SWEPT2

Completed

Renewable Energy Sources(Wind Energy)

Basic and strategic applied research

PHYSICAL SCIENCES AND MATHEMATICS (Applied Mathematics)

Not Cross-cutting

Professor D G Infield
Electronic and Electrical Engineering
University of Strathclyde

Standard

EPSRC

01 May 2015

30 April 2018

36 months

£39,299

Energy

Scotland

Energy : Energy

Professor D G Infield, Electronic and Electrical Engineering, University of Strathclyde

The SWEPT2 consortium is funded via 5 EPSRC grants and one InnovateUK award : see EP/N508500/1, EP/N508512/1, EP/N508524/1, EP/N508536/1, EP/N508548/1, and InnUK/102239/01

The SWEPT2 project aims to develop a sophisticated tool for modelling of wind turbine wakes and wake interactions. It iswell known that present wake models are inadequate, especially for application to large offshore wind farms, and have ledto wind farm designs with larger than expected wake losses. Improved wake models are essential for improved wind farmdesigns with improved energy yield. Validation of wake models is critical but difficult to undertake at full scale. By makinguse of LIDAR and full size turbines, the project aims to collect data on wakes that will provide confidence in the validationprocess. However LIDAR data is not without its own technical challenges, mainly related to data dropout due at times toinadequate back-scatter from aerosol particles. Strathclyde has experience of LIDAR measurement of wind turbine wakesboth onshore and offshore and will apply the methods previously developed to provide high quality data sets to be used formodel validation within the consortium. There are different ways in which flow field measurements and CDF calculationscan be compared to assess the quality of wake models; the Strathclyde team will apply methods previously developed and shown to be effective to the SWEPT2 validation

20/07/15