Application of immune algorithm-based particle swarm optimization for optimized load distribution among cascade hydropower stations

Authors:
Anqiang Li;Liping Wang;Jiqing Li;Changming Ji
Affiliations:
The State's Key Laboratory of Water Resource and Hydropower Engineering Science, Wuhan University, Wuhan, 430072, China;College of Renewable Energy, North China Electric Power University, Beijing, 102206, China;College of Renewable Energy, North China Electric Power University, Beijing, 102206, China and Department of Land, Air and Water Resources, University of California Davis, Davis, 95616, USA;College of Renewable Energy, North China Electric Power University, Beijing, 102206, China
Venue:
Computers & Mathematics with Applications
Year:
2009

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Short-term scheduling of cascade reservoirs using an immune algorithm-based particle swarm optimization

Computers & Mathematics with Applications

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Abstract

The immune algorithm-based particle swarm optimization (IA-PSO), which is proposed by involving the immune information processing mechanism into the original particle swarm optimal algorithm, improves the ability to find the globally excellent result and the convergence speed with its special concentration selection mechanism and immune vaccination. Based on analyzing the model of load distribution among cascade hydropower stations and the traits of IA-PSO, the corresponding mathematical description and the solution procedure made with IA-PSO are given in detail. The result demonstrates that IA-PSO can achieve both a superior load distribution scheme and a higher convergence precision as compared to PSO, and will hopefully be applied to solving more extensive optimization problems.