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| 基于自适应模糊粒子群算法的电力系统无功优化研究 | |
| 引用本文： | 吴肖锋,仲伟坤,张程,孙艳学,陈维华,于宗平.基于自适应模糊粒子群算法的电力系统无功优化研究[J].陕西电力,2012,40(8):38-41. |
| 作者姓名： | 吴肖锋 仲伟坤 张程 孙艳学 陈维华 于宗平 |
| 作者单位： | 1. 东北电力大学电气工程学院,吉林吉林,132012 2. 云峰发电厂,吉林集安,134200 3. 牡丹江电业局,黑龙江牡丹江,157000 4. 广东粤电靖海发电有限公司,广东揭阳,515223 |
| 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. |
| 关 键 词： | 自适应 粒子群算法 模糊控制 无功优化 |
Application of Adaptive Fuzzy Particle Swarm Optimization Algorithm in Power System Reactive Power Optimization |
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| WU Xiao-feng , ZHONG Wei-kun , ZHANG Cheng , SUN Yan-xue , CHEN Wei-hua , YU Zong-ping.Application of Adaptive Fuzzy Particle Swarm Optimization Algorithm in Power System Reactive Power Optimization[J].Shanxi Electric Power,2012,40(8):38-41. | |
| Authors: | WU Xiao-feng ZHONG Wei-kun ZHANG Cheng SUN Yan-xue CHEN Wei-hua YU Zong-ping |
| Affiliation: | 1. College of Electrical Engineering of Northeast Dianli University, Jilin 132012, China; 2. Yunfeng Power Station, Ji＇an 134200, China; 3. Mudanjiang Electric Power Bureau, Mudanjiang 157000, China; 4. Guangdong Yuedian Jinghai Power Generation Co., Ltd., Jieyang 515223, China) |
| Abstract: | 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. |
| Keywords: | adaptation particle swarm algorithm fuzzy control reactive power optimization |
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