A modified Primal-Dual Logarithmic-Barrier Method for solving the Optimal Power Flow problem with discrete and continuous control variables


Autoria(s): Soler, Edilaine Martins; de Sousa, Vanusa Alves; da Costa, Geraldo R. M.
Contribuinte(s)

Universidade Estadual Paulista (UNESP)

Data(s)

20/05/2014

20/05/2014

01/11/2012

Resumo

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

The aim of solving the Optimal Power Flow problem is to determine the optimal state of an electric power transmission system, that is, the voltage magnitude and phase angles and the tap ratios of the transformers that optimize the performance of a given system, while satisfying its physical and operating constraints. The Optimal Power Flow problem is modeled as a large-scale mixed-discrete nonlinear programming problem. This paper proposes a method for handling the discrete variables of the Optimal Power Flow problem. A penalty function is presented. Due to the inclusion of the penalty function into the objective function, a sequence of nonlinear programming problems with only continuous variables is obtained and the solutions of these problems converge to a solution of the mixed problem. The obtained nonlinear programming problems are solved by a Primal-Dual Logarithmic-Barrier Method. Numerical tests using the IEEE 14, 30, 118 and 300-Bus test systems indicate that the method is efficient. (C) 2012 Elsevier B.V. All rights reserved.

Formato

616-622

Identificador

http://dx.doi.org/10.1016/j.ejor.2012.05.021

European Journal of Operational Research. Amsterdam: Elsevier B.V., v. 222, n. 3, p. 616-622, 2012.

0377-2217

http://hdl.handle.net/11449/8589

10.1016/j.ejor.2012.05.021

WOS:000307144700022

Idioma(s)

eng

Publicador

Elsevier B.V.

Relação

European Journal of Operational Research

Direitos

closedAccess

Palavras-Chave #OR in energy #Optimal Power Flow #Interior point methods #Discrete variables #Nonlinear programming
Tipo

info:eu-repo/semantics/article