Title :
Hydroelectric Unit Commitment by Enhanced PSO
Author :
Liu, Shuangquan ; Li, Xiaoting
Author_Institution :
Post-Doctoral Workstation of Yunnan Power Grid Corp., Kunming, China
Abstract :
The constrained hydroelectric unit commitment problem is turned into an unconstrained optimization problem by means of penalty function method, and to improve the diversity and search ability, the classical particle swarm optimization (PSO) approach is enhanced by incorporating a genetic crossover operator and a self-adaptive decreasing inertia weight. Then the enhanced PSO is used to solve the hydroelectric unit commitment problem, with the numerical results, the proposed method is verified to be feasible and effective.
Keywords :
hydroelectric power; particle swarm optimisation; enhanced PSO; genetic crossover operator; hydroelectric unit commitment; particle swarm optimization; penalty function method; self-adaptive decreasing inertia weight; unconstrained optimization problem; Economics; Electricity; Gallium; Hydroelectric power generation; Optimization; Schedules; Search problems;
Conference_Titel :
E-Product E-Service and E-Entertainment (ICEEE), 2010 International Conference on
Conference_Location :
Henan
Print_ISBN :
978-1-4244-7159-1
DOI :
10.1109/ICEEE.2010.5661259