Articles | Volume 7, issue 6
https://doi.org/10.5194/wes-7-2231-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/wes-7-2231-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Review article
| 
08 Nov 2022
Review article |
| 08 Nov 2022
| 08 Nov 2022
Research challenges and needs for the deployment of wind energy in hilly and mountainous regions
Andrew Clifton
CORRESPONDING AUTHOR
Stuttgart Wind Energy, University of Stuttgart, Stuttgart, Germany
now at: TGU enviConnect, TTI GmbH, Stuttgart, Germany
Sarah Barber
Institute for Energy Technology, Eastern Switzerland University of Applied Sciences, Oberseestrasse 10, 8640 Rapperswil, Switzerland
Alexander Stökl
Energiewerkstatt e.V., Heiligenstatt 24, 5211 Friedburg, Austria
Helmut Frank
FE13, Deutscher Wetterdienst, Frankfurter Str. 135, 63067 Offenbach, Germany
Timo Karlsson
VTT Technical Research Centre of Finland Ltd., Tekniikantie 21, P.O. Box 1000, 02044 VTT, Espoo, Finland
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Cited
17 citations as recorded by crossref.
- Wind Energy Siting Optimization in Fujian Province, China S. Bimenyimana et al. 10.3390/su162411103
- Performance assessment of wind turbines in near-fault mountain regions subjected to physics-based simulated earthquake ground motions W. Wang et al. 10.1016/j.soildyn.2025.109442
- Visual anemometry for physics-informed inference of wind J. Dabiri et al. 10.1038/s42254-023-00626-8
- Complex terrains and wind power: enhancing forecasting accuracy through CNNs and DeepSHAP analysis T. Konstantinou & N. Hatziargyriou 10.3389/fenrg.2023.1328899
- Long-term Hydrometeorological Time-series Analysis over the Central Highland of West Papua S. Herho et al. 10.18517/ijods.4.2.84-96.2023
- Customized design of wind turbine towers based on a multi-layer optimization model and integrated simulation Y. Zhao et al. 10.1016/j.istruc.2025.109527
- A case study on the feasibility and optimization of wind farm deployment in India L. Agarwal et al. 10.1080/15567036.2025.2537739
- Implications of steep hilly terrain for modeling wind-turbine wakes D. Wang et al. 10.1016/j.jclepro.2023.136614
- Wind Field Modeling over Hilly Terrain: A Review of Methods, Challenges, Limitations, and Future Directions W. Wang & F. Chen 10.3390/app151810186
- Domain-invariant icing detection on wind turbine rotor blades with generative artificial intelligence for deep transfer learning J. Chatterjee et al. 10.1017/eds.2023.9
- Wind Speed Measurement via Visual Recognition of Wind-Induced Waving Light Stick Target W. Zhou et al. 10.3390/app13095375
- Impact of atmospheric turbulence on wind farms sited over complex terrain J. Singh & J. Alam 10.1063/5.0222245
- Resolving three-dimensional wind velocity fields with sequential wind-Doppler LiDAR for wind energy in the complex terrain - Gotthard Pass, Switzerland B. van Schaik et al. 10.12688/openreseurope.19095.1
- Influence of Surface Complexity and Atmospheric Stability on Wind Shear and Turbulence in a Peri-Urban Wind Energy Site W. Zhang et al. 10.3390/en18195211
- A spatio-techno-economic analysis for wind-powered hydrogen production in Tunisia S. Rekik et al. 10.1016/j.aej.2025.07.028
- Multiscale coupling wake simulations for a horizontal-axis wind turbine mounted in complex terrains L. Mi et al. 10.1080/15567036.2025.2449980
- Influence of air flow features on alpine wind energy potential F. Kristianti et al. 10.3389/fenrg.2024.1379863
17 citations as recorded by crossref.
- Wind Energy Siting Optimization in Fujian Province, China S. Bimenyimana et al. 10.3390/su162411103
- Performance assessment of wind turbines in near-fault mountain regions subjected to physics-based simulated earthquake ground motions W. Wang et al. 10.1016/j.soildyn.2025.109442
- Visual anemometry for physics-informed inference of wind J. Dabiri et al. 10.1038/s42254-023-00626-8
- Complex terrains and wind power: enhancing forecasting accuracy through CNNs and DeepSHAP analysis T. Konstantinou & N. Hatziargyriou 10.3389/fenrg.2023.1328899
- Long-term Hydrometeorological Time-series Analysis over the Central Highland of West Papua S. Herho et al. 10.18517/ijods.4.2.84-96.2023
- Customized design of wind turbine towers based on a multi-layer optimization model and integrated simulation Y. Zhao et al. 10.1016/j.istruc.2025.109527
- A case study on the feasibility and optimization of wind farm deployment in India L. Agarwal et al. 10.1080/15567036.2025.2537739
- Implications of steep hilly terrain for modeling wind-turbine wakes D. Wang et al. 10.1016/j.jclepro.2023.136614
- Wind Field Modeling over Hilly Terrain: A Review of Methods, Challenges, Limitations, and Future Directions W. Wang & F. Chen 10.3390/app151810186
- Domain-invariant icing detection on wind turbine rotor blades with generative artificial intelligence for deep transfer learning J. Chatterjee et al. 10.1017/eds.2023.9
- Wind Speed Measurement via Visual Recognition of Wind-Induced Waving Light Stick Target W. Zhou et al. 10.3390/app13095375
- Impact of atmospheric turbulence on wind farms sited over complex terrain J. Singh & J. Alam 10.1063/5.0222245
- Resolving three-dimensional wind velocity fields with sequential wind-Doppler LiDAR for wind energy in the complex terrain - Gotthard Pass, Switzerland B. van Schaik et al. 10.12688/openreseurope.19095.1
- Influence of Surface Complexity and Atmospheric Stability on Wind Shear and Turbulence in a Peri-Urban Wind Energy Site W. Zhang et al. 10.3390/en18195211
- A spatio-techno-economic analysis for wind-powered hydrogen production in Tunisia S. Rekik et al. 10.1016/j.aej.2025.07.028
- Multiscale coupling wake simulations for a horizontal-axis wind turbine mounted in complex terrains L. Mi et al. 10.1080/15567036.2025.2449980
- Influence of air flow features on alpine wind energy potential F. Kristianti et al. 10.3389/fenrg.2024.1379863
Latest update: 03 Nov 2025
Short summary
The transition to low-carbon sources of energy means that wind turbines will need to be built in hilly or mountainous regions or in places affected by icing. These locations are called
complexand are hard to develop. This paper sets out the research and development (R&D) needed to make it easier and cheaper to harness wind energy there. This includes collaborative R&D facilities, improved wind and weather models, frameworks for sharing data, and a clear definition of site complexity.
The transition to low-carbon sources of energy means that wind turbines will need to be built in...
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