Razgar Ebrahimy

Razgar Ebrahimy serves as Head of the Dynamical Systems Section and Senior Researcher at the Department of Applied Mathematics and Computer Science, DTU Compute, Technical University of Denmark. His expertise spans energy systems modeling, smart grid technologies, and data-driven solutions for grid flexibility and renewable integration.

His research centers on Demand-Side Flexibility, Energy Systems Optimization, and Data-Driven Control, employing stochastic methodologies and machine learning to address challenges in district heating, power system stability, and renewable forecasting. Key contributions target UN Sustainable Development Goals for affordable clean energy (SDG7).

Recent publications (2023-2025) reveal a strong focus on deep learning for energy forecasting, incentive-based flexibility mechanisms, and secure grid automation. Notable trends include photovoltaic prediction models, stochastic optimization for thermal systems, and middleware solutions for low-voltage grids, collectively advancing sustainable energy management.

Dr. Ebrahimy mentors PhD students including M. Solé Àvila on data-driven modeling for smart energy systems. He leads critical research initiatives:

• BEGONIA (2024-2026): Cross-border digital platforms for energy internet and transport optimization
• ARV (2022-2025): Climate-positive circular communities through energy renovation
• IEA DHC Annex TS9 (2025-2027): Digitalization of district heating for efficiency improvement

He collaborates within DTU Compute's Dynamical Systems group and the CitCom.ai TEF facility, driving innovation in AI for smart cities and grid automation through international partnerships.