基于改进粒子群算法的中压配电网无功优化

建立了以年费用最小为目标函数的无功优化数学模型,提出一种融合裂变和变异操作的分合群粒子群算法求解该模型,并结合对系统分区、合理设置补偿上限等方法减小搜索范围,实现了同时求解补偿点和补偿量。算法在标准粒子群优化(particle swarm optimization,PSO)算法的基础上通过分群和裂变,保持粒子的多样性,避免收敛早熟;通过合群和变异,加强算法的搜索精度,提高算法的收敛稳定性。用IEEE 33节点系统进行仿真计算,与标准PSO算法对比表明,改进PSO算法在计算精度、收敛稳定性等方面具有明显优势;与无功二次精确矩法对比表明,改进PSO算法具有自动调整补偿点个数的能力,补偿方案经济性更好,能有效解决中压配电网的无功优化问题。

Reactive Power Optimization for Medium Voltage Distribution Network Based on Improved Particle Swarm Optimization

Taking minimum annual operation cost as objective function,a mathematical model for reactive power optimization is built,and a dividing-gregarious particle swarm algorithm that integrates fission and mutation operations is proposed to solve the built model.The search region is narrowed by partitioning the network and reasonably setting upper compensation limit to implement simultaneous solution of both compensation position and compensation capacity.Based on standard particle swarm optimization(PSO) and by means of dividing and fission,the diversity of particles is kept to avoid the premature of convergence;by means of gregariousness and mutation the search accuracy of the proposed algorithm as well as its convergence stability are improved.Simulation results of IEEE 33-bus system show that the calculation accuracy and convergence stability of the proposed algorithm is better than the calculation results by standard PSO algorithm;the proposed algorithm possesses the ability of automatically regulating the number of compensation points that reactive quadric accurate moment method does not possess,and the compensation scheme possesses better economy and can effectively solve the reactive power optimization in medium-voltage distribution network.