Title :
Particle swarm optimization solution to emission and economic dispatch problem
Author :
Kumar, A.I.S. ; Dhanushkodi, K. ; Kumar, J.J. ; Paul, C.K.C.
Author_Institution :
Karunya Inst. of Technol., Coimbatore, India
Abstract :
The paper presents an efficient and reliable particle swarm optimization (PSO) algorithm based technique for solving emission and economic dispatch (E&ED) problems. The harmful ecological effects of the emission of particulate and gaseous pollutants from fossil fuel power plants can be reduced by proper load allocation among the various generating units of the plants. This load allocation, however, may lead to an increase in the operating costs of the generating units. It is therefore necessary to find a solution which gives a balanced result between emission and cost. A particle swarm optimization solution to E&ED problems is presented. The results are obtained for a test system with six generating units. The performance of the PSO is compared with conventional methods, real coded genetic algorithm and hybrid genetic algorithm. The results clearly show that the proposed method gives a global optimum solution compared to the other methods.
Keywords :
air pollution control; environmental economics; genetic algorithms; load distribution; optimisation; thermal power stations; emission and economic dispatch problem; emission problem; fossil fuel power plants; gaseous pollutants; harmful ecological effects; hybrid genetic algorithm; load allocation; operating costs; particle swarm optimization; particulate pollutants; real coded genetic algorithm; Costs; Environmental economics; Fossil fuels; Fuel economy; Genetic algorithms; Paper technology; Particle swarm optimization; Pollution; Power generation; Power generation economics;
Conference_Titel :
TENCON 2003. Conference on Convergent Technologies for the Asia-Pacific Region
Print_ISBN :
0-7803-8162-9
DOI :
10.1109/TENCON.2003.1273360