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Reference Number GR/N37308/01
Status Completed
Energy Categories RENEWABLE ENERGY SOURCES(Wind Energy) 100%;
Research Types Basic and strategic applied research 80%;
Applied Research and Development 20%;
Science and Technology Fields PHYSICAL SCIENCES AND MATHEMATICS (Physics) 30%;
PHYSICAL SCIENCES AND MATHEMATICS (Statistics and Operational Research) 20%;
PHYSICAL SCIENCES AND MATHEMATICS (Computer Science and Informatics) 10%;
ENGINEERING AND TECHNOLOGY (Mechanical, Aeronautical and Manufacturing Engineering) 10%;
UKERC Cross Cutting Characterisation Not Cross-cutting 100%
Principal Investigator Dr JA (Jim ) Halliday
No email address given
Energy Research Unit
STFC (Science & Technology Facilities Council)
Award Type Standard
Funding Source EPSRC
Start Date 25 June 2001
End Date 24 June 2004
Duration 36 months
Total Grant Value £162,568
Industrial Sectors Energy; Environment
Region South East
Programme Materials, Mechanical and Medical Eng, Process Environment and Sustainability
Investigators Principal Investigator Dr JA (Jim ) Halliday , Energy Research Unit, STFC (Science & Technology Facilities Council) (100.000%)
  Industrial Collaborator Project Contact , Unit Energy Ltd (0.000%)
Web Site
Abstract The exploitation of the UK's large onshore and offshore wind energy resource has been identified as an important part of the Government's Renewable Energy Policy. As wind energy is highly variable, accurate wind forecasting on the timescale of a few hours is required for wind energy to compete effectively under the likely form of the New Energy Trading Arrangements (NETA). The project therefore aims to develop new methods for the improved prediction of wind power production inthe UK. The development will concentrate on improving short-term predictive methods based on statistical analysis of wind speed and power time series data relevant to onshore sites to address the current needs of the wind energy industry. These techniques will be extended to prediction of wind power at offshore sites. The value of longer-range wind power forecasting based on the latest numerical weather prediction models in facilitating future large-scale integration of wind energy in the UKnational grid will also be assessed. An economic evaluation of the methods for short-range onshore power prediction using a simple price forecasting model will be made. Finally a Windows-based software package to aid UK wind energy suppliers in formulating their trading strategies, will be written.EngProg\
Publications (none)
Final Report (none)
Added to Database 01/06/07