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Gregor GiebelView profile

Researcher

• Wind Power Forecasting
• Renewable Energy Integration
• Wind Farm Flow Control
• +7 more

Dr. Gregor Giebel is a senior researcher and Head of Section in the Department of Wind and Energy Systems at the Technical University of Denmark (DTU), specifically within the Renewable Plants in Energy Systems group. He is actively engaged in advancing wind energy technologies and their integration into modern power systems. His leadership extends to major international and EU-funded initiatives, including IEA Wind Task 51 and the NEST Facilities research infrastructure. Gregor Giebel's research focuses on short-term wind power forecasting , large-scale integration of wind into electricity grids , wind farm flow control , and condition monitoring of wind turbines . His work is instrumental in improving the reliability and efficiency of renewable energy systems. He has made significant contributions to international standardization through the IEC and is a key figure in global wind energy research coordination. The recent publications highlight a strong trend toward weather-driven energy forecasting , modeling wind farm impacts on weather systems , and developing national research infrastructures for energy transition . These works reflect a deep integration of meteorology, energy systems engineering, and policy-relevant research. His scientific recognition includes: Poster Award at the WindEurope Offshore Conference, Copenhagen 2019 Poster Award on WindEurope Conference, Copenhagen 2021 Dr. Giebel is a Principal Investigator (PI) on multiple high-impact projects such as NEST Facilities , IEA Wind Task 51 , and GreenHyScale . He is renowned for his success in research funding, with a proposal success rate exceeding 50%. He has led the EU Marie Curie Initial Training Network Train 2 Wind and previously headed the FarmConners EU Coordination Action on wind farm control. He leads and is deeply involved in the NEST Facilities —a distributed Danish research infrastructure for energy transition—and contributes significantly to the Weather2X and GreenHyScale projects, which aim to advance green hydrogen production and weather forecasting for energy systems.

• Climate Dynamics
• Numerical Weather Prediction (NWP)
• Atmospheric Modeling
• +3 more

Professor Eigil Kaas is affiliated with the Niels Bohr Institute at the University of Copenhagen . His work spans climate dynamics , numerical weather prediction (NWP) , and atmospheric modeling . As former Section Head of Climate and Computational Geophysics , he leads research on climate-chemistry coupling and sea ice impacts. Education : MSc (1987) and PhD (1993) in Meteorology from University of Copenhagen Research Focus : Climate dynamics and physics Numerical methods in atmospheric models Machine learning for weather prediction Arctic sea ice-climate interactions Thunderstorm electricity and radiation Coupled atmosphere-ocean modeling Article Trends : Recent work combines neural networks with radiative transfer optimization Focus on storm dynamics and gamma-ray flashes Extreme precipitation modeling under climate change Pioneering tidal flow studies in Faroe Island fjords Teaching Legacy : Instructor of Atmospheric Physics and Dynamical Meteorology courses Developed zonally averaged climate model for educational use Mentored 12 PhD/MSc students with DMI/ECMWF collaborations Professional Roles : Chairman of BFI Group 28 (Geosciences & Climate) Scientific Advisory Committee member at ECMWF Project lead in EU ENSEMBLES and PEGASOS initiatives

Amin HajizadehView profile

Associate Professor

• Renewable Energy Systems
• DC Microgrids
• Offshore Renewable Energy
• +6 more

Amin Hajizadeh is an Associate Professor at Aalborg University (AAU), affiliated with the Esbjerg Energy Section in the Faculty of Engineering and Science . His research focuses on renewable energy systems, DC microgrids, offshore renewable energy integration, and AI-driven energy solutions. He holds a PhD in Electrical Power Engineering (2010). Research Highlights: Developing control strategies for modular multiport DC-DC converters and offshore wind-hydrogen systems Advancing energy management in net-zero buildings and smart city frameworks Pioneering work in AI-based wake steering for wind farm optimization Projects & Awards: Lead investigator in BlueBARGE (€5M EU project on renewable bunkering for anchored ships) Recipient of the 2024 Best Paper Award for work on neural network-based wake steering Key Contributions: Published 140+ papers in journals like IEEE Transactions and Renewable Energy Supervised 6 PhD students and contributed to 19 funded research projects Active in editorial roles (e.g., IET Renewable Power Generation)

