Design and accuracy analysis of multi-level state estimation based on smart metering infrastructure

While the first aim of smart meters is to provide energy readings for billing purposes, the availability of these measurements could open new opportunities for the management of future distribution grids. This paper presents a multi-level state estimator that exploits smart meter measurements for monitoring both low and medium voltage grids. The goal of the paper is to present an architecture able to efficiently integrate smart meter measurements and to show the accuracy performance achievable if the use of real-time smart meter measurements for state estimation purposes were enabled. The design of the state estimator applies the uncertainty propagation theory for the integration of the data at the different hierarchical levels. The coordination of the estimation levels is realized through a cloud-based infrastructure, which also provides the interface to auxiliary functions and the access to the estimation results for other distribution grid management applications. A mathematical analysis is performed to characterize the estimation algorithm in terms of accuracy and to show the performance achievable at the different levels of the distribution grid when using the smart meter data. Simulations are presented, which validate the analytical results and demonstrate the operation of the multi-level estimator in coordination with the cloud-based platform.