Analysis of Digital Twin Implementation Technologies for Power Distribution Systems

Digital twin technology has emerged as a cutting-edge solution, providing virtual representations of physical systems that enable real-time monitoring, analysis, and control of distribution systems affected by uncertainty. However, issues such as data errors and limited real-time measurements pose observability problems, affecting the accuracy and performance of digital twin models in distribution systems. This paper offers a comprehensive analysis of the current research landscape and outlines the key technical requirements for implementing digital twins in distribution systems. The focus is on both data and model aspects, including data imputation and augmentation, topology and line parameter identification, intelligent state estimation methods, and digital twin model construction methods. Future research is encouraged to deepen the understanding of these requirements and develop high-performance digital twins capable of addressing various application scenarios in power distribution systems.