Kalman filter based microgrid state estimation and control using the IoT with 5G networks

Abstract

Given the significant concerns regarding carbon emissions from fossil fuels, global warming and energy crisis, the renewable distributed energy resources (DERs) are going to be integrated in smart grids, which will make the energy supply more reliable and decrease the cost and transmission losses. Unfortunately, one of the key technical challenges in power system planning, control and operation with DERs is the voltage regulation at the distribution level. This problem stimulates the deployment of smart sensors and actuators in smart grids so that the voltage regulation can be controlled at an accepted level. The observation from the multiple DERs information is transmitted to a control center via the internet of things (IoT) based fifth generation (5G) communication network. In other words, the proposed communication infrastructure provides an opportunity to address the voltage regulation challenge by offering the two-way communication links for microgrid state information collection, estimation and control. Based on this innovative communication infrastructure, we propose a least square based Kalman filter for state estimation and a feedback control method for voltage regulation of this intermittent and weather-dependent renewable power generation. Specifically, we propose to optimize the performance index by using semidefinite programming techniques in the context of smart grid applications. At the end, the efficacy of the developed approaches is demonstrated using the linear physical model of a microgrid incorporating DERs.