Power generation expansion planning with emission control: a nonlinear model and a GA-based heuristic approach

This paper presents an application of genetic algorithms (GA) for solving the long‐term power generation expansion planning (PGEP) problem, a highly constrained nonlinear discrete optimization problem. The problem is formulated into a mixed integer nonlinear programming (MINLP) program that determin...

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Veröffentlicht in:	International journal of energy research Jg. 30; H. 2; S. 81 - 99
Hauptverfasser:	Sirikum, Jiraporn, Techanitisawad, Anulark
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Chichester, UK John Wiley & Sons, Ltd 01.02.2006 Wiley
Schlagworte:	Applied sciences emission modelling Energy Energy. Thermal use of fuels Exact sciences and technology genetic algorithms Installations for energy generation and conversion: thermal and electrical energy mixed integer nonlinear programming power generation expansion planning Thermal power plants Costs power generation expansion planning Power production Thermal power plant Non linear programming genetic algorithms Modeling Optimization Case study mixed integer nonlinear programming emission modelling Genetic algorithm Heuristic method Models Planning Expansion
ISSN:	0363-907X, 1099-114X
Online-Zugang:	Volltext
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