基于PSO考虑谐波影响的补偿电容器优化配置

配电网合理的电容器配置不仅可以有效改善电网的电压水平，降低系统的有功网损，而且能够避免谐波谐振或电流放大，该文在建立电容器优化配置问题的非线性整数规划模型时，考虑了电压谐波畸变率约束条件，以保证优化方案下的各节点电压总谐波畸变率控制在规定限值以内。文中应用了一种简单有效，且收敛性很好的演化计算算法－微粒群优化算法（PSO）进行问题的求解，从编码方式，操作过程，目标函数选取，参数调节以及信息共享机制等五个方面分析了该算法的优越性，并给出了用于电容器优化配置问题中算法的具体求解步骤。对2个不同规模的IEEE测试系统的优化计算表明，微粒群算法可以很好地获得电容器优化配置问题的全局最优解。

OPTIMAL SHUNT CAPACITOR PLACEMENT USING PARTICLE SWARM OPTIMIZATION ALGORITHM WITH HARMONIC DISTORTION CONSIDERATION

The desirable scheme of capacitor placement in distribution systems aims at achieving voltage regulation and power loss reduction, while preventing harmonic resonance or magnification. Optimal shunt capacitor placement problem is formulated as a nonlinear integer programming problem with total harmonic distortion constraints in this paper. A new-proposed evolutionary computation called Particle Swarm Optimization (PSO) is applied to solve the problem. As an efficient algorithm which has good convergency, PSO shows great advantages in the ways of coding, operations, objective function consideration, parameter adjustment and information sharing mechanism. The iteration steps of solving capacitor placement problem are given in detail. The proposed solution methodology has been implemented on two test systems with different sizes, and the results show that PSO can solve the capacitor placement problem effectively and achieve the global optimal solution.