Modeling in power industry
We develop new mathematical models of intelligent electric power systems
More →Science. Technology. Energy of the future.
AI and digital twins for reliable and intelligent power engineering
We develop research-driven digital technologies for design, control and operation of next-generation power systems.
40+
years of research in power engineering and AI
15+
researchers and engineers
30+
implemented projects
40+
publications in Q1–Q2 journals
20+
industrial partners
Research areas
Programming in power industry
We develop software to simulate the operation of intelligent electric power systems
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Analysis of the state of equipment
We analyze the current technical state of equipment of electric power systems
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Forecasting the state of equipment
We predict changes in the technical state of equipment of electric power systems throughout its life cycle
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Diagnostics of the equipment state
We carry out diagnostics of the state of equipment of electric power systems by various methods of non-destructive testing
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Digital twin
Digital twin of a 110/10 kV substation
A platform for real-time monitoring and condition analysis of power equipment.
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AI forecasting
ML-based load forecasting
Short- and medium-term load forecasting with external factor analysis.
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Reliability
Failure risk assessment in distribution grids
A model for risk analysis and prioritization based on topology and equipment condition.
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RES and storage
Hybrid energy system optimization
Control algorithms for hybrid systems with renewable generation and storage.
More →Team
Alexandra Khalyasmaa
Head of the laboratory
Pavel Matrenin
Leading researcher
Irina Iumanova
Senior researcher
Andrey Bramm
Junior Researcher
Dmitry Klimenko
Senior researcher
Elena Zinoveva
Researcher
Publications
A Review of XAI Methods Applications in Forecasting Runoff and Water Level Hydrologica…
Andrey Mikhailovich Bramm Matrenin Pavel Viktorovich Khalyasmaa Alexandra Ilmarovna
Analysis of Modern Models Capabilities and Software for Automatic Annotation of Graphi…
Matveev Ivan Viktorovich Khaliasmaa Alexandra Ilmarovna Matrenin Pavel Viktorovich
Approach to Evaluating Fidelity and Consistency of Rule-based Explanations of Machine…
Khaliasmaa Alexandra Ilmarovna Matrenin Pavel Viktorovich
Automated mission planning for aerial large-scale power plant thermal inspection
Eroshenko Stanislav Andreevich
News
🧩 A digital twin is more than a 3D model.
In energy, a digital twin uses real-world data to support monitoring, diagnostics, and condition forecasting.
More →🌆 What happens to a city’s power system in the evening?
Why evening demand rises, and how forecasting, energy storage, and EV charging management can help power systems meet peak loads.
More →🏆 First place at Russian Energy Week 2026
Valeria Borovskikh won first place at REN-2026 Youth Day for research on thermal image quality and AI-based fault detection.
More →⚡ A new youth research laboratory will open at UrFU’s UralENIN.
UrFU’s new youth laboratory will focus on autonomous energy systems, renewables, storage, and control algorithms.
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