Real-coded Genetic Algorithm for solving Multi-Area Economic Dispatch problem

Author

Huynh Thi Thanh Binh ; Tran Kim Toan

Author_Institution

Hanoi Univ. of Sci. & Technol., Hanoi, Vietnam

fYear

2013

fDate

16-19 April 2013

Firstpage

97

Lastpage

101

Abstract

We consider the Multi-Area Economic Dispatch problem (MAEDP) in deregulated power system environment for practical multi-area cases with tie line constraints. Our objective is to generate allocation to the power generators in such a manner that the total fuel cost is minimized while all operating constraints are satisfied. This problem is NP-hard. In this paper, we propose Real-coded Genetic Algorithm (RCGA) to solve MAEDP. The experimental results are reported to show the efficiency of proposed algorithms compared to Particle Swarm Optimization with Time-Varying Acceleration Coefficients (PSO-TVAC).

Keywords

electricity supply industry deregulation; genetic algorithms; power generation dispatch; power generation economics; MAEDP; NP-hard problem; PSO-TVAC; RCGA; deregulated power system; multiarea economic dispatch problem; particle swarm optimization; power generators; real-coded genetic algorithm; tie line constraints; time-varying acceleration coefficients; Cost function; Economics; Fuels; Generators; Genetic algorithms; Sociology; Statistics; Genetic Algorithm; Multi-Area Economic Dispatch;

fLanguage

English

Publisher

ieee

Conference_Titel

Computational Intelligence for Engineering Solutions (CIES), 2013 IEEE Symposium on

Conference_Location

Singapore

Type

conf

DOI

10.1109/CIES.2013.6611735

Filename

6611735