Using a neural network to predict the dynamic frequency response of a power system to an under-frequency load shedding scenario

This paper proposes a method to quickly and accurately predict the dynamic response of a power system during an under-frequency load shedding scenario. Emergency actions in a power system due to loss of generation typically calls for under-frequency load shedding measures to avoid potential collapse due to the lack of time in which to correct the imbalance via other means. Due to the slow and repetitious use of dynamic simulators the need for a fast and accurate procedure is evident when calculating optimal load-shedding strategies. A neural network (NN) seems to be an ideal solution for a quick and accurate way to replace standard dynamic simulations The steps taken to produce a viable NN and corresponding results are discussed.