Optimization of Directional Overcurrent Relay Coordination using Metaheuristic Coronavirus Technique

Abstract This paper employs the Coronavirus Herd Immunity Optimizer (CHIO), a recently proposed optimizer that incorporates multi-population evolution in the search mechanism, to study the problem of directional overcurrent relays (DOCR). Minimizing the overall tripping time for all primary relays along with meeting the selectivity criteria between relay pairs and complying with any operating limits is the principal objective of optimal coordination of DOCRs. The efficacy and feasibility of the CHIO approach in solving the DOCRs problem is investigated using 8-bus IEEE network and the accuracy of the results is validated using ETAP Program. The ability of CHIO to determine the optimal relay settings and cut down the overall tripping time of relays shown in the minimization of the total tripping time where the reduction percentage reaches more than
$30{\rm{\% }}$
with respect to PSO and GSA algorithms.