Julian Antony QuickView profile

Researcher

• Wind Power
• Wind Turbine Engineering
• Compressed Air Motors
• +3 more

Julian Antony Quick is a Researcher at the Department of Wind and Energy Systems within the Technical University of Denmark . His work focuses on wind farm optimization, energy management, and market-driven renewable energy systems. Active research in wind farm control and market integration Specializes in hybrid power plant design and uncertainty quantification Contributes to UN Sustainable Development Goals through wind energy research His research explores advanced optimization techniques for wind resource assessment, turbine design, and revenue maximization in electricity markets. Key areas include: Compressed air energy storage integration Wind farm layout optimization Surrogate-based system modeling Dynamic energy management strategies While not explicitly listed, his collaborative projects suggest active involvement in PhD supervision and industry partnerships across Europe. His recent publications demonstrate a strong focus on translating technical advances into economic benefits through: Market-aware wind farm design Data-driven flow control Hybrid system efficiency improvements SDG-aligned sustainable energy solutions

Charlotte Bay HasagerView profile

Professor

• Offshore Wind Energy Meteorology
• Remote Sensing
• Boundary-layer Meteorology
• +4 more

Charlotte Bay Hasager serves as Professor in the Department of Wind and Energy Systems at the Technical University of Denmark (DTU), specializing in offshore wind energy meteorology with expertise in remote sensing, boundary-layer processes, and environmental load impacts on wind turbines. Her research directly supports UN Sustainable Development Goals through renewable energy innovation and climate action initiatives. Her primary research domains include: Offshore wind resource assessment using satellite and radar technologies Boundary-layer meteorology and surface flux dynamics Leading edge erosion mechanisms from rain-wind interactions AI-driven operational strategies for wind farm durability Synthetic Aperture Radar (SAR) applications for wind field mapping Recent publications (2024-2025) demonstrate converging trends in erosion risk modeling, reinforcement learning for turbine operation, and advanced remote sensing techniques. These works span renewable energy engineering, meteorological science, and artificial intelligence applications, with strong emphasis on practical solutions for offshore wind farm challenges under extreme weather conditions. Professor Hasager actively secures major research funding through projects including: AIRE Horizon Europe project (2023-2026): Atmospheric flow integration for wind farm design Thunderbolt project (2023-2025): Wind power optimization initiatives ESA WAII project (2023-2025): Explainable AI for SAR wind assessment CCA LEE project (2022): Leading Edge Erosion cross-cutting research INOWER project (2022-2023): International offshore wind energy networks She maintains significant scientific leadership through conference organization (6th International Symposium on Leading Edge Erosion, 2025), workshop participation (Sandia Blade Workshop, 2024), and media contributions on wind energy topics including North Sea wind farm impacts and satellite Earth observation.

• Wind Energy Systems
• Renewable Energy
• Energy Systems Engineering
• +4 more

Matti Juhani Koivisto is a Senior Researcher at the Department of Wind and Energy Systems at the Technical University of Denmark (DTU). His work focuses on renewable energy systems integration, particularly wind power modeling and analysis within large-scale energy systems. His research expertise spans several critical domains in renewable energy: Wind Energy Systems Engineering (100%) Wind Power Engineering (89%) Variable Renewable Energy Integration (80%) Power Engineering (56%) Time Series Analysis in Energy Systems (37%) Energy Engineering (35%) Dr. Koivisto's research addresses fundamental challenges in renewable energy integration, with particular emphasis on wind power forecasting, variability analysis, and the impacts of climate change on renewable resources. His work bridges theoretical modeling with practical energy system applications, contributing to more reliable and efficient integration of renewable energy sources into power grids. His recent publications demonstrate a strong focus on offshore wind energy, hybrid power plants, and advanced modeling techniques for wind farm generation. His work on increasing the resolution of solar and wind time series has been particularly influential in energy system modeling, addressing critical data requirements for high renewable penetration scenarios. Dr. Koivisto contributes significantly to UN Sustainable Development Goals related to affordable and clean energy (SDG 7) and climate action (SDG 13), with research directly addressing the technical challenges of transitioning to sustainable energy systems. He is actively involved in several major international research projects including AWETRAIN (Airborne Wind Energy Training), DTWO (Federated Digital Twins for Wind-Offshore), and GREAT (GRid Enhancement for Ancillaries in Tomorrow's power systems), where he serves as both project participant and PhD supervisor.

Mahdi AbkarView profile

Associate Professor

• Fluid Mechanics
• Turbulence
• Data-driven Modeling
• +5 more

Mahdi Abkar is an Associate Professor at the Department of Mechanical and Production Engineering, Aarhus University, leading the Fluids and Energy section. His research focuses on fluid mechanics, turbulence modeling, and wind energy optimization using computational fluid dynamics (CFD) and machine learning techniques. Research Areas: Fluid Mechanics, Turbulence, Wind Energy, Data-Driven Modeling Affiliation: Aarhus University, College of Engineering His recent work emphasizes turbulence modeling, LES/RANS simulation improvements, and wind farm power prediction. Articles highlight data-augmented models, flow separation analysis, and drag reduction strategies. He contributes to CFD applications in renewable energy systems, including ultrasonic flow meter design and atmospheric boundary layer interactions.

