Predicting Small Wind Turbine Performance using Remote Wind Data
Abstract
Wind maps are typically used to predict the performance of small wind turbine systems such as 10 kW units which are sized for single rural residences. The general nature of the wind maps may negatively impact the reliability of wind turbine performance predictions. Multi-million dollar wind farms rely on multi-year siting studies to characterize wind velocity. However such siting studies are probably cost-prohibitive compared to the cost of a small wind turbine system which is on the order of $50,000 installed. The use of non site-specific wind velocity data such as that available from a regional database may be a cost effective means for predicting wind turbine performance. Regional climate databases collect wind velocity from widely-scattered weather stations, and an obvious drawback to engineers interested in using this data is that it is likely that the weather stations will not be co-located with the desired wind turbine location. Monte Carlo models were developed to compare wind turbine performance predictions calculated using remote wind velocity data downloaded from a regional climate database to actual wind turbine performance at a Nebraska Superfund site.
Recommended Citation
A. C. Elmore and R. Gallagher, "Predicting Small Wind Turbine Performance using Remote Wind Data," Proceedings of the World Environmental and Water Resources Congress (2008, Honolulu, HI), vol. 316, American Society of Civil Engineers (ASCE), May 2008.
The definitive version is available at https://doi.org/10.1061/40976(316)635
Meeting Name
World Environmental and Water Resources Congress (2008: May 12-16, Honolulu, HI)
Department(s)
Geosciences and Geological and Petroleum Engineering
Keywords and Phrases
Data analysis; Hydraulic properties; Predictions; Co-located; Cost-effective means; General nature; Monte Carlo model; Nebraska; Regional climate; Site-specific; Small wind turbine; Superfund sites; Turbine performance; Weather stations; Wind data; Wind farm; Wind maps; Wind turbine performance predictions; Wind velocities
International Standard Book Number (ISBN)
978-0784409763
Document Type
Article - Conference proceedings
Document Version
Citation
File Type
text
Language(s)
English
Rights
© 2008 American Society of Civil Engineers (ASCE), All rights reserved.
Publication Date
01 May 2008
