Economic load dispatch with environmental emission using MRPSO

The economic load dispatch (ELD) is the online process for allocating the generation among the available generating unit to fulfill the load demand in such a way to minimize the total generation cost and satisfying the equality and inequality constraints. In literature many papers have used the particle swarm optimization to solve the economic load dispatch problem with emission constraint which is a population based optimization technique inspired by sociological behavior of bird flocking, It can solve ELD problem to a wide range but it lacks global search ability in the last stage of iterations. So it is difficult to get the global optimal solution for the ELD problem by using PSO. At the time of generation of large power, fossil fuel burns at power plants which produces many toxic gases and pollute the environment. The main objective of this paper is to minimize the total generation cost of thermal units as well as to minimize the pollutant emission emitted by toxic gases. This paper, a novel PSO with a moderate random search strategy called as moderate-random particle swarm optimization (MRPSO) is used for solving ELD problem with emission as constraints. MRPSO enhances the ability of particles to explore the solution spaces more effectively and increases their convergence rates. The validation of the proposed MRPSO algorithm is demonstrated through its application for six generator systems with emission constraints for various load demand.