|
|||||
|
|
| 基于细菌趋化的改进粒子群算法在电力系统无功优化中的应用 | |
| 引用本文： | 周涛,崔德义,任书燕. 基于细菌趋化的改进粒子群算法在电力系统无功优化中的应用[J]. 上海电力学院学报, 2014, 30(4): 315-318,323 |
| 作者姓名： | 周涛 崔德义 任书燕 |
| 作者单位： | 上海电力学院电气工程学院;上海市电力公司嘉定供电公司; |
| 摘 要： | 传统粒子群算法易陷入局部最优、后期多样性差,得不到最优解.在原有无功优化数学模型的基础上,引入了基于细菌趋化的粒子群改进算法.通过算例表明,该算法可以有效克服传统粒子群算法的缺点,优化计算结果. |
| 关 键 词： | 粒子群算法 细菌趋化 无功优化 |
| 收稿时间： | 2013-12-23 |
Application of Particle Swarm Optimization Based on Bacterial Chemotaxis to Reactive Power Optimization |
|
| ZHOU Tao,CUI Deyi and REN Shuyan. Application of Particle Swarm Optimization Based on Bacterial Chemotaxis to Reactive Power Optimization[J]. Journal of Shanghai University of Electric Power, 2014, 30(4): 315-318,323 | |
| Authors: | ZHOU Tao CUI Deyi REN Shuyan |
| Affiliation: | ZHOU Tao , CUI Deyi, REN Shuyan ( 1. School of Electrical Engineering, Shanghai University of Electric Power, Shanghai 200090, China; 2. Jiading Power Company, Shanghai Power Supply Company, Shanghai 138000, China) |
| Abstract: | Traditional PSO falls into local optimum easily and has a poor late diversity and can not obtain the optimal solution. Based on traditional mathematical model, a new PSO advanced method based on bacterial chemotaxis is introduced. The simulation example shows that it can overcome the above shortcomings of traditional particle swarm algorithm and optimize the result effectively. |
| Keywords: | particle swarm optimization bacteria chemotaxis reactive power optimization |
| 本文献已被 CNKI 维普 等数据库收录！ | |
| 点击此处可从《上海电力学院学报》浏览原始摘要信息 | |
| 点击此处可从《上海电力学院学报》下载全文 | |