Success Story: Optimal positioning of mini wind turbines

NCC presenting the success story

NCC Spain

Client/user profile:

A company specialized in distributed energy solutions or energy generated at the place of consumption, tailored to customer needs. International market presence with proprietary and patented technology (patented products developed in-house)


Time and cost savings (from 4 to 12 months to 15 days maximum; in terms of moneyr, from 4000-12000 € cost to 1500-2000 €)

Key points before agreeing on project:

  • Data confidentiality
  • IPR
  • Efficient implementation
  • Secured infrastructure access
  • Migration to client infrastructure

Technical/scientific Challenge:

This challenge needs to develop an application that combines GIS (Geographic Information System), NWP (Numerical Weather Prediction), CFD (Computational Fluid Dynamics) and analytical software, NWP (Numerical Weather Prediction), CFD (Computational Fluid Dynamics) and analytical software in a cloud environment.

The company needs a cloud environment, to provide detailed information about wind flow in urban environments for small wind turbine manufacturers, suppliers and also potential customers.


Development of a computational tool based on HPC-Cloud that provides an accurate estimation of wind potential in an urban area, including identification of acceleration, channeling, blocking, recirculation and turbulence zones.


The application developed in this experiment can provide the potential of wind energy in urban areas at a competitive cost compared to current methods. Currently, the time required for a measurement campaign is in the range of 4 months to one year, with the cost being between 4000 and 12000€, which is high considering the scale of small wind turbine projects, as in some cases, the price is similar to that of the turbine.

The estimated cost of using the application is around 1500-2000 €, requiring approximately 15 days of computational calculations.

This project has received funding from the European High-Performance Computing Joint Undertaking (JU) under grant agreement No 951732. The JU receives support from the European Union’s Horizon 2020 research and innovation program and Germany, Bulgaria, Austria, Croatia, Cyprus, the Czech Republic, Denmark, Estonia, Finland, Greece, Hungary, Ireland, Italy, Lithuania, Latvia, Poland, Portugal, Romania, Slovenia, Spain, Sweden, the United Kingdom, France, the Netherlands, Belgium, Luxembourg, Slovakia, Norway, Switzerland, Turkey, Republic of North Macedonia, Iceland, Montenegro