Designing a modified Hopfield network to solve an Economic Dispatch problem with nonlinear cost function


Autoria(s): da Silva, I. N.; Nepomuceno, L.; Bastos, T. M.; IEEE
Contribuinte(s)

Universidade Estadual Paulista (UNESP)

Data(s)

20/05/2014

20/05/2014

01/01/2002

Resumo

Economic 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.

Formato

1160-1165

Identificador

http://dx.doi.org/10.1109/IJCNN.2002.1007658

Proceeding of the 2002 International Joint Conference on Neural Networks, Vols 1-3. New York: IEEE, p. 1160-1165, 2002.

1098-7576

http://hdl.handle.net/11449/33348

10.1109/IJCNN.2002.1007658

WOS:000177402800207

Idioma(s)

eng

Publicador

Institute of Electrical and Electronics Engineers (IEEE)

Relação

Proceeding of the 2002 International Joint Conference on Neural Networks, Vols 1-3

Direitos

closedAccess

Tipo

info:eu-repo/semantics/conferencePaper