基于模拟退火粒子群算法的含DG配电网重构研究  

Research on Distribution Network Reconfiguration with DG Based on Simulated Annealing and Particle Swarm Optimization

作　　者：游文霞[1] 崔雷[1] 李文武[1] 贺鹏程[2] 陈浩[2] 

机构地区：[1]三峡大学电气与新能源学院,湖北宜昌443002 [2]湖南省电力公司电力调度控制中心,长沙410007

出　　处：《三峡大学学报（自然科学版）》2013年第3期45-49,共5页Journal of China Three Gorges University：Natural Sciences

基　　金：湖北省自然科学基金资助(50579019);三峡大学研究生科研创新基金资助(2011CX045)

摘　　要：含分布式电源的配电网重构是配网优化的重要课题.二进制粒子群算法(BPSO)是解决优化问题的重要算法,首先根据配电网重构的拓扑约束条件,将轮盘赌操作引入到BPSO中,改进了BPSO算法中粒子位置状态更新策略.接着将模拟退火算法中的动态变异机制引入到改进的BP-SO中,解决了BPSO容易陷入局部最优的缺点,最终能够快速有效地达到网路损耗最小的目的.选取IEEE69节点系统进行算例仿真,并与现有研究成果进行对比,结果表明该算法在继承了粒子群优化算法简单容易实现的特点同时,使其具有了摆脱局部极值点的能力,能够优化最优解,提高算法的收敛速度,适合解决含分布式电源的配电网重构问题.Distribution network reconfiguration with distributed generators is an important subject for optimi- zation. Binary particle swarm optimization（BPSO） is an important algorithm to solve optimization. First of all, roulette operations are introduced into the BPSO according to the distribution network topological con- straints. It improves the update strategy for particles location. Then the dynamic mutation mechanism of sim- ulated annealing （SA） is led into the modified BPSO that it is easy to fall into local optimal solution. Finally, the algorithm is able to quickly and efficiently achieve the purpose of the minimum network loss. IEEE 69 bu- ses system is used as an example for simulation. Its simulation results contrasted with the previous research results shows that the proposed algorithm inherits the BPSO＇s characteristics, such as simple, easy to imple- ment. Meanwhile, the proposed algorithm has the ability to get rid of the local extreme points, optimize the optimum solution and improve convergence rate and execution efficiency. Therefore, this algorithm is suitable for solving distribution network reconfiguration with distributed generators.

关 键 词：分布式电源 配电网重构 二进制粒子群优化 模拟退火 轮盘赌选择算子 

分 类 号：TM743[电气工程—电力系统及自动化]