Title :
Particle swarm optimization with Exponentially Varying Inertia Weight Factor for solving Multi-Area Economic Dispatch problem
Author :
Rani, C. ; Petkov, E. ; Busawon, K. ; Farrag, M.
Author_Institution :
Northumbria Univ., Newcastle upon Tyne, UK
Abstract :
This paper aimed at exploring the performance of Particle Swarm Optimisation with Exponentially Varying Inertia Weight Factor (PSO-EVIWF) for solving Multi-Area Economic Dispatch (MAED) problem with tie line constraints considering valve-point loading in each area. The effectiveness of the proposed algorithm has been verified on 4 interconnected areas with 16 generators standard test system. The paper presents the search capability and convergence behavior of the proposed method. Simulation results show that the PSO-EVIWF achieved quality solutions and smooth convergence characteristics and it is an alternative method for solving MAED problem.
Keywords :
particle swarm optimisation; power generation dispatch; power generation economics; MAED problem; PSO-EVIWF; convergence behavior; exponentially varying inertia weight factor; generators standard test system; multiarea economic dispatch problem; particle swarm optimisation; search capability; tie line constraints; valve-point loading; Convergence; Economics; Generators; Optimization; Particle swarm optimization; Sociology; Statistics; Economic dispatch; Multi area economic dispatch; exponentially varying inertia weight factor; particle swarm optimisation;
Conference_Titel :
Environmental Friendly Energies and Applications (EFEA), 2014 3rd International Symposium on
DOI :
10.1109/EFEA.2014.7059938
