摘要
针对传统粒子群算法搜索精度低和易早熟的缺点,提出了一种自适应模糊粒子群算法(AFPSO)对电力系统进行无功优化。该算法对惯性权重进行非线性的调整,有效地提高了算法的收敛速度和精度,并对位置的更新采用模糊控制,较好地解决了粒子群易早熟的问题。将该算法应用于无功优化问题中,在IEEE-30节点系统上进行测试,证明了AFPSO算法的有效性和优越性。
In order to overcome the drawback of traditional particle swarm optimization （PSO） such as low search precision and falling into local optimization, an adaptive fuzzy PSO is proposed to electric power system reactive power optimization. In this algorithm, inertia weight was nonlinearly adjusted, which effectively improve the convergence speed and accuracy, and the particle position update are controlled by fuzzy membership function, which avoids the prematurity problem of particle swarm. The algorithm was applied to reactive power optimization studies, and simulation results on IEEE 30-bus power system indicate that the validity and superiority of proposed algorithm.
出处
《陕西电力》
2012年第8期38-41,共4页
Shanxi Electric Power
关键词
自适应
粒子群算法
模糊控制
无功优化
adaptation
particle swarm algorithm
fuzzy control
reactive power optimization
