ANN Based Adaptive Mho Distance Protection in Distribution Network with Distributed Generations

Abstract

Distributed generation (DG) when added to distribution network has resulted in bidirectional power flow. Directional Over current relay used for detection of fault in Distribution network (DN) has limited performance due to changes in direction and magnitude of power flow due to the inclusion of DG. Hence, with increased penetration of DG, distance relays (DR) are applied for protection of the DN. However, the distance relay also suffers due to the combined effect of DG infeed and fault resistance. Under reaching effect of distance relay may cause a delayed operation if fault in zone 2 is cleared by the zone 3 and this will hamper the stability. In order to prevent under reaching of distance relays, an adaptive distance relaying protection for the distribution network considering the impact of fault resistance and intermediate sources infeed effect is proposed in this work. This paper discusses the Artificial Neural Network (ANN) as a suitable candidate for classification of various zones in adaptive distance protection in distribution network with distributed generations. The system has been simulated on DIgSILENT Power Factory environment and ANN based classification technique helps in detecting fault which may occur in different zones based on MATLAB toolbox. © 2020 IEEE.