DocumentCode :
1765694
Title :
Low-cost wind resource assessment for small-scale turbine installations using site pre-screening and short-term wind measurements
Author :
Weekes, Shemaiah Matthias ; Tomlin, Alison S.
Author_Institution :
Doctoral Training Centre in Low Carbon Technol., Univ. of Leeds, Leeds, UK
Volume :
8
Issue :
4
fYear :
2014
fDate :
41760
Firstpage :
348
Lastpage :
358
Abstract :
A two-stage approach to low-cost wind resource assessment for small-scale wind installations has been investigated in terms of its ability to screen for non-viable sites and to provide accurate wind power predictions at promising locations. The approach was implemented as a case study at ten UK locations where domestic-scale turbines were previously installed. In stage one, sites were pre-screened using a boundary-layer scaling model to predict the mean wind power density, including estimated uncertainties, and these predictions were compared to a minimum viability criterion. Using this procedure, five of the seven non-viable sites were correctly identified without direct onsite wind measurements and none of the viable sites were excluded. In stage two, more detailed analysis was carried out using 3 months onsite wind measurements combined with measure-correlate-predict (MCP) approaches. Using this process, the remaining two non-viable sites were identified and the available wind power density at the three viable sites was accurately predicted. The effect of seasonal variability on the MCP-predicted wind resource was considered and the implications for financial projections were highlighted. The study provides a framework for low-cost wind resource assessment in cases where long-term onsite measurements may be too costly or impractical.
Keywords :
boundary layers; wind; wind power; wind turbines; MCP approach; boundary layer scaling model; domestic scale turbines; mean wind power density prediction; measure-correlate-predict; nonviable sites identification; onsite wind measurements; site prescreening; small-scale turbine installation; uncertainty estimation; wind power prediction accuracy; wind resource assessment;
fLanguage :
English
Journal_Title :
Renewable Power Generation, IET
Publisher :
iet
ISSN :
1752-1416
Type :
jour
DOI :
10.1049/iet-rpg.2013.0152
Filename :
6809366
Link To Document :
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