Multi-objective optimal load flow problem with interior-point trust-region strategy

Abstract

In this paper, an interior-point trust-region algorithm to generate a Pareto optimal solution for a multi-objective optimal load flow (MOLF) problem is introduced. A weighted Tchebychev approach is used in this paper to transform (MOLF) problem to a single objective optimization problem.In the algorithm, an interior-point Newton method is used with Coleman-Li scaling matrix and a trust-region globalization strategy to insure global convergence. The trust region technique is suitable for multi-objective optimal load flow problem such that its objective functions may be ill-defined or having a non-convex Pareto-optimal front. A projected Hessian technique is used in the algorithm to handling the difficulty of having an infeasible trust region subproblems.The proposed algorithm is carried out on the standard IEEE 30-bus 6-generator test systems to assert the efficacy of the algorithm used to solve the multi-objective (MOLF) problem. Our results have been compared to those reported in the literature. The comparison demonstrates the superiority of the proposed approach and confirm its potential to generate the Pareto optimal solution for (MOLF) problem.