Investigating Economic Emission Dispatch Problem Using Improved Particle Swarm Optimization Technique
This paper presents utilization of particle swarm optimization in solving combined economic emission dispatch (EED) problem. The economic emission dispatch is an important problem in power sector as it combines two major objectives viz., cost minimization and emission minimization while maintaining operational constraints. Several meta-heuristic techniques have been developed in recent times and have been applied on power dispatch problems. PSO is such a meta-heuristic technique where time-varying acceleration coefficients (TVAC) are incorporated and used in the EED problem in this work. Thus it addresses the techno-economic-environmental aspect of power system operation. Economic emission dispatch problem is first resolved using weighted sum method, and second trade-off curve between two objectives has been found, referred to as pareto front which traces solutions obtained by non-dominated approach of the problem. The formulation is implemented on IEEE 30 bus test system and outcome obtained validates effectiveness of this research work.
KeywordsEconomic emission dispatch Time-varying acceleration coefficients incorporated particle swarm optimization (TVAC-PSO) Meta-heuristic techniques Non-dominated solutions
The authors express thanks to all members of Power Engineering department, Jadavpur University for providing support for research work. This research work is helped by project of (DRS and UPE II, UGC, DST-PURSE II, GOI) awarded to the Power Engineering department, Jadavpur University, Kolkata.
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