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

Large scale nonlinear optimal power flow (OPF) problems have been efficient ly solved lately by extensions from linear programming to nonlinear program ming of the primal-dual logarithmic barrier interior-point method and its p redictor-corrector variant. Motivated by the impressive performance of the nonlinear predictor-corrector extension, in this paper we extend from linea r programming to nonlinear OFF the efficient multiple centrality correction s (MCC) technique that was developed by Gondzio, The numerical performance of the proposed MCC algorithm is evaluated on a set of power networks rangi ng in size from 118 buses to 2098 buses. Extensive computational results de monstrate that the MCC technique is fast and robust, and outperforms the su ccessful predictor-corrector technique.