An Adaptive Particle Swarm Optimization Algorithm for Reactive Power Optimization in Power System

被引：3

作者：

Wu, Enqi ^{[1
]}

Huang, Yue ^{[2
]}

Li, Dan ^{[3
]}

机构：

[1] North China Elect Power Univ, Sch Elect & Elect Engn, Baoding 071003, Peoples R China

[2] Shenyang Ligong Univ, Sch Informat Sci & Engn, Shenyang 110168, Peoples R China

[3] Northeast China Grid Co Ltd, Shenyang 110181, Peoples R China

来源：

2010 8TH WORLD CONGRESS ON INTELLIGENT CONTROL AND AUTOMATION (WCICA) | 2010年

关键词：

particle swarm optimization; adaptive mutation; reactive power optimization; DISPATCH;

D O I：

10.1109/WCICA.2010.5553988

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

An adaptive particle swarm optimization(APSO) algorithm is presented to solve the problem that the standard particle swarm optimization(PSO) algorithm is easy to fall into a locally optimized point, where inertia weight is nonlinearly adjusted by using population diversity information. Velocity mutation factor and position interchange factor are both introduced. The APSO algorithm thus improves its solvability for global optimization to avoid effectively the precocious convergence. The new algorithm is applied to reactive power optimization of the standard IEEE-30-bus power system as instances, and the simulation results show the effectiveness and feasibility of APSO algorithm for the reactive power optimization. It is proved to be efficient and practical during the reactive power optimization.

引用

页码：3132 / 3137

页数：6

共 50 条

[1] Adaptive particle swarm optimization algorithm for power system reactive power optimization
Li, Dan
Gao, Liqun
Lu, Shun
Ma, Jia
Li, Yang
2007 AMERICAN CONTROL CONFERENCE, VOLS 1-13, 2007, : 2242 - 2246
[2] Adaptive particle swarm optimization algorithm for reactive power optimization of power system
Gao, Liqun
Wang, Ke
Li, Dan
Li, Yang
DYNAMICS OF CONTINUOUS DISCRETE AND IMPULSIVE SYSTEMS-SERIES B-APPLICATIONS & ALGORITHMS, 2006, 13E : 1312 - 1315
[3] Power System Reactive Power Optimization Based on Adaptive Particle Swarm Optimization Algorithm
Sun Shuqin
Zhang Bingren
Wang Jun
Yang Nan
Meng Qingyun
2013 FOURTH INTERNATIONAL CONFERENCE ON DIGITAL MANUFACTURING AND AUTOMATION (ICDMA), 2013, : 935 - 939
[4] Power system reactive power optimization based on adaptive particle swarm optimization algorithm
Li, Dan
Gao, Liqun
Zhang, Junzheng
Li, Yang
WCICA 2006: SIXTH WORLD CONGRESS ON INTELLIGENT CONTROL AND AUTOMATION, VOLS 1-12, CONFERENCE PROCEEDINGS, 2006, : 7572 - 7576
[5] Reactive power optimization in power system based on Adaptive Particle Swarm Optimization
Zhao, Wenqing
Wang, Liwei
Han, Feifei
Wang, Dewen
ADVANCES IN MECHATRONICS, AUTOMATION AND APPLIED INFORMATION TECHNOLOGIES, PTS 1 AND 2, 2014, 846-847 : 1209 - 1212
[6] Reactive power optimization in power system based on adaptive focusing particle swarm optimization
Liu, Shu-Kui
Chen, Wei-Rong
Li, Qi
Lin, Chuan
Duan, Tao
Dianli Xitong Baohu yu Kongzhi/Power System Protection and Control, 2009, 37 (13): : 1 - 6
[7] Reactive power optimization of power system using the improved particle swarm optimization algorithm
School of Information Science and Engineering, Central South University, Changsha 410083, China
不详
Gaodianya Jishu, 2007, 7 (159-162):
[8] Application of Improved Adaptive Particle Swarm Optimization Algorithm in Reactive Power Optimization
Jiang, Xiangdong
Liu, Zhendong
Zhu, Ming
PROCEEDINGS OF THE 2014 INTERNATIONAL CONFERENCE ON MECHATRONICS, CONTROL AND ELECTRONIC ENGINEERING, 2014, 113 : 684 - 687
[9] An improved particle swarm optimization algorithm and its application in reactive power optimization of power system
Yuan, HJ
Wang, CR
Zhang, JW
Sun, CJ
PROGRESS IN INTELLIGENCE COMPUTATION & APPLICATIONS, 2005, : 446 - 453
[10] Adaptive particle swarm for reactive power optimization in power systems
Zhang, Wen
Liu, Yutian
Clerc, Maurice
ENGINEERING INTELLIGENT SYSTEMS FOR ELECTRICAL ENGINEERING AND COMMUNICATIONS, 2006, 14 (03): : 161 - 167

← 1 2 3 4 5 →