自适应粒子群优化算法及其在无功优化中的应用

针对传统的粒子群优化(PSO)算法中的某些参数需通过试验确定因而影响了其实用性的问题,提出了一种自适应粒子群优化(APSO)算法,并将其应用于电力系统无功优化问题的求解。该算法能在优化过程中自动调整各参数,从而取得问题的全局优化解。某具有151个节点、71个控制变量的实际电网无功优化结果表明,该算法较传统的PSO算法具有更强的全局寻优能力。

Adaptive Particle Swarm Optimization and Its Application in Reactive Power Optimization

Some parameters in the traditional particle swarm optimization (PSO) algorithm need to be predefined by test, so the algorithm's practicability is restricted. For this reason, the authors propose an adaptive particle swarm optimization (APSO) algorithm and apply it to reactive power optimization of power system. This algorithm can adjust parameters automatically in the optimization process to find the global optimal solution. The reactive power optimization results of an actual 151-bus power system with 71 control variables show that the proposed algorithm is more efficient than traditional PSO in searching global optimal solution.