Distributed state estimation for renewable energy microgrids with sensor saturations

Abstract

In this paper, the distributed state estimation problem is studied for renewable energy microgrids with sensor saturations. A system model for the microgrids with sensor saturations is proposed. Attention is focused on the design of a distributed recursive estimation scheme such that, in the presence of the sensor saturations, an upper bound of the estimation error covariance is guaranteed. Subsequently, such an upper bound is minimized by appropriately designing the gain matrices of the corresponding state estimator. In particular, the sparsity of the gain matrices resulting from network topology is handled by using a matrix simplification method. Moreover, the performance evaluation of the designed distributed state estimator is conducted by analyzing the exponential boundedness of the estimation error in the mean square sense. Finally, simulation experiments under two cases are carried out on a renewable energy microgrid which contains two distributed generation units. The simulation results demonstrate that the developed state estimation scheme is effective.