DocumentCode :
3469227
Title :
Economic dispatch using simplified personal best oriented particle swarm optimizer
Author :
Chen, C.H.
Author_Institution :
Dept. of Electr. Eng., Tungnan Univ., Taipei
fYear :
2008
fDate :
6-9 April 2008
Firstpage :
572
Lastpage :
576
Abstract :
In this paper, the simplified personal best oriented particle swarm optimizer (SPPSO) is employed to solving economic power dispatch problem considering transmission losses. SPPSO is a simplified version of personal best oriented particle swarm optimizer (PPSO), stemming from particle swarm optimization (PSO). Although one term is eliminated from the velocity updating rule, the performance of SPPSO is not affected significantly, especially for small scale problems. Nevertheless, it gains the advantage of computation efficiency. The usefulness and capability of the proposed algorithm is verified via testing on three power systems having different numbers of committed generators. The optimal solutions obtained by the proposed method are compared with those obtained by other methods posted in literature. The results show that the proposed method indeed capable of obtaining high quality solutions quickly.
Keywords :
matrix algebra; particle swarm optimisation; power generation dispatch; power transmission economics; economic power dispatch problem; particle swarm optimizer; power system generators; power system testing; transmission losses; Ant colony optimization; Cost function; Fuel economy; Particle swarm optimization; Power demand; Power generation; Power generation economics; Power systems; Propagation losses; System testing; Economic Dispatch; Particle Swam Optimization; Transmission loss;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Electric Utility Deregulation and Restructuring and Power Technologies, 2008. DRPT 2008. Third International Conference on
Conference_Location :
Nanjuing
Print_ISBN :
978-7-900714-13-8
Electronic_ISBN :
978-7-900714-13-8
Type :
conf
DOI :
10.1109/DRPT.2008.4523471
Filename :
4523471
Link To Document :
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