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A temporal model for vertical extrapolation of wind speed and wind energy assessment.

Authors :
Crippa, Paola
Alifa, Mariana
Bolster, Diogo
Genton, Marc G.
Castruccio, Stefano
Source :
Applied Energy. Nov2021, Vol. 301, pN.PAG-N.PAG. 1p.
Publication Year :
2021

Abstract

• A temporal model to extrapolate hourly winds to turbine hub height is proposed. • The proposed model outperforms traditional vertical extrapolation methods. • A time-varying variance model improves extrapolation for stable/unstable regimes. • The temporal model reduces the absolute bias in capacity factors by 58–64%. Accurate wind speed estimates at turbine hub height are critical for wind farm operational purposes, such as forecasting and grid operation, but also for wind energy assessments at regional scales. Power law models have widely been used for vertical wind speed profiles due to their simplicity and suitability for many applications over diverse geographic regions. The power law requires estimation of a wind shear coefficient, α, linking the surface wind speed to winds at higher altitudes. Prior studies have mostly adopted simplified models for α, ranging from a single constant, to a site-specific constant in time value. In this work we (i) develop a new model for α which is able to capture hourly variability across a range of geographic/topographic features; (ii) quantify its improved skill compared to prior studies; and (iii) demonstrate implications for wind energy estimates over a large geographical area. To achieve this we use long-term high-resolution simulations by the Weather Research and Forecasting model, as well as met-mast and radiosonde observations of vertical profiles of wind speed and other atmospheric properties. The study focuses on Saudi Arabia, an emerging country with ambitious renewable energy plans, and is part of a bigger effort supported by the Saudi Arabian government to characterize wind energy resources over the country. Results from this study indicate that the proposed model outperforms prior formulations of α, with a domain average reduction of the wind speed RMSE of 23–33%. Further, we show how these improved estimates impact assessments of wind energy potential and associated wind farm siting. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
03062619
Volume :
301
Database :
Academic Search Index
Journal :
Applied Energy
Publication Type :
Academic Journal
Accession number :
152187275
Full Text :
https://doi.org/10.1016/j.apenergy.2021.117378