• Kseniya E. Korotkova, National Research Irkutsk State Technical University (Irkutsk, Russia)
• Aleksey S. Govorkov, National Research Irkutsk State Technical University (Irkutsk, Russia)

The article discusses the main components of digital twins and their interconnections, the specific features of distributed generation units, and the challenges that arise during their use. Digital twin technology is currently widely used in industrial production. Digital twins act as virtual analogues of physical objects, groups of objects, or processes. They are complex software solutions based on large volumes of data and the synthesis of artificial intelligence, machine learning, and specialized software, enabling the creation of dynamic digital models capable of live interaction and adaptation. The article presents a methodology for constructing digital twins of distributed generation units, the use of which helps optimize the design, operation, and monitoring of electric power systems. The methodology is presented using a turbogenerator unit as an example and includes the following stages: collecting data on the physical object, modeling the turbogenerator unit, and comparing experimental data and the response of a fuzzy model. The scientific novelty of the study lies in the development of a hybrid approach combining neural networks, a fuzzy inference system, and a genetic algorithm. The study identified the minimum root-mean-square deviation (RMS) of the model's response to experimental data, determined the optimal number of rules in a fuzzy system (144 rules), and established the relationship between model accuracy and computational costs. The practical significance of the results lies in the potential application of the developed method to optimize the operation of distributed generation units, improve power supply reliability, and enhance the management efficiency of electric power systems. The proposed approach enables the creation of accurate digital models capable of adapting to changing operating conditions. The research findings can be used in the development of new energy systems, the modernization of existing facilities, and the implementation of Smart Grid technologies. The proposed approach opens new prospects for the development of energy-efficient and reliable power supply systems.

digital twins, distributed generation installations, Smart Grids

2026-06-05