A comparative Studies on different islanding detection methods for distributed generation systems

Abstract

ABSTRACT Renewable-based distributed generation (DG) has a vital contribution to the evolution of the microgrid model. It is usually operated in both grid-connected mode and island mode. Detection of the islanding event (IE) is required to avail benefits like safety and protection of the connecting devices and personnel or crewmen. The improper islanding detection may lead to power quality degradation (PQD), out-of-phase reclosing, and grid protection interference. The IE can be properly detected by using an islanding detection scheme (IDS). IDS regularly monitors the EPS state, and if there is a problem with the grid’s healthiness, the TS is delivered. Usually, when load demand is the same as DG generation, or load demand is more than DG generation capacity, it is an IE. To mitigate these issues concerning islanding detection, numerous researchers have suggested various strategies that are widely categorized as Passive, Active, Hybrid, Communication-based, Signal Processing-based, and Intelligent-technique-based. Here, a review of several proposed methods is discussed with their performance indices like control variables, merits, demerits, non-detection zone (NDZ), Power quality issues, speed of detection, and computational burden. Conventional passive IDS lies within 80% accuracy that is very poor, Active IDS and hybrid IDS are intermediate range, and communication-based IDS (CIDS) is known to be a good one, but signal processing-based IDS and intelligent-based IDS have the highest accuracy in the range of 95% to 100%. Researchers and scientists can use this review to assist them in choosing the best approach for future applications.