基于遗传算法和微分进化算法的分布式电源优化配置  

Optimal Allocation of Distributed Generation Based on Genetic Algorithms and Differential Evolution Algorithm

作　　者：袁沔齐 邹振宇[1] 孙凯祺[2] 刘合金[2] 李可军[2] 

机构地区：[1]山东电力工程咨询院有限公司,山东济南250013 [2]山东大学电气工程学院,山东济南250061

出　　处：《中国电力》2013年第1期16-20,共5页Electric Power

摘　　要：配电系统中,分布式电源(DG)安装位置的选择、额定容量的确定对于电网规划、设计和投资至关重要,以10节点配电网系统为例,采用遗传算法和微分进化算法对分布式电源进行了优化配置,建立了DG的不确定性模型,并将其加入到优化分析中,给出了优化算法的求解程序。对含DG的配电网进行了潮流计算,分析了DG容量与系统总网损的关系。算例分析结果表明,优化配置有效改善了配电网的电压分布,减小了网损,提高了系统负荷率,说明了该优化配置方法合理、有效。Selection of the position and rated capacity of the distributed generation （DG） is crucial for power system in planning, design and investment. Genetic algorithm and differential evolution algorithm are adopted for the optimal allocation of DG based on a 10-node distribution network and an uncertainty DG model is built and added into the optimization analysis with an optimization algorithm program. The load flow is calculated for a distribution network with DG and the relation between installed DG capacity and the system＇s total transmission loss is analyzed. The computational example shows that the proposed method of optimal allocation is reasonable and effective in improving the voltage distribution of distribution network, reducing transmission loss and improving the system＇ s output factor.

关 键 词：分布式电源 优化配置 不确定性模型 遗传算法 微分进化算法 

分 类 号：TM715[电气工程—电力系统及自动化] TP18[自动化与计算机技术—控制理论与控制工程]