The Problem of Integrating Digital Twins into Electro-Energetic Control Systems

Abstract

Highlights: What are the main findings? Identification of key parameters, characteristics, and challenges of digital twins in electric power systems. Evaluation and comparison of existing digital twin models based on these key characteristics. What are the implications of the main finding? Recommendations for future development to address challenges such as data security, AI integration, and continuous model updating. Development and continuous improvement of a digital twin model, with the aim of creating a platform for testing, analysis, and education. The use of digital twins (DTs) in the electric power industry and other industries is a hot topic of research, especially concerning the potential of DTs to improve processes and management. This paper aims to present approaches to the creation of DTs and models in general. It also examines the key parameters of these models and presents the challenges that need to be addressed in the future development of this field. Our analysis of the DTs and models discussed in this paper is carried out on the basis of identified key characteristics, which serve as criteria for an evaluation and comparison that sets the basis for further investigation. A discussion of the findings shows the potential of DTs and models in different sectors. The proposed recommendations are based on this analysis, and aim to support the further development and use of DTs. Research into DTs represents a promising sector with high potential. However, several key issues and challenges need to be addressed in order to fully realize their benefits in practice.