Efficient evolutionary particle swarm optimization approach for nonconvex economic load dispatch problem

The main objective of economic load dispatch (ELD) is to allocate the output power generator at minimum cost while satisfying all the operation constraints. This paper presents a new hybrid method by integrating particle swarm optimization with time varying acceleration coefficients and evolutionary programming (TVAC-EPSO) for solving nonconvex ELD problem. The competition, sorting and selection in EP method are used to determine the best particle in PSO for finding the optimum solution efficiently. The proposed TVAC-EPSO has been tested on three different power system benchmarks. The simulation results have demonstrated the effectiveness of the proposed method in solving nonconvex ELD problem. Streszczenie. W artykule przedstawiono hybrydową metode ekonomicznie uzasadnionego określenia zalozen dotyczących generowanej energii elektrycznej (ang. Economic Load Dispatch - ELD). Algorytm oparty jest na wykorzystaniu metody optymalizacji roju cząstek ze wspolczynnikami zmiennymi w czasie i programowaniu ewolucyjnym. (ang. TVAC-EPSO). Proponowana metoda zostala poddana weryfikacji na trzech roznych systemach energetycznych. Wyniki symulacyjne potwierdzają jej efektywnośc w analizie problemu ELD. (Zagadnienie ekonomicznie uzasadnionego określenia wytwarzanej energii elektrycznej o charakterystyce niewypuklej - wykorzystanie metody optymalizacji roju cząstek).

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