Title :
Environmental/economic dispatch of thermal units using an elitist multiobjective evolutionary algorithm
Author :
Rughooputh, Harry C S ; King, Robert T F Ah
Author_Institution :
Mauritius Univ., Reduit, Mauritius
Abstract :
The classical economic dispatch problem is to operate electric power systems so as to minimize the total fuel cost. This single objective can no longer be considered alone due to the environmental concerns that arise from the emissions produced by fossil-fueled electric power plants. The environmental/economic dispatch problem has been commonly been solved by considering each objective separately or as a weighted sum of both objectives. Multiobjective evolutionary algorithms can find multiple Pareto-optimal solutions in one single run and this ability makes them attractive for solving problems with multiple and conflicting objectives. The non-dominated sorting genetic algorithm-II (NSGA-II), an elitist multiobjective evolutionary algorithm is used for solving the environmental/economic dispatch problem. Simulation results are presented for two test systems.
Keywords :
Pareto optimisation; fossil fuels; genetic algorithms; load dispatching; power plants; Pareto-optimal solutions; economic dispatch problem; electric power systems; elitist multiobjective evolutionary algorithm; fossil-fueled electric power plants; nondominated sorting genetic algorithm-II; total fuel cost minimization; Costs; Dispatching; Environmental economics; Evolutionary computation; Fuel economy; Hopfield neural networks; Linear programming; Optimization methods; Power generation economics; Power system economics;
Conference_Titel :
Industrial Technology, 2003 IEEE International Conference on
Print_ISBN :
0-7803-7852-0
DOI :
10.1109/ICIT.2003.1290230