Title :
Extremal optimization for unit commitment problem for power systems
Author :
Jin Ding ; Yong-Zai Lu ; Jian Chu
Author_Institution :
State Key Lab. of Ind. Control Technol., Zhejiang Univ., Hangzhou, China
Abstract :
This paper introduces extremal optimization (EO) method to solve unit commitment problem for power systems. EO is a local-search heuristic algorithm and originally developed from the fundamentals of statistical physics. In the implementation of EO for unit commitment (UC) problem, a novel problem-specific mutation operator is introduced and rule-based heuristic constraint-repairing techniques are devised. Simulation results on power systems which are composed of up to 100-units over a scheduling horizon of 24-hours demonstrate competitive performance with EO method compared with other existing methods for UC problem.
Keywords :
optimisation; power generation dispatch; power generation scheduling; search problems; statistical analysis; EO method; UC problem; extremal optimization method; local-search heuristic algorithm; power systems; problem-specific mutation operator; rule-based heuristic constraint-repairing techniques; scheduling horizon; statistical physics; time 24 hour; unit commitment problem; Cost function; Fuels; Indexes; Power generation; Power systems; Spinning; combinatorial optimization; extremal optimization; power system; unit commitment;
Conference_Titel :
Power and Energy Society General Meeting, 2012 IEEE
Conference_Location :
San Diego, CA
Print_ISBN :
978-1-4673-2727-5
Electronic_ISBN :
1944-9925
DOI :
10.1109/PESGM.2012.6343918
