基于自适应聚焦粒子群优化算法的电力系统多目标无功优化

自适应聚焦粒子群算法(adaptive focusing particle swarm optimization，AFPSO)是根据粒子群算法的全局搜索与局部搜索平衡特性，并予以改进得到的一种具有较好全局搜索能力和寻优速度的自适应群体智能优化算法。作者将此算法用于电力系统无功优化。该方法以最优控制原理为基础，引入了静态电压稳定性指标，建立了综合考虑系统有功网损最小、静态电压稳定裕度最大的多目标无功优化模型。IEEE 30节点系统仿真结果表明，AFPSO算法在实现系统经济运行的同时也增强了电网的电压稳定性，证明了AFPSO算法的有效性和优越性。

Power System Multi-Objective Reactive Power Optimization Based on Adaptive Focusing Particle Swarm Optimization Algorithm

Based on the improvement of balance performance of particle swarm optimization in global and local searching, an adaptive focusing particle swarm optimization (AFPSO) is proposed which is an adaptive swarm intelligence optimization algorithm possessing better global searching ability and faster searching speed. In this paper the proposed AFPSO algorithm is applied to power system reactive power optimization. Taking optimal control principle as its foundation and led in the index of static voltage stability, a multi-objective reactive power optimization model in which the minimum active network loss and maximum static voltage stability margin are considered comprehensively is built. Simulation results of IEEE 30-bus system show that AFPSO algorithm can enhance power system voltage stability, meanwhile economic operation of power system is also implemented, thus the effectiveness and superiority of AFPSO algorithm are verified.