Pierre-Elouan Mikael RéthoréView profile

Researcher

• Wind Turbine Engineering
• Computational Fluid Dynamics
• Offshore Wind
• +7 more

Pierre-Elouan Mikael Réthoré is a Researcher at the Department of Wind and Energy Systems of the Technical University of Denmark (DTU). His work focuses on wind energy systems, particularly in Wind Turbine Engineering , Computational Fluid Dynamics , and Offshore Wind technologies. He leads the System Engineering and Optimization section within the Wind Energy Systems Division .

Srinivasa Raghavendra Bhuvan GummidiView profile

Assistant Professor

• Algorithms for Geographical Information Systems
• Database Systems
• Optimization Algorithms
• +7 more

Srinivasa Raghavendra Bhuvan Gummidi is an Assistant Professor at the Department of Green Technology (IGT) within the University of Southern Denmark . His research focuses on Circular Economy , Building Stock Modeling , and Environmental Impact Assessment through advanced Geographical Information Systems (GIS) and Deep Learning techniques. Recent work includes high-precision building material identification and spatiotemporal tracking of urban material stocks. Research Keywords : Algorithms for Geographical Information Systems, Optimization Algorithms, Building Stock Modeling, Circular Economy, Deep Learning, Environmental Impact Assessment His peer-reviewed publications (2025–2015) span topics from urban material sustainability to spatial crowdsourcing systems . He teaches Geographic Information Systems for Engineering Sustainability (2024) and collaborates internationally on urban development and resource management projects.

Paul van der LaanView profile

Researcher

• Wind Energy
• Computational Fluid Dynamics
• Atmospheric Boundary Layer
• +3 more

Paul van der Laan is a Senior Researcher at the Department of Wind and Energy Systems, Technical University of Denmark (DTU). His work focuses on wind energy systems, particularly computational fluid dynamics (CFD) modeling of wind turbine wakes, atmospheric boundary layers, and wind farm flow optimization. He actively contributes to research projects and publications in wind energy, with a focus on Reynolds-averaged Navier-Stokes (RANS) simulations and turbulence modeling. Research Interests: Wind energy systems, CFD modeling, atmospheric boundary layers, wind turbine wake analysis, turbulence modeling, and wind farm parametrization. Projects: Involved in initiatives like Train2Wind (Training School in Entrainment of Wind Power) and EERA-DTOC (Design Tools for Offshore Wind Farm Clusters). Supervision: Supervises PhD students in wind energy-related research, including M. C. Baungaard and others. Collaborations: Works with European Union institutions, DTU colleagues, and international researchers on wind farm CFD validation. Recent publications emphasize RANS-based wake modeling, turbulence intensity adjustments, and wind farm cluster simulations. His methodologies enhance predictive accuracy for wind turbine interactions and energy production efficiency. Paul’s contributions align with UN Sustainable Development Goals for renewable energy development. He is currently active in conference presentations and scientific supervision, with a focus on improving wind farm simulation tools like PyWake. No explicit scientific awards are mentioned in the provided text.

Ju FengView profile

Researcher

• Wind Energy Systems
• Floating Offshore Wind Farms
• Wind Farm Optimization
• +6 more

Ju Feng is a Senior Researcher at the Department of Wind and Energy Systems, Technical University of Denmark (DTU), specializing in Wind Energy Systems , Wind Farm Optimization , and Control Strategies . He contributes to research in Floating Offshore Wind Farms , Multi-Disciplinary Optimization , and Noise Propagation . His work includes developing simulation tools, wake models, and control frameworks for wind farms in complex environments. Research Interests: Optimization of wind farm design and operation Advanced wake and flow modeling AI-driven wind energy solutions Noise control and acoustic propagation Multi-fidelity/multi-disciplinary modeling Cost-effective wind farm technologies Publication Trends: Ju Feng's recent work (2022-2024) focuses on floating offshore wind farms , noise constraints , and multi-disciplinary integration . Older articles (2012-2017) emphasize control algorithms , wake modeling , and optimization frameworks . Advising: Supervising PhD Student Wang R. (AI-Augmented Wind Farm Design Optimization, 2025-2028) Co-supervising Nyborg C. M. (Noise Control in Wind Farms, 2019-2023) Collaboration Network: Active in international projects like DecoWind, ModFarm, and FarmConners. Collaborates with institutions such as DTU Wind Energy and researchers including Shen W. Z. , Réthoré P.-E. , and Bredmose H. .

