Alexey V. Edelev, Dmitriy N. Karamov, Olga Yu. Basharina

Melentiev Energy Systems Institute SB RAS, National Research Irkutsk State Technical University, Matrosov Institute for System Dynamics and Control Theory of SB RAS, Ural State University of Economics

This work is the first of a series of articles devoted to the application of the developed digital twin technology of a complex technical system for the study of its properties. One of these properties is resilience, which is understood as the property of these energy complexes to adapt to large disturbances and restore their initial state after their impact. Autonomous micro-networks are considered as complex technical systems in the article. The study of the resilience of these local-level energy complexes is usually based on multivariate computational experiments, however, if there is a feedback of a digital twin with a micro-grid or a test bench, field experiments can also be used. The key component of the digital twin of the microgrid should be a complex of various models that accurately describe all aspects of the behavior of this energy complex. This article describes an optimization model of a microgrid based on the concept of an energy hub. The energy hub concentrates production capacities for generating, converting and accumulating energy resources, which are connected to each other and to consumers using energy transport networks. The article presents a software implementation of an optimization model of a microgrid based on the concept of an energy hub. In conclusion, a comparison is made with a fundamentally similar two-level model of the city's energy complex, showing that the modeling of a microgrid based on the concept of an energy hub provides higher computational efficiency. On the other hand, the model of the energy complex of the city more accurately than the microgrid model presented in this article reflects the physical features of some processes, for example, the transport of heat and electricity.

digital twin, test-bed, micro-grid, resilience, mathematical model, energy hub