Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/12004
Title: Optimal generation expansion planning via improved genetic algorithm approach
Authors: Chung, TS
Li, YZ
Wang, ZY
Keywords: Generation expansion planning
Genetic algorithm
Optimal mix problem
Issue Date: 2004
Publisher: Elsevier
Source: International journal of electrical power and energy system, 2004, v. 26, no. 8, p. 655-659 How to cite?
Journal: International journal of electrical power and energy systems 
Abstract: This paper presents an improved genetic algorithm approach developed to solve the optimal generation expansion planning problem of an all-thermal power system. The problem is focused on the optimal mix of generation units in a given target year with the constrained consideration of certain thermal units committed during peaking periods. The problem formulation thus requires considering the technical limits of the thermal unit outputs due to the large difference between the daily peak-load and valley-load demands. In addition, the implementation issues of penalty coefficients, ranking, adaptive crossover and mutation probabilities are effectively considered in the algorithm. The test results on a 14-generator power system are presented. The results show that the methodology is effective in solving such mixed integer, constrained nonlinear generation expansion problem.
URI: http://hdl.handle.net/10397/12004
ISSN: 0142-0615
DOI: 10.1016/j.ijepes.2004.04.012
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