Helge Aa MadsenView profile

Professor

• Wind Turbine Engineering
• Aerodynamic Modeling
• Renewable Energy Systems
• +3 more

Helge Aa Madsen is a Professor at the Department of Wind and Energy Systems , Technical University of Denmark . His work focuses on wind turbine aerodynamics, active flap systems, and renewable energy optimization. Research Areas: Rotor Aerodynamics, Blade Element Momentum Theory, Computational Fluid Dynamics (CFD), Active Load Control, Wake Modeling Projects: IEA Wind TCP Task 47 TURBINIA Phase II (2025-2029), Hydrogen Wind Turbine Project (2022), LowWind System Integration (2019-2021) Recent Publications emphasize rotor aerodynamic modeling for non-uniform inflow, actuator disc theory applications, electricity price integration in turbine design, and active flap system validation on 4.3 MW turbines. His research spans Wind Turbine Engineering , Renewable Energy Systems , and Aeroelastic Dynamics . Scientific Contributions : 2011: Poster Prize for quasi-3D wake computation Student Supervision : PhD Student: Gamberini, A. (2020-2023) PhD Student: Li, A. (2019-2022)

Mac GaunaaView profile

Researcher

• Wind Turbine Engineering
• Rotors Engineering
• Airfoil Engineering
• +12 more

Mac Gaunaa is a Senior Scientist at the Department of Wind and Energy Systems at the Technical University of Denmark (DTU). His work focuses on wind turbine aerodynamics, computational fluid dynamics, and renewable energy systems. He has contributed to advancements in actuator disk modeling, wind rotor performance, and airborne wind energy technologies. Research Interests: Wind Turbine Engineering, Rotors, Airfoil Design, Vortex Dynamics, Computational Fluid Dynamics, and Airborne Wind Energy Systems. Projects: Supervised PhD projects on aerodynamic performance in complex terrain, developed next-generation aerodynamic models, and contributed to Martian habitat wind energy research. Publications: Authored 181 publications, including peer-reviewed journal articles and conference proceedings, with recent work on streamwise flow acceleration, rooftop wind energy, and lifting line corrections. Supervision: Served as supervisor for PhD students like Zengler, C. P. and Li, A., and participated in numerous collaborative projects. Media: Engaged in public outreach through media contributions on topics like ferry wind resistance reduction and wind turbine design principles.

Kirsten Mølgaard NielsenView profile

Associate Professor

• Control Systems
• Automation
• Renewable Energy
• +8 more

Kirsten Mølgaard Nielsen is an Associate Professor in the Department of Electronic Systems at Aalborg University, under The Technical Faculty of IT and Design. She is affiliated with the Automation & Control Green Lab, focusing on sustainable automation and control systems for energy and environmental applications. University: Aalborg University School: The Technical Faculty of IT and Design Department: Department of Electronic Systems Research Lab: Automation & Control Green Lab Email: kmn@es.aau.dk Phone: +4599408761 ORCID: https://orcid.org/0000-0002-2552-1764 Her research interests include control systems, automation, renewable energy (particularly wave and wind), digital hydraulics, smart grids, and wastewater treatment. She has contributed extensively to projects involving energy storage, process control, and sustainable engineering solutions. Her recent publications (2018–2022) demonstrate a strong trend in environmental and energy control systems, particularly in wastewater treatment plant optimization, sewer flow management, and refrigeration system control. These works highlight her expertise in applying advanced control strategies to real-world engineering challenges. She has participated in multiple research projects such as 'Digital Hydraulic Power Take Off for Wave Energy', 'IFIV: Intelligent Remote Control of Individual Heat Pumps', and 'Plug and Play Process Control (P³C)', showcasing her collaborative and interdisciplinary approach. Kirsten Mølgaard Nielsen has not received any explicitly mentioned scientific awards in the provided texts. There is no indication of student advising or grants, though her role in major research projects suggests leadership and mentorship within her team. She is actively involved in research and development within the Automation & Control Green Lab, contributing to advancements in sustainable energy and environmental control technologies.

Corneliu BarbuView profile

Professor

• Electrical Energy Systems
• Renewable Energy Technologies
• Battery Storage Systems
• +3 more

Corneliu Barbu is a Professor at the Department of Electrical and Computer Engineering, Aarhus University, specializing in Electrical Energy Technology. He holds affiliations within the Faculty of Engineering and additional institutional roles. His work focuses on renewable energy systems, battery storage technologies, and wind turbine control. Key projects include high-performance power converters for electric transport, sustainable battery systems, and energy storage integration. Research interests span electrical energy systems, wind energy optimization, and advanced control methodologies. Notable projects include Reinventing High-performance Power Converters for Heavy-Duty Electric Transport (2022–2025) and Copper-Based Flow Batteries for Energy Storage (2020–2023). Publications emphasize wind turbine control, battery management, and vibration damping in mechanical systems. He has contributed to anti-windup control strategies and combustion dynamics in industrial gas turbines. His contact details include coba@ece.au.dk and +45 93 52 13 25.