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差分进化粒子群算法求解发电资源调度问题
引用本文:唐俊,胡志敏,王敏. 差分进化粒子群算法求解发电资源调度问题[J]. 计算机工程与应用, 2012, 48(8): 239-242
作者姓名:唐俊  胡志敏  王敏
作者单位:1.湖南城建职业技术学院 信息工程系,湖南 湘潭 411101 2.湖南机电职业技术学院 信息工程系,长沙 410151
基金项目:湖南省教育厅资助科研项目(No.08D030,07D018).
摘    要:为了有效地解决水火电力系统资源短期优化调度问题,提出了一种基于差分进化粒子群的调度算法。设计了水火电力系统资源调度问题的数学模型,给出了差分进化粒子群优化算法的框架,通过PSO种群和DE种群之间的信息交流机制以寻求全局最优位置,从而使算法具有动态自适应性,能够较容易地跳出局部最优。实验结果表明,该算法能有效解决水火发电资源调度问题,具有较好的应用价值。

关 键 词:差分进化  粒子群优化算法  水火电力系统  发电资源调度问题  

Differential evolution particle swarm algorithm for power resources scheduling problem
TANG Jun , HU Zhimin , WANG Min. Differential evolution particle swarm algorithm for power resources scheduling problem[J]. Computer Engineering and Applications, 2012, 48(8): 239-242
Authors:TANG Jun    HU Zhimin    WANG Min
Affiliation:1.Department of Information Engineering, Hunan Urban Construction College, Xiangtan, Hunan 411101, China 2.Department of Information Engineering, Hunan Mechanical & Electrical Polytechnic, Changsha 410151, China
Abstract:In order to solve hydrothermal power system resource short-term optimization scheduling problem, a novel scheduling solution based on differential evolution particle swarm optimization algorithm is proposed. The mathematical model of hydrothermal power sys- tem resource scheduling problem is designed, the framework of differential evolution particle swarm optimization algorithm is given, the information exchange mechanism between PSO population and DE population for the optimal particle location is introduced to make proposed algorithm easily jump out of local optimum with effective dynamic adaptability. Experimental result shows that pro- posed algorithm can solve the scheduling problem ofhydrothermal power system resource, and has the advantage of good application value.
Keywords:differential evolution  particle swarm optimization algorithm  hydrothermal power system  power system resource schedul-ing problem
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