A Hybrid Particle Swarm Optimization for Short-Term Scheduling Optimization of Cascade Hydro Plants with Risk Management
A novel strategy for short-term scheduling optimization of cascade hydro plants with risk management is presented in this paper. Based on chance-constrained programming, the model takes into account the detailed representation of cascade hydro plants, which includes uncertainties, spatial-temporal constraints among cascaded reservoirs, etc. A hybrid particle swarm optimization (HPSO), in the class of evolutionary algorithms, for the solution of global optimization problems, is presented. Catastrophe theory which is concerned with natural evolutionary or survival-ofthe-fittest is utilized as an indication for the premature converge of particle swarm optimization (PSO), and the positions of particles are further adjusted in the search space according to chaos optimization. In this way, each particle competes and cooperates with its neighbors. The proof shows that EPSO is guaranteed to converge to the global optimization solution with probability one. The model presented is solved by a combination of HPSO and Monte Carlo simulation. Finally, a numerical example is served for demonstrating the feasibility of the method developed.
J. Q. Zhu J. K. Wu G. T. Chen H. L. Zhang
Department of Electrical Engineering Guangxi University Wuzhou, Guangxi, China 543000 Department of Electrical Engineering Guangxi University Nanning, Guangxi, China 530022 Wuzhou Power Supply Bureau Guangxi Electric Net Company Nanning, Guangxi, China 530004 Guangxi Fangyuan Elctric Power Co.LTD Guangxi Electric Net Company Nanning, Guangxi, China 530004
国际会议
南宁
英文
2007-07-20（万方平台首次上网日期，不代表论文的发表时间）