[1]马细霞,储冬冬..粒子群优化算法在水库调度中的应用分析[J].郑州大学学报(工学版),2006,27(04):121-124.[doi:10.3969/j.issn.1671-6833.2006.04.029]
　Ma Xiaoxia,Storage winter winter.Application analysis of particle swarm optimization algorithm in reservoir scheduling [J].Journal of Zhengzhou University (Engineering Science),2006,27(04):121-124.[doi:10.3969/j.issn.1671-6833.2006.04.029]

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粒子群优化算法在水库调度中的应用分析()

分享到：

《郑州大学学报(工学版)》[ISSN:1671-6833/CN:41-1339/T]

卷:

27

期数:

2006年04期

页码:

121-124

栏目:

出版日期:

1900-01-01

文章信息/Info

Title:

Application analysis of particle swarm optimization algorithm in reservoir scheduling

作者:

马细霞; 储冬冬.

郑州大学环境与水利学院,河南,郑州,450001, 郑州大学环境与水利学院,河南,郑州,450001

Author(s):

Ma Xiaoxia; Storage winter winter

关键词:

粒子群算法;  水库优化调度;  罚函数

Keywords:

particle swarm algorithm;  Optimal scheduling of reservoirs;  Penalty function

DOI:

10.3969/j.issn.1671-6833.2006.04.029

文献标志码:

A

摘要:

寻求水库最优调度轨迹过程线是水库优化调度中的经典、难点问题.本文在分析以往水库优化调度模型优缺点的基础上,提出了基于粒子群优化算法(Particle Swarm Optimization,简称PSO)的水库优化调度模型,并通过引入罚函数解决强约束问题.以某综合利用水库优化调度为实例进行研究,并与动态规划模型计算结果进行对比分析.结果表明:粒子群优化算法原理简单,易于编程实现,而且占用计算机内存小,计算速度快,适用于年内水库优化调度规则的确定.

Abstract:

Seeking the optimal reservoir scheduling trajectory process line is a classic and difficult problem in reservoir optimal scheduling. Based on the analysis of the advantages and disadvantages of previous reservoir optimization scheduling models, this paper proposes a reservoir optimization scheduling model based on Particle Swarm Optimization (PSO), and solves the problem of strong constraint by introducing a penalty function. The optimal scheduling of a comprehensive utilization reservoir is studied as an example, and the calculation results of dynamic programming model are compared and analyzed. The results show that the particle swarm optimization algorithm is simple in principle, easy to program, occupies small computer memory, and has fast calculation speed, which is suitable for determining the optimal scheduling rules of reservoirs within the year.

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