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A study into the accuracy of using meteorological wind data to estimate turbine generation output

Kubik, M. L., Coker, P. J., Barlow, J. F. and Hunt, C. (2013) A study into the accuracy of using meteorological wind data to estimate turbine generation output. Renewable Energy, 51. pp. 153-158. ISSN 0960-1481

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To link to this item DOI: 10.1016/j.renene.2012.08.084


Meteorological (met) station data is used as the basis for a number of influential studies into the impacts of the variability of renewable resources. Real turbine output data is not often easy to acquire, whereas meteorological wind data, supplied at a standardised height of 10 m, is widely available. This data can be extrapolated to a standard turbine height using the wind profile power law and used to simulate the hypothetical power output of a turbine. Utilising a number of met sites in such a manner can develop a model of future wind generation output. However, the accuracy of this extrapolation is strongly dependent on the choice of the wind shear exponent alpha. This paper investigates the accuracy of the simulated generation output compared to reality using a wind farm in North Rhins, Scotland and a nearby met station in West Freugh. The results show that while a single annual average value for alpha may be selected to accurately represent the long term energy generation from a simulated wind farm, there are significant differences between simulation and reality on an hourly power generation basis, with implications for understanding the impact of variability of renewables on short timescales, particularly system balancing and the way that conventional generation may be asked to respond to a high level of variable renewable generation on the grid in the future.

Item Type:Article
Divisions:Interdisciplinary centres and themes > Centre for Technologies for Sustainable Built Environments (TSBE)
Interdisciplinary centres and themes > Energy Research
Science > School of Mathematical, Physical and Computational Sciences > Department of Meteorology
Science > School of the Built Environment > Energy and Environmental Engineering group
ID Code:29885

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