Using GA to improve coordination of overcurrent relays for distribution network with high DG penetration

Abstract

In recent years, with the increasing penetration of distributed generators (DGs) with large-share capabilities, the efficient coordination of primary and backup overcurrent relay (OCR) schemes has emerged as one of the most challenging tasks in contemporary MV-distribution networks (DN). The main goal is to design a protection scheme to protect the power system where different intermittent sources significantly impact. The performance of the existing protection scheme needs to be analysed to develop a robust power system. In this project, an IEEE 33 bus system is considered for short circuit analysis and protection coordination, relying upon coordination for designing of overcurrent protection scheme to operate the relay efficiently and disconnect the fault section from the healthy network instantly. It also compares the differences between conventional systems and DG-connected radial systems. Moreover, the project examined the coordination scheme based on the Optimization Algorithm. The optimum coordination increases the sensitivity and reliability of the protection system by reducing the operating time of OCRs by using a standard tripping characteristic. Improved optimisation strategies have benefited from a new constraint that considers the maximum Plug Setting Multiplier (PSM) and improves the complementing OCR tripping properties by using optimisation approaches to improve coordination time intervals. The Time Multiplying Setting (TMS) for OCR coordination is optimised using the Genetic Algorithm (GA) in MATLAB coding tools. The ETAP has used the network to test the effectiveness of the proposed new constraint to improve the constrained optimisation technique in grid-connected modes.