Title :
Application of Simulated Annealing Particle Swarm Algorithm in Optimal Scheduling of Hydropower Plant
Author :
Bin, Li ; Jun, Rui
Author_Institution :
Nanjing Autom. Res. Inst., Nanjing, China
Abstract :
Taking Hongjiadu hydropower plant as an instance, an algorithm of Simulated Annealing Particle Swarm Optimization (SAPSO) is proposed to optimize the regulation of hydropower plant. Practical application demonstrates that SAPSO solve the regulation problem of hydropower plant well, which is a nonlinear problem with complicated constraints. Compared with Standard Particle Swarm Optimization (SPSO), SAPSO is more efficient and simple and has high precision and convergence velocity.
Keywords :
hydroelectric power stations; particle swarm optimisation; simulated annealing; Hongjiadu hydropower plant; hydropower plant; optimal regulation; optimal scheduling; simulated annealing particle swarm optimization; Hydroelectric power generation; Mathematical model; Optimal scheduling; Particle swarm optimization; Reservoirs; Scheduling algorithm; Simulated annealing; Water conservation; Water resources; Water storage; hydropower plant; optimal regulation; particle swarm optimization; simulated annealing;
Conference_Titel :
Artificial Intelligence and Computational Intelligence, 2009. AICI '09. International Conference on
Conference_Location :
Shanghai
Print_ISBN :
978-1-4244-3835-8
Electronic_ISBN :
978-0-7695-3816-7
DOI :
10.1109/AICI.2009.161
