Deep Reinforcement Learning-BasedRobust Protection in DER-Rich Distribution Grids [article]

Dongqi Wu, Dileep Kalathil, Miroslav Begovic, Le Xie
2021 arXiv   pre-print
This paper introduces the concept of Deep Reinforcement Learning based architecture for protective relay design in power distribution systems with many distributed energy resources (DERs). The performance of widely-used overcurrent protection scheme is hindered by the presence of distributed generation, power electronic interfaced devices and fault impedance. In this paper, a reinforcement learning-based approach is proposed to design and implement protective relays in the distribution grid.
more » ... particular algorithm used is an Long Short-Term Memory (LSTM) enhanced deep neural network that is highly accurate, communication-free and easy to implement. The proposed relay design is tested in OpenDSS simulation on the IEEE 34-node test feeder and demonstrated much more superior performance over traditional overcurrent protection from the aspect of failure rate, robustness and response speed.
arXiv:2003.02422v3 fatcat:5koxf42bhba4blz27jz2imyjhe