广东工业大学学报 ›› 2012, Vol. 29 ›› Issue (4): 49-53.doi: 10.3969/j.issn.1007-7162.2012.04.010

• 综合研究 • 上一篇    下一篇

基于虚拟极值粒子群的电网无功优化研究

胡廷鹤,孟安波   

  1. 广东工业大学 自动化学院,广东 广州 510006
  • 收稿日期:2012-01-29 出版日期:2012-12-25 发布日期:2012-12-25
  • 作者简介:胡廷鹤(1985-),男,硕士研究生,主要研究方向为电力系统运行分析与控制以及新能源发电.
  • 基金资助:

    广东省电力节能与新能源技术重点实验室资助项目(ZDSYS200701)

Reactive Power Optimization Based on Virtual Extreme Particle Swarm Optimization in Electrical Power System

Hu Tinghe,Meng An-bo   

  1. School of Automation, Guangdong University of Technology,Guangzhou 510006,China
  • Received:2012-01-29 Online:2012-12-25 Published:2012-12-25

摘要: 为解决电网无功优化中因控制变量种类多、维数高而导致优化结果精度低且容易陷入局部最优等问题,提出一种基于虚拟极值的粒子群算法对电网进行无功优化.该算法采用蒙特卡洛模拟技术对初始种群进行选择,保证取值的多样性;加入影响因子,根据控制变量的种类分区间制定不同的优化参数;引入虚拟全局极值,帮助粒子跳出局部最优.应用该算法对IEEE-14节点系统进行无功优化计算并与传统粒子群算法进行比较,结果表明虚拟极值粒子群算法在电网无功优化计算中具有较强的全局搜索能力和较高的收敛精度.

关键词: 电力系统;虚拟极值;无功优化;蒙特卡洛模拟;领域拓扑结构

Abstract: To overcome the problem of low accuracy and easily falling into local optimum, the local extreme caused by too much variety and high dimension of control variables, it proposes a new type of particle swarm algorithm, based on virtual extreme for reactive power optimization. The algorithm adopts the Monte Carlo simulation technology to the initial population selection to ensure the diversity of value. The impact factor was added, and the optimization parameters were set according to the control variables. The virtual global extreme was introduced to help particles jump out of the local optimum. At last, the proposed algorithm was applied to the IEEE-14bus system. The comparative results show that this virtual extreme particle swarm optimization algorithm has better search capability and higher degree of convergence for reactive power optimization.

Key words: electrical power system; virtual extreme; reactive power optimization; Monte Carlo simulation; topological structure of the field

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