Adaptive neural network based intelligent secondary control for microgrids

This paper proposes a neural network based intelligent secondary controller for microgrids to tackle system dynamics uncertainties, faults and/or disturbances. The proposed adaptive neural network controller is based on a class of feedforward artificial neural network, named multilayer perceptron (MLP). The learning capability of the proposed intelligent controller makes it a promising approach to take system uncertainties, faults and/or disturbances into account. The satisfactory performance of the proposed intelligent secondary controller is validated based on the simulation results of a microgrid with system uncertainties and disturbances, such as transition to the islanded mode.