| 基于粒子群优化算法与混合罚函数 |
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| 引用本文： | 崔鹏程,陈明榜,向铁元.基于粒子群优化算法与混合罚函数[J].中国农村水利水电,2007,0(2):90-92. |
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| 作者姓名： | 崔鹏程 陈明榜 向铁元 |
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| 作者单位： | 武汉大学电气工程学院,湖北,武汉,430072 |
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| 摘 要： | 粒子群算法(PSO)具有简单易实现，可调参数少的优点。将其用于最优潮流的求解，结合混合罚函数来限制最优潮流的约束条件，使粒子群算法的寻优速度加快，迭代次数减少。通过在IEEE9节点和IEEE30节点上的仿真计算表明，该算法在优迭代速度和收敛精度上都取得了较好的效果。
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| 关 键 词： | 粒子群算法（PSO） 最优潮流（OPF） 混合罚函数（Mult-SUMT） |
| 文章编号： | 1007-2284(2007)02-0090-03 |
| 修稿时间： | 2006-05-16 |
Optimal Power Flow Calculation by Particle Swarm Optimization and Multi-SUMT |
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| CUI Peng-cheng,CHEN Ming-bang,XIANG Tie-yuan.Optimal Power Flow Calculation by Particle Swarm Optimization and Multi-SUMT[J].China Rural Water and Hydropower,2007,0(2):90-92. |
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| Authors: | CUI Peng-cheng CHEN Ming-bang XIANG Tie-yuan |
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| Institution: | School of Electrical Engineering, Wuhan University, Wuhan 430072, China |
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| Abstract: | A brief introduction of Particle Swarm Optimization(PSO),one of the new evolutionary optimization algorithms,is given in this paper.It is used in the solution of the optimal power flow along with the Multi-Sequential Unconstrained Minimization Technique,which is composed of interior point penalty function and exterior point penalty function.PSO can be implemented easily with few parameters need to be identified.The hybrid algorithms are applied to the calculation of IEEE9 bus and IEEE30 bus systems respectively.The results prove that the application of the PSO and Multi-Sequential Unconstrained Minimization Technique can improve the speed of iteration and the precision of convergence. |
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| Keywords: | particle swarm optimization optimal power flow multi-sequential unconstrained minimization technique |
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