Kalman Filter Based Microgrid State Estimation Using the Internet of Things Communication Network

Abstract

Recently, the smart grid is expected to modernize the current electricity grid by commencing a new set of technologies and services that make the electricity networks secure, automated controlled, cooperative and sustainable. Consequently, the smart control centre feels the requirement of a robust and scalable technique for state estimation (SE) that allows continuous and accurate wide-area real-time monitoring of power system operation and customer utilization of smart grid. This paper proposes a Kalman filter (KF) based micro grid SE using the internet of things (IoT) communication network under two different sensing scenarios. Particularly, the observation from the multiple distributed energy resources (DERs) information is obtained by a set of sensors, which is transmitted to a control center via the IoT communication network. In this control center, the information is fed to a state estimator program for estimating the states of the multiple DERs. Finally, the simulation results show that the proposed KF based micro grid SE is able to estimate the system states properly in all scenarios. Results indicate that it is better to use the same number of sensors as that of states for properly estimating the DERs states using the IoT communication network.