Windräder im Sonnenuntergang

Unsere Publikationen

S. Barber, F. Hammer, Improving Site-Dependent Wind Turbine Performance Prediction Accuracy Using Machine Learning

S. Barber, A. Schubiger, A New Decision Process for Choosing the Wind Resource Assessment Workflow with the Best Compromise between Accuracy and Costs for a Given Project in Complex Terrain

S. Barber, Modeling and Monitoring Erosion of the Leading Edge of Wind Turbine Blades

S. Barber, F. Hammer, Transferability of site-dependent wind turbine performance predictions using machine learning

S. Barber, Research challenges and needs for the deployment of wind energy in atmospherically complex locations

S. Barber, J. Deparday, Y. Marykovskiy, Development of a wireless, non-intrusive, MEMS-based pressure and acoustic measurement system for large-scale operating wind turbine blades

S. Barber, A. Schubiger, The wide range of factors contributing to Wind Resource Assessment accuracy in complex terrain

Y. Marykovskiy, T. Clark, S. Barber and E. Chatzi, “Digital Twin Development Framework in the context of Fluid Structure Interaction” , Wind Energy Science Conference 2021.

H. Müller, T. Polonelli, R. Fischer, S. Barber and M. Magno, “Towards A Self-sustaining Wireless Smart Sensor Node for Continuous Monitoring of Wind Turbines” , Wind Energy Science Conference 2021.

G. Duthé, I. Abdallah, Y. Marykovskiy and S. Barber, “Learning to diagnose leading edge erosion degradation on an airfoil via aerodynamic pressure coefficients”, Wind Energy Science Conference 2021.

J. Deparday, Y. Marykovskiy and S. Barber, “Development of a method for obtaining local inflow angle from pressure gradient at leading edge on operating wind turbine blades” , Wind Energy Science Conference 2021.

Barber and H. Nordborg (2020), Improving site-dependent power curve prediction accuracy using regression trees, Journal of Physics Conference Series Volume 1618

S. Barber, A. Schubiger, S. Koller, A. Rumpf, H. Knaus and H. Nordborg (2020), Actual Total Cost reduction of commercial CFD modelling tools for Wind Resource Assessment in complex terrain, Journal of Physics Conference Series Volume 1618

S. Barber, M. Buehler and H. Nordborg (2020), IEA Wind Task 31: Design of a new comparison metrics simulation challenge for wind resource assessment in complex terrain Stage 1, Journal of Physics Conference Series 1102

Sarah Barber, Machine learning in site specific wind turbine power curve prediction, Energy Data Hackdays 2020

Sarah Barber, The role of machine learning in site-specific wind turbine power curve prediction, Data Science in Climate and Climate Impact Research Workshop, ETH Zurich 2020.

Alain Schubiger, Sarah Barber, and Henrik Nordborg, Evaluation of the Lattice Boltzmann Method for wind modelling in complex terrain, Wind Energy Science Journal 2020. 

Sarah Barber, Alain Schubiger and Henrik Nordborg, A new process for the pragmatic choice of wind models in complex terrain – quantification of "skill score" and "cost", Wind Energy Science Conference, Cork, Ireland, June 2019.  zur Webseite

Sarah Barber, Simon Boller and Henrik Nordborg, Feasibility study for 100% renewable energy microgrids with medium-sized wind turbines in Switzerland, Wind Energy Science Conference, Cork, Ireland, June 2019. 

Alain Schubiger, Sarah Barber and Henrik Nordborg, Evaluation of the Lattice Boltzmann Method for wind modelling in complex terrain, Wind Energy Science Conference, Cork, Ireland, June 2019.

Sarah Barber and Henrik Nordborg, Comparison of simulations and wind tunnel measurements for the improvement of design tools for Vertical Axis Wind Turbines, Journal of Physics: Conference Series, Volume 1102, 2018.

Sarah Barber, Hybride Lösungen für eine zuverlässige Stromversorgung der Zukunft, Energie Experten, September 2018.

Henrik Nordborg, Validierte Simulationen einer vertikalachsigen Windturbine, ANSYS Users' Conference, Juni 2018