DocumentCode
2333289
Title
Research of constraint handling techniques for Economic Load Dispatch of power system
Author
Wang, Yu ; Li, Bin ; Jing, Guang Mei ; Wang, Peng ; Wang, Jianyu
Author_Institution
Dept. of Electron. Sci. & Technol., Univ. of Sci. & Technol. of China, Hefei, China
fYear
2010
fDate
18-23 July 2010
Firstpage
1
Lastpage
8
Abstract
Economic Load Dispatch (ELD) optimization is an important and difficult task in power system planning. Previously, most of the research mainly focused on proposing various evolutionary algorithms (EAs) to pursue better results of ELD problems. However, few comprehensive analysis of the effects of various constraint handling techniques (CHTs) on the performance of EA-based techniques are available so far. In this paper, we try to fill this gap by experimentally testing the algorithmic variants of combining four effective and widely used EAs with three CHTs. From the experimental results on the ELD problems with valve-point and those problems with both valve-point and multiple-fuel effect, several important conclusions can be achieved, including 1) for the low scale ELD problem with valve-point only, the selection of EAs is more important than CHTs; 2) for the large scale problems, CHTs play crucial roles; 3) the appropriate combination of EA and CHT is helpful to achieve better performance. This study is also expected to provide solid basis for further strengthening the robustness of EAs for ELD optimization. It is also interesting to observe that the experimental results obtained in this paper are much better than those of the previous effective ELD optimization algorithms.
Keywords
evolutionary computation; optimisation; power generation dispatch; power generation economics; power system planning; constraint handling; economic load dispatch optimization; evolutionary algorithms; multiple fuel effect; power system planning; valve point; Algorithm design and analysis; Computational efficiency; Cost function; Generators; Particle swarm optimization;
fLanguage
English
Publisher
ieee
Conference_Titel
Evolutionary Computation (CEC), 2010 IEEE Congress on
Conference_Location
Barcelona
Print_ISBN
978-1-4244-6909-3
Type
conf
DOI
10.1109/CEC.2010.5586470
Filename
5586470
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