Particle Swarm Optimization Based on Cultural Algorithm for Short-Term Optimal Operation of Cascade Hydropower Stations

Natural Computation, 2009. ICNC '09. Fifth International Conference（2009）

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摘要

Difficulties likely exist in optimal reservoir operation along with discreteness and nonlinear constraints. Therefore, particle swarm optimization based on cultural Algorithm (PSO-CA) is presented in this paper for overcoming these defects. In this article the evolutionary mechanism of particle swarm optimization algorithm (PSO) is guided by cultural algorithm (CA). PSO-CA uses PSO in population space and guides the evolution by shape knowledge and standardization knowledge in belief space. An example is also used to show that the PSO-CA algorithm has a better applied prospect for its high reliability and fast operation speed in global optimization.

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关键词

cascade hydropower stations,optimal reservoir operation,evolutionary mechanism,cultural algorithm,particle swarm optimisation,global optimization,short-term optimal operation,belief space,hydroelectric power stations,fast operation speed,shape knowledge,particle swarm optimization algorithm,population space,pso-ca algorithm,standardization knowledge,reservoirs,optimal operation of reservoir,particle swarm optimization,algorithm design and analysis,shape,optimization,standardization

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