基于PSO算法与协同进化算法的地区电网无功优化模型  

Reactive Power Optimization Model for Local Power System Based on Co-evolutionary Algorithm and PSO

作　　者：康丽[1] 陈裔生[2] 杨勇[2] 华栋[3] 

机构地区：[1]东莞理工学院电子工程学院,广东东莞523808 [2]广东电网公司佛山供电局,广东佛山528000 [3]华南理工大学电力学院,广东广州510641

出　　处：《水电能源科学》2012年第8期155-158,共4页Water Resources and Power

基　　金：2011教育部新世纪优秀人才支持计划基金资助项目(NCET080207)

摘　　要：电力系统无功优化属于非线性优化范畴,传统的数学规划算法处理时存在较大的局限性,针对大规模电网全局无功电压优化控制困难,提出了基于协同进化框架的合作协同进化粒子群优化算法(PSO)的电力系统无功优化方法,构建了数学模型。实际大电网计算结果表明,该算法寻优质量高、收敛性好、计算复杂度低,适合求解大规模系统无功优化问题。Reactive power optimization of power system belonging to nonlinear optimization category, there are some limitations of traditional mathematical programming algorithm for solving this problem. In view of difficulty for reactive power optimization voltage control in large-scale power grid, a mathematical model with co-evolutionary algorithm and particle swarm optimization algorithm （PSO） is proposed to solve reactive power optimization problem. The result of an instance shows that the proposed algorithm has advantages of high quality solution, good convergence and low computational complexity, which is suited to solve large-scale reactive power optimization of power system .

关 键 词：无功优化 协同进化算法 粒子群算法 优化模型 地区电网 

分 类 号：TM711[电气工程—电力系统及自动化] TM714