Voltage Recovery and Current Sharing of DC Microgrids With Uncertain Constant Power Loads Using Neural Networks

In this paper, we investigate distributed secondary control for DC microgrids with uncertain constant power load (CPL). First, a model of DC microgrids is established, where a controllable current source is introduced to be an control input and uncertain CPLs are regarded as unknown nonlinear dynamics. Based on the established model, an adaptive neural network (NN) controller is designed to achieve both voltage recovery and current sharing. The approximation property of radial basis function neural networks (RBFNNs) is used to neutralize the uncertain nonlinear dynamics in DC microgrids. It is proved that our proposed controller can guarantee the stability of DC microgrids. Simulations are performed to demonstrate the effectiveness and validity of the proposed method.