da Silva, I. N.Nepomuceno, L.Bastos, T. M.2014-05-202014-05-202002-01-01Proceeding of the 2002 International Joint Conference on Neural Networks, Vols 1-3. New York: IEEE, p. 1160-1165, 2002.1098-7576http://hdl.handle.net/11449/33348Economic Dispatch (ED) problems have recently been solved by artificial neural networks approaches. In most of these dispatch models, the cost function must be linear or quadratic. Therefore, functions that have several minimum points represent a problem to the simulation since these approaches have not accepted nonlinear cost function. Another drawback pointed out in the literature is that some of these neural approaches fail to converge efficiently towards feasible equilibrium points. This paper discusses the application of a modified Hopfield architecture for solving ED problems defined by nonlinear cost function. The internal parameters of the neural network adopted here are computed using the valid-subspace technique, which guarantees convergence to equilibrium points that represent a solution for the ED problem. Simulation results and a comparative analysis involving a 3-bus test system are presented to illustrate efficiency of the proposed approach.1160-1165engTrabalho apresentado em evento10.1109/IJCNN.2002.1007658WOS:000177402800207Acesso aberto2013445187247691