Nonlinear optimal control for DC industrial microgrids

Abstract

ABSTRACTDC industrial microgrids can assure uninterrupted and free-of-perturbations power supply to industrial units. Besides the solution of the related optimal control problem can result in minimisation of electric power consumption by such units. In this article, the problem of nonlinear optimal (H-infinity) control for industrial microgrids is treated. The dynamic model of an indicative microgrid that comprises photovoltaic units, batteries and supercapacitors is considered. This model undergoes approximate linearisation around a temporary operating point that is recomputed at each time-step of the control method. The linearisation relies on Taylor series expansion and on the computation of the associated Jacobian matrices. For the linearised state-space model of the system, a stabilising optimal (H-infinity) feedback controller is designed. This controller stands for the solution to the nonlinear optimal control problem under model uncertainty and external perturbations. To compute the controller’s feedback gains an algebraic Riccati equation is repetitively solved at each iteration of the control algorithm. The stability properties of the control method are proven through Lyapunov analysis. Finally, to implement state estimation-based control without the need to measure the entire state vector of the DC microgrid the H-infinity Kalman Filter is used as a robust state estimator.