Distributed event-triggered state estimation for renewable microgrids subject to incomplete observations

Abstract

In this paper, we investigate the distributed state estimation problem for renewable microgrids (RMGs) with incomplete observations, where information transmission is governed by the event-triggered communication criterion. The missing measurements with the description of uncertain occurrence probabilities (UOPs) are considered and modeled via the integration of nominal probabilities and the associated bounds. In addition, an event-triggered mechanism involving some parameters is employed to improve reliability of communication by transmitting measurements under specific triggered conditions. The aim of this paper is to design a distributed event-triggered state estimation algorithm against missing measurements under UOPs that guarantees the existence of an upper bound on the estimation error covariance (EEC) with satisfactory algorithm performance. Afterwards, the gain matrix of the corresponding state estimator is properly designed by minimizing the trace of the upper bound on the EEC. Besides, the boundedness of the upper bound of EEC is further ensured by providing a sufficient condition. Subsequently, we discuss the monotonicity relationship with respect to the trace of upper bound and the nominal occurrence probability of missing measurements. Finally, a simulation experiment with comparisons is conducted on RMGs with two distributed generation units to demonstrate the effectiveness of newly designed state estimation algorithm.