Enhanced self‐adaptive differential evolution multi‐Objective algorithm for coordination of directional overcurrent relays contemplating maximum and minimum fault points

Abstract

In this study, a parameter tune free enhanced self-adaptive differential evolution multi-objective (ESA-DEMO) approach has been proposed for coordination of directional overcurrent relays. The advantages of the proposed method are: avoid the use of conventional single-objective function, which requires tuning of weighting parameters; avoid tuning of algorithm parameters; minimisation of primary, backup and coordination time interval; zero violation of coordination constraints in large interconnected network; and low computational resource consumption leading to fast algorithm execution time. The proposed method has been implemented on the highly interconnected 6-bus, IEEE 14- and 30-bus systems, where results have shown robustness and consistency of the algorithm. Moreover, two-fault point coordination criterion considering close- and far-end (maximum and minimum) faults has been performed. ESA-DEMO has been compared with popular genetic algorithms and state-of-the-art multi-objective algorithm for protection coordination study.