MULTI-OBJECTIVE COMBINED ECONOMIC AND EMISSION DISPATCH BY FULLY INFORMED PARTICLE SWARM OPTIMIZATION

Muhammad F. Tahir, Kashif Mehmood, Chen Haoyong, Atif Iqbal, Adeel Saleem, and Shaheer Shaheen

Keywords

Combined economic emission dispatch problem, economic dispatch, fully inform particle, price penalty factor, swarm optimization, valvepoint loading effect

Abstract

Combined economic and emission dispatch problem (CEEDP) leads towards economical and greener power system by improving the economy (reducing fuel costs) and minimizing emission (reducing greenhouse gases) while fulfilling power demands. In this work, a fully informed particle swarm optimization (FIPSO) is proposed to optimize CEEDP that is considered a multi-objective optimization problem. Higher accuracy in case of heavily constrained optimization in comparison to simple PSO makes FIPSO even more useful while addressing CEEDP. This research does not focus only to solve CEEDP by FIPSO algorithm but also to compare it with PSO and is tested on IEEE 30 bus benchmark system with six generators and 20 load buses. In addition, ED problem with three-generator system is solved by including valve-point loading effect, and its comparison with other popular algorithms is made. Optimizing accuracy, fast convergence, less computational time and fewer emission values by the proposed algorithm show its superiority in comparison to other conventional methods.

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