Abstract
AbstractOperation optimization of the cascaded hydropower stations is of great significance to utilization efficiency of water, safety and stability of the grid, and comprehensive benefits of the reservoirs. In this study, a multi-objective operation optimization model of cascaded hydropower stations is established, and a novel multi-objective particle swarm optimization (MOPSO) algorithm is proposed to deal with the optimization problem of multi-objective, multi-constraint, high-dimension, and strong-coupling. A turbulence mechanism and a circular elimination strategy, are presented to strengthen the performance of MOPSO algorithm. The result of a case study indicates that, with the proposed techniques, the pro-posed algorithm performs well on both convergence and diversity of Pareto solutions, which implies that the proposed MOPSO algorithm can be used as an effective optimization tool to handle the multi-objective operation optimization of the cascaded hydropower stations.KeywordsBacteria quorum sensingCascaded hydropower stationsMulti-objective optimizationParticle swarm optimization
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