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《Journal of Hydroelectric Engineering》 2012-01
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Application of self-adaptive hybrid particle swarm optimization algorithm to optimal operation of cascade reservoirs

WANG Sen1,WU Xinyu1,CHENG Chuntian1,GUO Youan2,LI Honggang2(1.Institute of Hydropower & hydroinformation,Dalian University of Technology,Dalian 116024; 2.HydroLancang River Corporation,Kunming 650000)  
A self-adaptive hybrid particle swarm optimization algorithm(AHPSO) is proposed to solve the long-term optimal operation model of cascade reservoirs.With total power output as objective function,this model generates initial solutions with chaos and defines variables of particle energy,particle similarity and their thresholds to describe the algorithm's self-adaptive changes and the swarm-evolving degree.In the model,a random greedy searching strategy of neighborhood is adopted to overcome the shortcoming of slow evolving at the later stage.Application in a case study of the cascade reservoirs on the Lancangjiang river shows that the self-adaptive AHPSO is better in convergence and optimized solution than the traditional particle swarm method and that it is comparable to the progressive optimization algorithm but its computational cost is lower.
【Fund】: 国家自然科学基金(50979010) 国家自然科学基金(51109024);; 国家杰出青年科学基金(51025934)
【CateGory Index】: TV737
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