,针对配电网中分布式电源的规划问题,建立了以投资成本最小,电网网损费用最低、电压质量最优为目标的多目标优化模型,采用PSAT搭建算例模型进行潮流计算,同时,为了克服传统遗传算法的早熟现象及收敛性问题,采用改进的自适应遗传算法对分布式电源接入的位置和容量进行了优化,通过对IEEE33节点配电网络进行仿真分析,结果表明采用搭建的模型和算法可以有效改善系统的电压质量、降低网络损耗,验证了上述模型和算法的合理性及有效性。Distributed generation in distribution network has some influence on the system voltage , network loss and etc.In the planning of distributed generation in distribution network , a multi-objective optimization model is pro-posed in this paper , which includes the minimum investment cost , minimum power loss and the best voltage quality . Using PSAT to build numerical model for power flow calculation , and in order to overcome the premature phenomena and convergence problem of genetic algorithms , a new improved self-adaptive genetic algorithm is employed to opti-mize the location and sizing of the distributed generation in distribution network .The effectiveness and feasibility for improving the quality of voltage and reducing the power loss are finally verified by the simulation of the IEEE 33 bus system example .

关 键 词：分布式电源 优化配置 多目标优化 自适应遗传算法 配电网规划 

分 类 号：TM715[电气工程—电力系统及自动化]