David Infield


  • United Kingdom

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Personal 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.

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.  

Education/Academic qualification

Doctor of Science, University of Kent

Bachelor of Mathematics and Physics, Lancaster University

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Projects 2007 2022

Research Output 2001 2020

3 Citations (Scopus)
Condition monitoring
Wind turbines
Exponential functions
Fault detection
Chemical analysis
3 Citations (Scopus)
22 Downloads (Pure)

Comparison of advanced non-parametric models for wind turbine power curves

Pandit, R. K., Infield, D. & Kolios, A., 8 Jul 2019, In : IET Renewable Power Generation. 13, 9, p. 1503-1510 8 p.

Research output: Contribution to journalArticle

Open Access
Wind turbines
Support vector machines
Curve fitting
Fault detection
Data acquisition


Development of novel gearbox lubrication condition monitoring sensors in the context of wind turbine gearboxes

Author: Hamilton, A., 1 Oct 2013

Supervisor: Quail, F. (Supervisor) & Infield, D. (Supervisor)

Student thesis: Doctoral Thesis

Dynamic response of spar-type offshore floating wind turbines

Author: Proskovics, R., 1 Oct 2014

Supervisor: Day, A. (Supervisor) & Infield, D. (Supervisor)

Student thesis: Doctoral Thesis


Elected member of European Technology Platform Wind

David Infield (Recipient), Oct 2008

Prize: Election to learned society


David Infield (Recipient), 2012

Prize: Election to learned society


Activities 2004 2017

IPCC (External organisation)

David Infield (Advisor)
11 Aug 20175 Sep 2017

Activity: Membership typesMembership of committee

Offshore Wind Energy

David Infield (Speaker)
3 May 2017

Activity: Talk or presentation typesInvited talk