Deterministic Branch and Cut Algorithm for Multiobjective Optimization of Protective Device Allocation in Radial Distribution Systems

Abstract

Installing protective devices enhances reliability of power distribution systems by means of failure separation. Finding optimal positions of protective devices to minimize a given objective function can be achieved using various single-objective optimization methods. Solutions obtained for different objective functions may differ significantly. Multiobjective optimization algorithms may be used to solve the optimization problem taking into account more than one objective function. In this work, a new branch and cut algorithm is proposed to solve the multiobjective optimization problem of protective device allocation in radial distribution systems with a single feeder. It is shown that the proposed algorithm can successfully handle very large power distribution systems. The performance of the algorithm is compared with the performance of three other approaches: 1) the exhaustive search; 2) an evolutionary algorithm; and 3) a reinforcement learning algorithm. It is shown that the proposed algorithm outperforms other methods both in terms of the computation time and the quality of the results.