Harrison, Gareth

Wallace, Robin

Hawkins, Samuel Lennon

Engineering and Physical Sciences Research Council (EPSRC)

2013-10-17T10:47:34Z

2013-10-17T10:47:34Z

2012-11-29

The UK has highly ambitious targets for wind development, particularly offshore, where over 30GW of capacity is proposed for development. Integrating such a large amount of variable generation presents enormous challenges. Answering key questions depends on a detailed understanding of the wind resource and its temporal and spatial variability. However, sources of wind speed data, particularly offshore, are relatively sparse: satellite data has low temporal resolution; weather buoys and met stations have low spatial resolution; while the observations from ships and platforms are affected by the structures themselves. This work uses a state-of-the art mesoscale atmospheric model to produce a new high-resolution wind speed dataset over the British Isles and surrounding waters. This covers the whole region at a resolution of 3km for a period of eleven consecutive years, from 2000 to 2010 inclusive, and is thought to be the first high resolution re-analysis to represent a true historic time series, rather than a statistically averaged climatology. The results are validated against observations from met stations, weather buoys, offshore platforms and satellite-derived wind speeds, and model bias is reduced offshore using satellite derived wind speeds. The ability of the dataset to predict power outputs from current wind farms is demonstrated, and the expected patterns of power outputs from future onshore and offshore wind farms are predicted. Patterns of wind production are compared to patterns of electricity demand to provide the first conclusive combined assessment of the ability of future onshore and offshore wind generation meet electricity demand and contribute to secure energy supplies.

http://hdl.handle.net/1842/7898

en

The University of Edinburgh

Hawkins, S., Eager, D., and Harrison, G. (2011). Characterising the reliability of production from future British offshore wind fleets. In Proceedings of the 1st IET Renewable Power Generation Conference. IET, Edinburgh.

mesoscale

wind integration

WRF

Weather Research and Forecast

renewable

High resolution reanalysis of wind speeds over the British Isles for wind energy integration

Thesis or Dissertation

Doctoral

PhD Doctor of Philosophy