Optimal power flow algorithm based on nonlinear multiple centrality corrections interior point method

A novel nonlinear multiple centrality corrections interior point algorithm is presented to solve optimal power flow problems of power systems in this paper. The original affine-scaling direction is used as the predictor direction and a weighting coefficient is added into the corrector direction. To obtain the largest step-length in the combination of the predictor direction and the corrector direction, the optimal value of the coefficient is chosen by line search method. The convergence of the algorithm is guaranteed by checking whether the corrected directions are in the symmetric neighborhood of the centering direction. Since the proposed algorithm can obtain a larger computing stepsize by only single corrector, the computing time is saved. Comparing with the predictor-corrector interior point method, this algorithm is faster and robuster especially under the bad circumstance of large difference complementarity pairs during the solving process. The proposed method was tested on five systems and the numeric results demonstrated its validity.