Study On Dynamic Economic Emission Dispatch Of Hybrid Power Systems Using Soft Computing Techniques

Abstract

Economic load dispatch (ELD) is the allocation of generators to meet the load with a minimum cost of generation. The main aim is to optimize money and satisfy load balance and certain limits which will serve some change in load and constraints. This paper deals with the optimization of ELD problem using Constriction Factor Based Particle Swarm Optimization (CFBPSO) algorithm. The constriction factor as proposed in earlier works is very useful for the convergence of the PSO algorithm. This factor is varied in this work and an improved result is observed. Two case studies are carried out on 10-unit and 20-unit system for the verification of viability and execution of the suggested approach. The suggested approach is implemented for an hourly dynamic and static load using MATLAB. The primary objective is to reduce the cost and the improved one is compared with the standard CFBPSO algorithm for this cost. Improvement in the result is observed. newline Then, the dynamic Economic Load Dispatch (ELD) problem with Plug-in Electric Vehicles (PEVs) is solved using Social Spider Algorithm (SSA). SSA is used to schedule the load demand among all the thermal generating units at minimum generation cost although fulfilling the system constraints. PEVs can be used as loads and energy sources. The SSA has been implemented to solve the dynamic ELD problem of the 10-unit thermal generation system. The outcomes were better when compared with Particle Swarm Optimization (PSO) and Improved Constriction Factor Based PSO ICFBPSO techniques. newline newline