基于改进粒子群算法的配网电容器优化配置  

Optimal configuration of capacitors in radial distribution network based on particle swarm optimization algorithm

作　　者：刘军志[1] 陈明照[1] 杜宗林[1] 

机构地区：[1]国网湖南省电力公司培训中心,湖南长沙410131

出　　处：《电源技术》2015年第7期1498-1500,共3页Chinese Journal of Power Sources

基　　金：湖南省科技计划项目(2012WK3036;2011CK3067;2011GK3132)

摘　　要：随着国民经济发展,配电网规模不断扩大。依照经验配置电容器的局限性日益显著,具体表现为电容器容量配置的不足或过剩,部分电容器需要时由于局部电压的限制而不能投入。将模拟退火粒子群算法用于解决配电网电容器优化配置问题,建立了相应的数学模型,目标函数为配电网有功网损费用、电容器的购置及安装总费用最小,该算法将电容器的安装位置及安装容量离散化,采用基于适应度值的动态阈值来控制实施局部搜索的粒子数目,来改善算法摆脱局部极值点的能力,提高算法的收敛速度和精度。对一个33节点配电网的电容器优化配置结果表明了模拟退火粒子群算法的合理性和优越性。Along-with the continuous enlargement of distribution network, the limitation of traditional experience based capacitor configuration reveals the lack or excess of configured capacitors, more seriously, when part of capacitors should be put into operation, they cannot be switched on because of the restriction of local voltage. Discrete particle swarm optimization algorithm was introduced to solve the problem of optimal configuration of capacitors in radial distribution network, where the simulated annealing optimization algorithm was combined with PSO to speed up the local search. And a mathematical model was established. The objective function was that the total cost, including the cost for network real power losses, the purchasing cost, the installation cost and the maintenance .cost of compen- sating capacitors, should be minimum. A threshold based on fitness was adopted to avoid the common defect of premature convergence, and improve the abilities of seeking the global excellent result ahd evolutio speed. The results of IEEE 33-node distribution system show that the presented algorithm is feasible and effective.

关 键 词：配电网 模拟退火粒子群算法 离散值 电容器优化配置 

分 类 号：TM53[电气工程—电器]