DocumentCode :
2896096
Title :
An improved binary particle swarm optimization for unit commitment problem
Author :
Li, Peng ; Xi, Peng ; Fei, Liqiang ; Qian, Jiang ; Chen, Jianjie
Author_Institution :
Sch. of Electr. & Electron. Eng., North China Electr. Power Univ., Baoding, China
fYear :
2011
fDate :
6-9 July 2011
Firstpage :
1306
Lastpage :
1310
Abstract :
This paper proposed a new approach combining priority list (PL) with binary particle swarm optimization (BPSO) to solve unit commitment (UC) problem. At first, PL method was used to determine the initial UC, and then the optimization window was determined according to the results, at last the BPSO method was adopted to solve the UC problem within the window. The window is to reduce the computing time and improve the optimization accuracy. In each iteration, the adjustment heuristic strategy was applied to revise the particle to meet the generators´ constraints. This paper adopted Lambda-iteration method combining with dichotomy algorithm to solve the economic dispatch (ED) problem. The simulation results showed that the proposed method is indeed capable of obtaining higher quality solutions.
Keywords :
electric generators; iterative methods; particle swarm optimisation; power generation dispatch; power generation economics; power generation scheduling; BPSO method; Lambda- iteration method; PL method; UC problem; computing time; dichotomy algorithm; economic dispatch problem; generator constraint; heuristic strategy; improved binary particle swarm optimization; unit commitment problem; Economics; Generators; Optimization; Particle swarm optimization; Power systems; Production; Spinning; binary particle swarm optimization; heuristic adjustment; priority list; unit commitment;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Electric Utility Deregulation and Restructuring and Power Technologies (DRPT), 2011 4th International Conference on
Conference_Location :
Weihai, Shandong
Print_ISBN :
978-1-4577-0364-5
Type :
conf
DOI :
10.1109/DRPT.2011.5994097
Filename :
5994097
Link To Document :
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