基于改进BPSO算法的PMU优化配置新方法  

New Method for PMU Configuration Based on Improved BPSO Algorithm

作　　者：王小匆 刘亚东[1] 盛戈皞[1] 江秀臣[1] 罗林根[1] 张煊 刘宗杰 

机构地区：[1]上海交通大学电子信息与电气工程学院,上海200240 [2]国网山东省电力公司济宁供电公司,山东济宁272100

出　　处：《广东电力》2018年第1期62-67,共6页Guangdong Electric Power

基　　金：国家自然科学基金项目(51707117)

摘　　要：相量测量单元(phase measurement unit,PMU)优化配置问题的主要目标是找到使电力系统完全可观所需的最小PMU数目及其位置。针对此问题,提出了一种基于二进制粒子群优化算法(binary particle swarm optimization,BPSO)的改进方法,并在IEEE标准测试系统中对此算法与传统的BPSO算法进行了比较。该方法在原始BPSO算法的基础上,使用V形阈值函数代替S形阈值函数更新粒子的位置,在粒子适应度评估函数中考虑到了冗余度指标,并且提出了新的变异规则以增加种群多样性。最后试验结果表明,该方法提高了收敛效率,减少了算法结果陷入局部最优的概率,最大程度保证了测量冗余度,从而验证了其准确性和有效性。The main objective of optimized configuration for phase measurement unit( PMU) is to find the minimum PMU number and location required for full observability of the power system,therefore,the paper presents a kind of improved method based on binary particle swarm optimization( BPSO) algorithm and compares this algorithm with the traditional BPSO algorithm in IEEE standard testing system. On the basis of original BPSO algorithm,this improved method uses V-shaped threshold function to replace S-shaped threshold function and update locations of particles,and considers redundancy degree index in the fitness function as well as proposes new mutation rules to increase diversity of population. Experimental results indicate this method has improved convergence efficiency,reduced probability of algorithm results falling into local optimum and ensured redundancy degree of measurement to the full extent,which verifies accuracy and effectiveness of this algorithm.

关 键 词：二进制粒子群优化算法(BPSO) 相量测量单元(PMU) 变异规则 局部最优 冗余 

分 类 号：TM93[电气工程—电力电子与电力传动]