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基于模拟退火的粒子群算法在水电站水库优化调度中的应用
引用本文:申建建,程春田,廖胜利,张俊.基于模拟退火的粒子群算法在水电站水库优化调度中的应用[J].水力发电学报,2009,28(3).
作者姓名:申建建  程春田  廖胜利  张俊
作者单位:大连理工大学水电水信息研究所,辽宁,大连,116024  
基金项目:国家自然科学基金,国家重点基础研究发展规划(973计划) 
摘    要:介绍了一种基于模拟退火的粒子群算法,并用其求解以水电站年发电量最大建立的优化调度的数学模型.考虑到基本的粒子群算法(PSO)后期粒子趋向同一化,使其进化速度变慢,精度较差,本文将模拟退火的思想应用到具有杂交和变异的粒子群算法当中,通过模拟退火的降温过程来提高算法后期的进化速度和精度.最后,以普定水电站的优化调度为例进行了计算,结果表明,该算法的性能较基本粒子群算法有了较大改善,且明显优于常规调度方法和动态规划.

关 键 词:水电工程  优化调度  模拟退火  粒子群  水电站

Optimization of hydropower station operation by using particle swarm algorithm based on simulated annealing
SHEN Jianjian,CHENG Chuntia,LIAO Shengli,ZHANG Jun.Optimization of hydropower station operation by using particle swarm algorithm based on simulated annealing[J].Journal of Hydroelectric Engineering,2009,28(3).
Authors:SHEN Jianjian  CHENG Chuntia  LIAO Shengli  ZHANG Jun
Affiliation:Institute of Hydropower & Hydroinformation;Dalian University of Technology;Dalian 116024
Abstract:The hybrid algorithm is presented based on particle swarm optimization(PSO) of simulated annealing(SA) approaches,and the mathematical model is appliad to the optimal operation of reservoir in order to get its maximum annual generation output. In consideration of stagnation phenomenon in the later phase of the PSO caused by diversity scarcity of particles,the SA approach is applied to the PSO with crossover and mutation to improve the evolutionary rate and precision of the algorithm through temperature decr...
Keywords:hydropower emgineering  optimal operation  simulated annealing  particle swarm optimization  hydropower station  
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