Wind Turbine Gust Prediction

Completed

Renewable Energy Sources(Wind Energy)

Basic and strategic applied research

PHYSICAL SCIENCES AND MATHEMATICS (Physics)
ENGINEERING AND TECHNOLOGY (Electrical and Electronic Engineering)
ENVIRONMENTAL SCIENCES (Earth Systems and Environmental Sciences)

Not Cross-cutting

Dr BL Jones
Automatic Control and Systems Engineering
University of Sheffield

Standard

EPSRC

01 March 2013

30 April 2014

14 months

£98,611

Energy

Yorkshire & Humberside

Energy : Engineering

Dr BL Jones, Automatic Control and Systems Engineering, University of Sheffield

Project Contact, Vestas Wind Systems A/S, Denmark

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

26/09/13