The research group develops advanced solutions for the analysis, optimization, and operation of modern power systems with high shares of renewable energy sources (RES). Its core expertise includes transmission and distribution network planning studies, grid integration analyses for new generation and demand, protection system coordination, techno-economic assessment of energy projects, electricity market analysis, optimal sizing of energy systems, and the application of advanced optimization and machine learning techniques through the development of specialized software tools.

 

The group’s research aims to enhance the reliability, flexibility, and efficiency of future power systems while maintaining a strong focus on technology transfer and close collaboration with industry partners.

• Optimization of transmission and distribution system operation with high penetration of renewable energy sources (RES) and electric vehicles (EVs)
• Development of specialized software tools and simulation models for the power industry
• Application of machine learning and deep learning methods for power system diagnostics and forecasting
• Transmission and distribution network development studies (long-term planning, congestion analysis, network development scenarios, etc.)
• Grid impact assessments for the integration of new generation units, energy storage systems, and electric vehicle charging infrastructure
• Verification of grid connection compliance with technical requirements, grid codes, and regulatory standards
• Protection system coordination and settings for transmission and distribution networks, including challenges associated with inverter-based resources
• Techno-economic assessment of energy projects and investments (LCOE, LCOH, feasibility studies, technology comparison, etc.)
• Optimal sizing of energy systems, including generation units, battery energy storage systems, EV charging infrastructure, and microgrids
• Electricity market analysis and optimization of market participation strategies for generation and consumption portfolios
• Application of advanced optimization techniques in power system planning and operation
• Machine learning and deep learning methods for forecasting and diagnostics of key power system parameters

Laboratories

• Laboratory for Power System Simulation and Real-Time Analysis
• Laboratory for Microgrids and Renewable Energy Systems
• Experimental Smart Grid Electric Vehicle Charging Laboratory

Equipment

• OPAL-RT real-time simulation platform for power systems and power electronics, including RT-LAB, ePHASORsim, and eHS software packages
• Engineering software: MATLAB/Simulink, PLECS, PowerFactory, NEPLAN, RT-LAB, ePHASORsim, eHS, GridLAB-D, OpenDSS, PowerCAD, WinDIS, EMTP-RV, EMTP-ATP, and others
• Microgrid laboratory testbed for implementing and validating control algorithms for photovoltaic systems and battery energy storage
• Photovoltaic modules based on different technologies and battery testing systems
• Meteorological station
• Electric vehicle charging infrastructure consisting of a 2 × 11 kW EVBox Elvi charging station, a 22 kW go-e mobile charger, and a backend management platform for charger monitoring and control
• Measurement equipment including oscilloscopes, electrical and non-electrical sensors, torque meters, and rotational speed measurement devices
• Optimization software and solvers: GAMS, GUROBI, and CPLEX

Advanced computing resources

• High-performance workstations for power system optimization using GAMS, PYOMO, JuMP, GUROBI, CPLEX, and related tools, as well as for machine learning and deep learning applications in power system diagnostics and forecasting

• 2025-2029 -FLEXsys: Implementation of Flexibility Resources and Advanced Control Algorithms for Modern Power Systems with High Shares of Renewable Energy Sources
• 2024-2026 – LUMINIH2: Laboratory Model and Prototype of a Control and Monitoring System for Microgrids with Renewable Energy Sources and Hydrogen Technologies
• 2021-2023 – MsEVP: Research and Development of a Smart Grid Electric Vehicle Charging Station Integrated into a Rotary Parking Structure
• 2021-2023 – GridS: System for Establishing a Stable Electricity Distribution Network
• 2020-2025 – ADVANCE-RES: Application of Advanced Optimization and Machine Learning Methods in Planning and Operation of Power Systems with High Shares of Renewable Energy Sources

The research group welcomes collaboration with universities and research institutions, power utilities, transmission and distribution system operators (TSOs and DSOs), equipment manufacturers, engineering and consulting companies, and industrial partners in the planning, analysis, and optimization of power systems with high shares of renewable energy sources.Its particular expertise includes transmission and distribution network development studies, grid integration studies for new generation units, energy storage systems, and electricity consumers, verification of compliance with grid connection requirements, and the design and coordination of protection systems in networks with a high penetration of inverter-based resources. The group also offers extensive expertise in techno-economic assessment of energy projects and investments, optimal sizing of energy systems—including generation units, battery energy storage systems, electric vehicle charging infrastructure, and microgrids—as well as electricity market analysis and the development of market participation strategies. A key strength of the group is the development of specialized software tools and simulation models tailored to the specific needs of industrial partners, combined with the application of advanced machine learning and deep learning techniques for power system diagnostics and forecasting. Collaboration opportunities include joint research and innovation projects (including Horizon Europe, Interreg, and national HRZZ and NPOO funding programmes), technical and feasibility studies, expert reports and consulting services, development of specialized software tools, validation of control, protection, and optimization algorithms, technical support, professional training and continuing education, as well as access to the group’s laboratory facilities and research infrastructure.