Applying Hybrid Interval Linear Programming and Genetic Algorithm to Coordinate Distance and Directional Over-current Relays

Abstract Interval linear programming (ILP) is a powerful tool for modeling problems with uncertain and bounded parameters. In real power systems, planned/unplanned events lead to changes in network topology. The changes cause altered distribution and magnitude of fault currents. Since protective relays are usually coordinated based on the fault currents of the main topology, mal-operation of the relays in such situations is likely. By covering the uncertainties, this paper aims to achieve the robust coordination of distance and directional overcurrent relays (D&DOCRs), as the main protections of transmission/subtransmission systems. Generally, relay coordination is a complicated nonlinear optimization problem. The complexity increases drastically by increasing coordination constraints, due to considering uncertainties. In this study, the problem is modeled as an ILP problem. The salient advantage of using ILP is that the number of constraints remains the same as in the main network topology, which greatly improves solving performance. Finally, to overcome the nonlinearity of the problem, a hybrid genetic algorithm and ILP (HGA/ILP), as a new optimization algorithm, is proposed. The proposed approach is applied to the IEEE 14-bus test system, and the results show that ILP is a useful tool to obtain robust settings of D&DOCRs in a power system.