On a nonlinear multiple-centrality-corrections interior-point method for optimal power flow

Author

Torres, Geraldo L. ; Quintana, Victor H.

Author_Institution

Dept. de Engenharia Eletrica e Sistems de Potencia, Univ. Federal de Pernambuco, Recife, Brazil

Volume

16

Issue

2

fYear

2001

fDate

5/1/2001 12:00:00 AM

Firstpage

222

Lastpage

228

Abstract

Large scale nonlinear optimal power flow (OPF) problems have been efficiently solved by extensions from linear programming to nonlinear programming of the primal-dual logarithmic barrier interior-point method and its predictor-corrector variant. Motivated by the impressive performance of the nonlinear predictor-corrector extension, in this paper we extend from linear programming to nonlinear OPF the efficient multiple centrality corrections (MCC) technique that was developed by Gondzio. The numerical performance of the proposed MCC algorithm is evaluated on a set of power networks ranging in size from 118 buses to 2098 buses. Extensive computational results demonstrate that the MCC technique is fast and robust, and outperforms the successful predictor-corrector technique

Keywords

load flow; nonlinear programming; predictor-corrector methods; 118 bus system; 2098 bus system; linear programming; nonlinear multiple-centrality-corrections interior-point method; nonlinear optimal power flow; nonlinear predictor-corrector extension; nonlinear programming; power networks; primal-dual logarithmic barrier interior-point method; Constraint optimization; Control systems; Helium; Linear programming; Load flow; Nonlinear control systems; Optimal control; Power system control; Power systems; Robustness;

fLanguage

English

Journal_Title

Power Systems, IEEE Transactions on

Publisher

ieee

ISSN

0885-8950

Type

jour

DOI

10.1109/59.918290

Filename

918290