Digital overcurrent relays coordination in renewable microgrids utilizing several operating characteristics using educational competition optimizer

Abstract

Renewable microgrids (MGs), characterized by bi-directional power flow, require enhanced attention in designing protection schemes, particularly in the coordination of overcurrent relays (OCRs). Accordingly, a fresh metaheuristic algorithm named educational competition optimizer (ECO) is proposed in this study to solve the OCRs coordination problem with various operation scenarios among digital relays. Additionally, two fitness functions are incorporated into the optimization mechanism considering several relay operating characteristics (CCs) along with continuous current pickup and time dial. In this context, the programmed simulation model is validated rigorously against two other metaheuristic optimizers: artificial bee colony (ABC) and dung beetle optimizer (DBO). Initially, the effectiveness of the ECO is assessed on the IEEE 15-bus benchmark network prior to validating the proposed methodology in the IEC benchmark MG. Considering all operational scenarios, ECO attempts the best shot in minimizing the total operating time (TOT) of OCRs in both investigated networks. For instance, the ECO attains TOT of 3.2704 s and 6.3968 s with various operating CCs for 15-bus and IEC MG respectively. Undoubtedly, ECO earns this rival for all scenarios compared to ABC and DBO besides additional 16 metaheuristic literature algorithms. It is worth highlighting that when optimizing the OCR’s curve among 17 CCs, TOT is enhanced by 64.9 % and 43 % compared to fixed standard curve for 15-bus and MG respectively. Eventually, ECO consistently proves its superiority over other published optimizers in addressing the complex problem of OCR’s coordination especially in renewable MGs. • Proposed ECO optimizes overcurrent relay coordination in renewable microgrids. • Improved relay coordination using various tripping characteristics and time dial. • Validation on 15-bus and IEC benchmark microgrids with superior results. • ECO outperforms 16 metaheuristic algorithms, minimizing relay operating time. • ECO reduces total operating time by 64.9 % compared to fixed standard curves.