Performance Analysis of Different Optimization Algorithms on Overcurrent Relay Coordination Problem in Distribution Systems

Optimal coordination of overcurrent relays is essential to ensure reliable and selective fault isolation in distribution systems. This paper evaluates the performance of various optimization algorithms in solving the overcurrent relay coordination problem. Algorithms such as Genetic Algorithm (GA), Particle Swarm Optimization (PSO), Ant Colony Optimization (ACO), Artificial Bee Colony (ABC), and Differential Evolution (DE) are compared based on their ability to minimize relay operating times while adhering to coordination constraints. The analysis is conducted on a standard distribution system model, considering fault scenarios with and without Distributed Generation (DG). The study provides insights into the suitability of each algorithm for practical implementation in dynamic power systems.