A Hybrid Optimization Algorithm (IA-PSO) for Optimal Coordination of Directional Overcurrent Relays in Meshed Power Systems

This paper presents a hybrid optimization approach for the optimal coordination of Inverse Definite Minimum Time (IDMT) directional overcurrent relays in meshed power systems, namely Immune Algorithm and Particle Swarm Optimization (IA-PSO) algorithm. The algorithm is employed by coupling the immune information processing mechanism with the particle swarm optimization algorithm in order to achieve a better global solution with less computational effort. In protection coordination problem, the objective function to be minimized is the sum of the operating time of all main relays. The optimization problem is subject to a number of constraints which are mainly focused on the operation of the backup relay, which should operate if a primary relay fails to respond to the fault near to it, Time Dial Setting (TDS), Plug Setting (PS) and the minimum operating time of a relay. The proposed optimization algorithm aims to minimize the total operating time of each protection relay. Two systems are used as case study to check the efficiency of the optimization algorithm which are IEEE 4-bus and IEEE 6-bus models. Results are obtained and presented for IA and PS and IA-PSO algorithms. The obtained results for the studied cases are compared with those results obtained when using other optimization algorithms which are Teaching Learning-Based Optimization (TLBO), Chaotic Differential Evolution Algorithm (CDEA) and Modified Differential Evolution Algorithm (MDEA). From analysing the obtained results, it has been concluded that IA-PSO algorithm provides the most optimum solution with the best convergence rate. Key-Words: Meshed Power Systems, Directional Overcurrent Protection Relays, Optimal Coordination, Immune Algorithm, Particle Swarm Optimization, Hybrid Optimization Algorithms.