摘要
针对粒子群算法在变压器局部放电超声波定位中存在定位精度不高、易陷入局部最优等问题,文中提出一种基于粒子群和克隆选择混合的优化方法。首先,根据电声法定位原理建立优化模型;然后,由粒子的适应度对粒子进行按比例克隆复制、高频变异和消亡补充处理,有效维持种群的多样性,避免算法早熟收敛,同时,利用粒子群算法指导变异抗体通过更新速度和位置来加速最优解的寻找,提高收敛速度;最后,将所提方法与粒子群算法和遗传算法的优化结果进行比较,仿真结果表明该算法具有较高的收敛速度和计算精度,提高了定位的准确度。
Because of low precision and local optimization of ultrasonic locating of partial discharge in transformer by using of traditional particle swarm algorithm,a kind of optimization method based on particle swarm algorithm and clonal selection method is proposed in this paper.The optimization model is built according to electro-acoustic locating technique,and the particles are cloned and selected by the fitness to effectively maintain the population diversity,at the same time,the antibody is guided by updating the speed and position of particles to obtain the optimal solutions.In the end,the simulation are carried out by using of proposed method,and results are compared with those by using of PSO and GA approaches,which show that this algorithm has higher convergence speed and calculation precision that improves the correctness of locating.
出处
《现代电力》
2010年第5期21-24,共4页
Modern Electric Power
关键词
粒子群算法
克隆选择
超声波定位
传感器
局部放电
Particle Swarm Optimization（PSO）
clonal selection
ultrasonic location
sensor
partial discharge
