Digital twin technologies in active distribution network: A comprehensive review

Recently, there has been a notable shift from synchronous generators to demand-side distributed energy resources aimed at reducing carbon emissions. This shift necessitates transforming the operational framework of the existing distribution system into an active distribution network. An active distribution network, which operates with a variety of distributed energy resources s, is expected to greatly enhance the performance of the power system. Simultaneously, advancements in computational capabilities and the expansion of available data have accelerated AI developments, including machine learning, and data utilization technologies like internet of things and big data. Additionally, the deployment of digital twins is growing, as they enable modeling of real-world system behaviors through diverse algorithms. In this paper, an operational structure that integrates active distribution network and digital twin is proposed, with an analysis of the necessary technologies for its implementation. The required methods encompass modeling of resources, fault diagnosis and verification, forecasting of renewable energy generation and load, and distribution system operations. Furthermore, this paper discusses the limitations and future requirements for the digital twin framework implementation. Ultimately, the paper illustrates the impact of the combined operation of digital twin and active distribution network.