Details of Grant 

EPSRC Reference:	EP/K007386/1
Title:	Wind Turbine Gust Prediction
Principal Investigator:	Jones, Dr BL
Other Investigators:
Researcher Co-Investigators:
Project Partners:	Vestas
Department:	Automatic Control and Systems Eng
Organisation:	University of Sheffield
Scheme:	First Grant - Revised 2009
Starts:	01 March 2013	Ends:	30 April 2014	Value (£):	98,611
EPSRC Research Topic Classifications:	Wind Power
EPSRC Industrial Sector Classifications:	Energy
Related Grants:
Panel History:	Panel Date Panel Name Outcome 31 Jul 2012 Engineering Prioritisation Meeting - 31 July Announced
Summary on Grant Application Form
Offshore wind power generation is a key component of the UK's commitment to deliver 15% of gross final energy consumption from renewable sources by 2020. Efforts to meet this target are prompting the design of ever larger turbines in order to capture more energy from the wind. However, as these structures grow taller, they become increasingly vulnerable to violent gusts of wind and other turbulent flow phenomena that are the primary cause of severe turbine damage. Advance warning of such gusts will enable turbine control systems to take preventative action, and so the ability to predict the strength of an oncoming gust is widely regarded within the wind energy industry as being a problem of critical importance. This research project will seek to overcome this problem by demonstrating a system that can accurately forecast the velocity profile of an oncoming wind, given only limited spatial measurements from state-of-the-art light detection and ranging (LIDAR) units. This approach will exploit recent interdisciplinary advances in the application of optimal estimation techniques, from the control systems community, to fluid-mechanical systems governed by the Navier-Stokes equations. The research will draw upon the PI's existing expertise in dynamical estimation of fluid flows and the project results will feed into the host institute's current industrial collaboration with Vestas Wind Systems, who have agreed to provide the data and technical support required to maximise research impact.
Key Findings
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Potential use in non-academic contexts
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Project URL:
Further Information:
Organisation Website:	http://www.shef.ac.uk