Professor David Infield

Research Professor

Electronic and Electrical Engineering

Personal statement

I joined the University in 2007 as Professor in Renewable Energy Technologies.  Together with colleagues, a considerable wind energy research activity has been built up since then. For five years I was Manager of the Doctoral Training Centre in Wind Energy Systems, delivering four year PhDs with a considerable training element; this was extended into the Centre for Doctoral Training in Wind and Marine Energy Systems for which I played a leading managerial role before retiring and taking on the role of Research Professor.  My teaching was mainly to these Doctoral students although I also supervised Undergraduate and Masters student projects across a range of renewable energy related topics.

My main responsibility outside the University is as Editor in Chief of the IET’s Renewable Power Generation journal.  


Probabilistic real-time thermal rating forecasting for overhead lines by conditionally heteroscedastic auto-regressive models
Fan Fulin, Bell Keith, Infield David
IEEE Transactions on Power Delivery Vol 32, pp. 1881-1890 (2017)
A hybrid forecasting method for wind power ramp based on Orthogonal Test and Support Vector Machine (OT-SVM)
Liu Yonqian, Sun Ying, Infield David, Zhao Yu, Han Shuang, Yan Jie
IEEE Transactions on Sustainable Energy Vol PP, pp. 1-7 (2016)
Probabilistic weather forecasting for dynamic line rating studies
Fan Fulin, Bell Keith, Infield David
2016 Power Systems Computation Conference (PSCC) 19th Power Systems Computation Conference, pp. 1-7 (2016)
A review of grid-tied converter topologies used in photovoltaic systems
Xiao W, El Moursi M S, Khan O, Infield D
IET Renewable Power Generation (2016)
Numerical weather prediction wind correction methods and its impact on computational fluid dynamics based wind power forecasting
Liu Yongqian, Wang Yimei, Li Li, Han Shuang, Infield David
Journal of Renewable and Sustainable Energy Vol 8 (2016)
Mapping hail meteorological observations for prediction of erosion in wind turbines
MacDonald Hamish, Infield David, Nash David H, Stack Margaret M
Wind Energy Vol 19, pp. 777-784 (2016)

more publications

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)
Offshore Wind Energy
Delft University of Technology (External organisation)
REN21 (External organisation)
WindEurope Summit 2016
European Academy of Wind Energy (External organisation)

more professional activities


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-Jan-2015 - 30-Jan-2018
ClimateXchange Energy Storage Literature Review
Infield, David (Principal Investigator)
01-Jan-2015 - 01-Jan-2015
Infield, David (Principal Investigator)
01-Jan-2015 - 31-Jan-2018
GE Campbell Booth CEPRI
Infield, David (Academic) Booth, Campbell (Academic) Xu, Liqiang (Academic)
UOS staff to attend CEPRI/UOS steering group on 25th July 2014 in Bejing and discuss a number of items. A steering group has already been established. Specific activities and objectives, as already discussed include - exchange of students/engineers between both parties, co-sponsorship and seeking of external funding for research projects including jointly organising technical workshops to identify and pursue opportunities, funding for potential joint research could be from future calls by EPSRC and NSFC, Ministry of Science and Technology of China through international joint research projects, Royal Society of Edinburgh through joint research funding schemes, European calls under EU2020 Horizon project for which CEPRI is a qualifies partner, co-authoring of journal and internationally-respected conference papers.
21-Jan-2014 - 21-Jan-2015
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-Jan-2014 - 28-Jan-2017
EPSRC Centre for Doctoral Training in Wind & Marine Energy Systems
Leithead, Bill (Principal Investigator) Infield, David (Co-investigator)
01-Jan-2014 - 30-Jan-2022

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