Professor David Infield
Research Professor
Electronic and Electrical Engineering
Back to staff profile
Prize And Awards
- Fellowship
- Recipient
- 2012
- ICE Baker Medal 2011
- Recipient
- 2011
- Elected member of European Technology Platform Wind
- Recipient
- 10/2008
Back to staff profile
Publications
- Accounting for environmental conditions in data-driven wind turbine power models
- Pandit Ravi, Infield David, Santos Matilde
- IEEE Transactions on Sustainable Energy Vol 14, pp. 168-177 (2023)
- https://doi.org/10.1109/tste.2022.3204453
- Research on the derated power data identification method of a wind turbine based on a multi-Gaussian-discrete joint probability model
- Ma Yuanchi, Liu Yongqian, Yang Zhiling, Yan Jie, Tao Tao, Infield David
- Sensors Vol 22 (2022)
- https://doi.org/10.3390/s22228891
- Wind turbine performance degradation monitoring using DPGMM and Mahalanobis distance
- Guo Peng, Gan Yu, Infield David
- Renewable Energy Vol 200, pp. 1-9 (2022)
- https://doi.org/10.1016/j.renene.2022.09.115
- Current status and grand challenges for small wind turbine technology
- Bianchini Alessandro, Bangga Galih, Baring-Gould Ian, Croce Alessandro, Cruz José Ignacio, Damiani Rick, Erfort Gareth, Simao Ferreira Carlos, Infield David, Nayeri Christian Navid, Pechlivanoglou George, Runacres Mark, Schepers Gerard, Summerville Brent, Wood David, Orrell Alice
- Wind Energy Science Vol 7, pp. 2003-2037 (2022)
- https://doi.org/10.5194/wes-7-2003-2022
- Sequential data-driven long-term weather forecasting models' performance comparison for improving offshore operation and maintenance operations
- Randit Ravi, Astolfi Davide, Tang Anh Minh, Infield David
- Energies — Open Access Journal of Energy Research Vol 15 (2022)
- https://doi.org/10.3390/en15197233
- SCADA data for wind turbine data-driven condition/performance monitoring : a review on state-of-art, challenges and future trends
- Pandit Ravi, Astolfi Davide, Hong Jiarong, Infield David, Santos Matilde
- Wind Engineering Vol 47, pp. 422-441 (2022)
- https://doi.org/10.1177/0309524X221124031
Back to staff profile
Research Interests
My research interests are with electricity generation from renewable energy sources, in particular from wind and to a lesser extent photovoltaics (PV), and the integration of these sources into electricity systems large and small. Associated with this central challenge I take an interest in energy storage technology and application, and increasingly demand side management such as available through controlled charging of electric vehicles.
Specific areas of research related to wind energy that I am presently active in include:
- condition monitoring for large offshore turbines;
- drive train analysis with an emphasis on improving reliability;
- wind resource spatio-temporal modelling; and
- power system support services such as frequency support from wind turbines.
Professional Activities
- IPCC (External organisation)
- Advisor
- 11/8/2017
- Offshore Wind Energy
- Speaker
- 3/5/2017
- Delft University of Technology (External organisation)
- Advisor
- 2/2/2017
- REN21 (External organisation)
- Advisor
- 10/1/2017
- WindEurope Summit 2016
- Chair
- 29/9/2016
- European Academy of Wind Energy (External organisation)
- Member
- 20/9/2016
Projects
- WindEurope Digitalisation Project
- Carroll, James (Principal Investigator) Infield, David (Co-investigator) Leithead, Bill (Co-investigator)
- 01-Jan-2022 - 31-Dec-2023
- Simulated Wakes Effect Platform for Turbines 2 (SWEPT2)
- Infield, David (Principal Investigator)
- "The SWEPT2 project aims to develop a sophisticated tool for modelling of wind turbine wakes and wake interactions. It is well known that present wake models are inadequate, especially for application to large offshore wind farms, and have led to wind farm designs with larger than expected wake losses. Improved wake models are essential for improved wind farm designs with improved energy yield. Validation of wake models is critical but difficult to undertake at full scale. By making use of LIDAR and full size turbines, the project aims to collect data on wakes that will provide confidence in the validation process. However LIDAR data is not without its own technical challenges, mainly related to data dropout due at times to inadequate back-scatter from aerosol particles. Strathclyde has experience of LIDAR measurement of wind turbine wakes both onshore and offshore and will apply the methods previously developed to provide high quality data sets to be used for model validation within the consortium. There are different ways in which flow field measurements and CDF calculations can 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."
- 01-May-2015 - 30-Apr-2018
- AWESOME (H2020 ETN)
- Infield, David (Principal Investigator)
- 01-Jan-2015 - 31-Dec-2018
- EPSRC Centre for Doctoral Training in Wind & Marine Energy Systems | Barrera Martin, Oswaldo
- Leithead, Bill (Principal Investigator) Infield, David (Co-investigator) Barrera Martin, Oswaldo (Research Co-investigator)
- 01-Oct-2014 - 28-Sep-2017
- EPSRC Centre for Doctoral Training in Wind & Marine Energy Systems
- Leithead, Bill (Principal Investigator) Infield, David (Co-investigator)
- 01-Apr-2014 - 30-Sep-2022
- ClimateXchange Energy Storage Literature Review
- Infield, David (Principal Investigator)
- 01-Feb-2014 - 31-Mar-2014
Back to staff profile
Contact
Professor
David
Infield
Research Professor
Electronic and Electrical Engineering
Email: david.infield@strath.ac.uk
Tel: 548 2373