The comparison with the different reported techniques demonstrates the superiority of the proposed MOPSO in terms of the diversity of the Pareto-optimal solutions obtained. The results demonstrate the capabilities of the proposed MOPSO technique to generate a set of well-distributed Pareto-optimal solutions in one single run. Several optimization runs of the proposed approach have been carried out on a standard test system. The proposed MOPSO technique has been implemented to solve the EED problem with competing and non-commensurable cost and emission objectives. The proposed MOPSO technique evolves a multiobjective version of PSO by proposing redefinition of global best and local best individuals in multiobjective optimization domain. ComparativeĪnalysis of the results obtained by both the methods has beenĪ new multiobjective particle swarm optimization (MOPSO) technique for environmental/economic dispatch (EED) problem is proposed in this paper. Generator system and five generator system. The solution methodologies have been validated on three
Method and Particle Swarm Optimization (PSO) technique. This paper, EED problem has been solved using Lambda Iteration
Problem called Economic Emission Dispatch (EED) problem. Have resulted in multi-dimensional power system optimization The combination ofīoth the objectives i.e. In addition to minimization of operating cost. In order to get clean energy,Įmission control has become an important operational objective To increase in emissions in the environment which is the primeĬoncern for power system planners. In present scenario, expansion in power generation has resulted
Is minimized while meeting load demand, power operating limits. Problem of ELD in power system is to plan the power output forĮach committed generating unit in such a way that operating cost Which gives rise to Economic Load Dispatch (ELD) problem. Necessary to operate the thermal power plants most economically, With the increase in energy demand, it becomes
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