Centralized controller design for voltage estimation error constrained in islanded DC-microgrids: Kalman Filtering Method

Abstract

The traditional model predictive control (MPC) design strategy heavily depends on the discritization of the non-linear model of DC/DC power converters to approximate the direct current (DC) microgrid system model. The system model does not includes the whole information of the physical implementation of the system. Assumptions have been made to add the model and sensor uncertainties in the system model to form a model with fully physical information that enables its solution through the linear kalman filtering method ( LKFM ). Due to the unbounded of the DC bus voltage estimation error, the instability of the LKFM during transient response increases exponentially. To standardize the MPC model and ensure bounded the DC bus voltage estimation error, a centralized controller design for DC bus voltage estimation error constrained is proposed in this paper. The proposed system model is constructed from DC/DC power converters and then translated into a deterministic model. Through measurements and time updates, the LKFM has been employed to estimate the DC bus voltage. The linear quadratic regulator is used for stabilizing the DC bus voltage estimation and current sharing error between DC/DC power converters. During a transient response, an integral action is utilized to close the loop and eliminate an error in DC bus voltage. A feedback control rule of the DC bus voltage estimation and a Riccati equation have been used to develop the proposed controller. Finally, the proposed approach was validated using Simulink, the Hardware-in-the-loop laboratory, and compared with conventional control approaches. Moreover, the LKFM's stability was examined using exponential stability criteria.