Project Sumary

Wind energy has become increasingly important as a clean and renewable alternative to fossil fuels in the energy portfolios of both Europe and Brazil. At almost every stage in wind energy exploitation ranging from wind turbine design, wind resource assessment to wind farm layout and operations, the application of HPC is a must. The goal of HPCWE is to address the following key open challenges in applying HPC on wind energy: (i) efficient use of HPC resources in wind turbine simulations, via the development and implementation of novel algorithms. This leads to the development of methods for verification, validation, uncertainty quantification (VVUQ) and in-situ scientific data interpretation; (ii) accurate integration of meso-scale atmosphere dynamics and micro-scale wind turbine flow simulations, as this interface is the key for accurate wind energy simulations. In HPCWE a novel scale integration approach will be applied and tested through test cases in a Brazil wind farm; and (iii) adjoint-based optimization, which implies large I/O consumption as well as storing data on large-scale file systems. HPCWE research aims at alleviating the bottlenecks caused by data transfer from memory to disk.

The HPCWE consortium consists of 13 partners representing the top academic institutes, HPC centres and industries in Europe and Brazil. By exploring this collaboration, this consortium will develop novel algorithms, implement them in state-of-the-art codes and test the codes in academic and industrial cases to benefit the wind energy industry and research in both Europe and Brazil.

Project objectives

Target of the project consortium is to bring wind energy simulation towards exascale and to address the key open challenges in applying HPC on wind energy.

  • Efficient use of HPC resources in wind turbine simulations, via the development and implementation of novel algorithms
  • Accurate integration of meso-scale atmosphere dynamics and micro-scale wind turbine flow simulations
  • Adjoint-based optimization

(Coordinator) University of Nottingham

UoN - United Kingdom

Universität Stuttgart - High Performance Computing Center

HLRS - Germany

Imperial College London

ICL - United Kingdom

Technical University of Denmark

(DTU) Denmark

EDF R\&D

(EDF) France

University of Twente

(UTwente) Netherland

University of Edinburgh

EPCC - United Kingdom

Vortex Factoria de Calculs S.L

(Vortex) Spain

University of São Paulo

USP - Brazil

University of Campinas

(UNICAMP) Brazil

Votorantim Energia

(VE) Brazil

Technological Institute of Aeronautics

(ITA) Brazil

Federal University of Santa Catarina

(UFSC) Brazil

   The HPCWE project has received funding from the European Union Horizon 2020 Framework Programme (H2020) under grant agreement number 828799