Title: "Optimal Overcurrent Relay Coordination Using Hybrid Genetic Algorithm and Linear Programming Method"

DOI: 10.15224/978-1-63248-113-9-48
Page(s): 60 - 63


Power systems are exposed to various faults, such as phase-phase, phase-ground, 3-phase-ground during their operations. Due to fault type and location, some part of the system cannot be supplied when a fault occurs. Moreover, this issue not only reduces power quality parameters but also increases total energy cost of the system. Overcurrent relays are widely used tools for detecting and clearing fault in power systems. In addition to this, relays must be operated in a harmony whilst fault occurs. The coordination among relays can be quarantined by arranging their characteristics through adjusting their parameters. In conventional approach, operation characteristics of relays depend on two variables namely, pick up current (Ip) and time multiplier settings (TMS). In recent decades, several studies about optimization of relay coordination problem have been done. Since relay coordination problem is a non-convex optimization problem, most of studies has been used heuristic optimization techniques such as Particle Swarm Optimization (PSO), Genetic Algorithm (GA), Ant Colony Optimization (ACO). In this paper, relay coordination problem is solved by a hybrid Genetic Algorithm and Linear Programming (GALP) method. Both GA search space and computational effort is reduced using GALP. Hybrid method is tested on IEEE 14-Bus Test System. GALP and GA is programmed in MATLAB while DigSILENT Power Factory program is used to obtain values of power system parameters. Results show that GALP can converge to optimal solution faster than GA and increase in Distributed Generation (DG) capacity causes a rise in the total relay operating time.