Digital Twin for Advanced Automation of Future Smart Grid

Abstract

This paper presents a framework for the implementation of a digital twin (DT) in electrical grid management. Automation in the electrical energy network has resulted in the transformation into Smart grid, which is utilized for the generation, transmission, and distribution of electrical power as well as interconnecting microgrids with dynamic scheduling and trading options. The evolution of the digital twin offers added advantages including real-time condition monitoring based maintenance of assets based on data analytics, energy forecasting, and prediction for appropriate decision making by investors. Thus, fault diagnosis and detection can be easily handled in the advanced automated future grid. These features have enhanced reliability and offer optimized energy management by incorporating a virtual DT domain. In this paper, some major benefits of establishing a digital twin for the smart-grid is highlighted followed by the case study on monitoring a single component of the Smart grid that is evaluated for the remaining useful life (RUL) of the equipment by using artificial intelligence (AI) algorithm. This approach of preventive maintenance based on DT can be effectively utilized for all the key components in the smart grid-connected via a sensor network for data sampling to reduce downtime and improve the reliability of the overall system.