Modeling in power industry

The research area focuses on the development of fundamental and applied methods for mathematical modeling of modern power systems, including intelligent energy complexes, distributed generation systems, and digital energy platforms.

The research activities involve the development of mathematical models and computational methods for analyzing power system operating modes, forecasting system conditions, assessing reliability, and improving the efficiency of energy facility operation. Particular attention is given to the creation of intelligent models that combine physical representations of processes in power systems with data processing methods, machine learning, and artificial intelligence technologies.

One of the key research directions is the development of digital twins of energy facilities, enabling virtual modeling of various operating conditions, analysis of emergency scenarios, prediction of equipment technical states, and generation of solutions for intelligent energy system management.

The research also includes the development of algorithms for diagnostics and monitoring of electrical equipment, methods for detecting faults and abnormal operating conditions, as well as models for integrating renewable energy sources, energy storage systems, and distributed energy resources.

The obtained results contribute to the digital transformation of the power industry, improving the reliability and resilience of energy infrastructure, and creating intelligent decision-support systems for the operation of modern energy facilities.