Dual Set-Membership State Estimation for Power Distribution Networks Under Event-Triggered Mechanism - Bai, Xingzhen; Li, Guhui; Ding, Mingyu; Ji, Xingquan; Li, Jing; Zheng, Xinlei (Frontiers in Energy Research, 2022)
This paper is concerned with the set-membership state estimation problem for power distribution networks (PDNs) over a resource-constrained communication network under the influence of unknown-but-bounded (UBB) noises. Firstly, in order to alleviate the pressure of information communication network (ICN) while meeting the state estimation requirements, the event-triggered mechanism is adopted to send data containing more valid information to estimation center, reasonably reducing the signal transmission frequency. Secondly, an event-based dual set-membership filter (ET-DSMF) is designed to improve the performance of state estimation. The proposed filter performs a discrete approximation for a semi-infinite programming problem by random sampling technique, and a compact linearization error bounding ellipsoid is obtained by solving the dual problem of the nonlinear programming. Subsequently, a sufficient condition for the existence of estimated ellipsoid is derived depending on mathematical induction method. The key time-varying filter gain parameter and optimal estimated ellipsoid are determined recursively by solving a convex optimization problem, according to the minimum trace criterion. Finally, the effectiveness of the proposed filtering algorithm is demonstrated by performing simulation experiments on the IEEE 13 distribution test system.