Situation awareness of distribution network based on digital twin technique

With the penetration of distributed generation and electric vehicles, the randomness and uncertainty significantly impact the distribution network operations. Distribution network situation awareness is an important fundamental for the safety, reliability, and efficiency of the distribution network operation. At present, accurate perception of the distribution network situation is a challenge due to inaccurate modelling, lacking real-time measurement, and insufficient computing power. This paper investigates the key technologies of distribution network situation awareness. A digital twin model of an actual distribution network was constructed and super-resolution technology was employed to improve the resolution of measurement data. To demonstrate the feasibility of the proposed solution, a distribution network situation awareness platform was implemented based on the cloud simulation platform CloudPSS. The hardware architecture of the platform is also present and discussed. An IEEE-33 node system was used to verify the performance of the distribution network situation awareness platform, showing that the platform can significantly improve the real-time situation awareness of the distribution network.