Fuzzy second correction on complementarity condition for optimal power flows

In this paper, an efficient fuzzy second correction scheme (FSCS) to improve the complementarity condition in a predictor-corrector interior point algorithm (PCIPA) for optimal power flows (OPF) is proposed. At every iteration, the proposed FSCS estimates, with the help of fuzzy logic, a better barrier parameter for each complementarity pair and effectively computes a second corrector term to improve the convergence of the PCIPA. The effectiveness of FSCS is demonstrated by several large-stale test cases. From the numerical results, it is found that the proposed FSCS improves PCIPA by 20% in terms of CPU times.