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A new measure-correlate-predict approach for resource assessment

Abstract

In order to find reasonable candidate site for wind farms, it is of great importance to be able to calculate the wind resource at potential sites. One way to solve this problem is to measure wind speed and direction at the site, and use these measurements to predict the resource. If the measurements at the potential site cover less than e.g. one year, which most likely will be the case, it is not possible to get a reliable estimate of the long-term resource, using this approach. If long-term measurements from e.g. some nearby meteorological station are available, however, then statistical methods can be used to find a relation between the measurements at the site and at the meteorological station. This relation can then be used to transform the long-term measurements to the potential site, and the resource can be calculated using the transformed measurements. Here, a varying-coefficient model, estimated using local regression, is applied in order to establish a relation between the measurements. The approach is evaluated using measurements from two sites, located approximately two kilometres apart, and the results show that the resource in this case can be predicted accurately, although this approach has serious shortcomings. (au)
Authors:
Joensen, A; Landberg, L; [1]  Madsen, H [2] 
  1. Risoe National Lab., Dept. of Wind Energy and Atmospheric Physics, Roskilde (Denmark)
  2. The Technical Univ. of Denmark, Dept. of Mathematical Modelling, Lyngby (Denmark)
Publication Date:
Mar 01, 1999
Product Type:
Conference
Report Number:
RISO-R-1114(EN); CONF-990314-
Reference Number:
SCA: 170100; PA: DK-99:001415; EDB-99:087293; SN: 99002098321
Resource Relation:
Conference: EWEC`99. European wind energy conference, Nice (France), 1-5 Mar 1999; Other Information: PBD: Mar 1999; Related Information: Is Part Of Contributions from the Department of Wind Energy and Atmospheric Physics to EWEC `99 in Nice, France; Larsen, Gunnar C.; Westermann, Kirsten; Noergaard, Per [eds.]; PB: 256 p.
Subject:
17 WIND ENERGY; WIND POWER; RESOURCE ASSESSMENT; SITE CHARACTERIZATION; WIND; STATISTICS
OSTI ID:
679633
Research Organizations:
Risoe National Lab., Roskilde (Denmark). Wind Energy and Atmospheric Physics Dept.
Country of Origin:
Denmark
Language:
English
Other Identifying Numbers:
Other: ON: DE99747779; CNN: Contract JOR3-CT98-0295; ISBN 87-550-2542-0; TRN: DK9901415
Availability:
OSTI as DE99747779
Submitting Site:
DK
Size:
pp. 165-168
Announcement Date:
Oct 15, 1999

Citation Formats

Joensen, A, Landberg, L, and Madsen, H. A new measure-correlate-predict approach for resource assessment. Denmark: N. p., 1999. Web.
Joensen, A, Landberg, L, & Madsen, H. A new measure-correlate-predict approach for resource assessment. Denmark.
Joensen, A, Landberg, L, and Madsen, H. 1999. "A new measure-correlate-predict approach for resource assessment." Denmark.
@misc{etde_679633,
title = {A new measure-correlate-predict approach for resource assessment}
author = {Joensen, A, Landberg, L, and Madsen, H}
abstractNote = {In order to find reasonable candidate site for wind farms, it is of great importance to be able to calculate the wind resource at potential sites. One way to solve this problem is to measure wind speed and direction at the site, and use these measurements to predict the resource. If the measurements at the potential site cover less than e.g. one year, which most likely will be the case, it is not possible to get a reliable estimate of the long-term resource, using this approach. If long-term measurements from e.g. some nearby meteorological station are available, however, then statistical methods can be used to find a relation between the measurements at the site and at the meteorological station. This relation can then be used to transform the long-term measurements to the potential site, and the resource can be calculated using the transformed measurements. Here, a varying-coefficient model, estimated using local regression, is applied in order to establish a relation between the measurements. The approach is evaluated using measurements from two sites, located approximately two kilometres apart, and the results show that the resource in this case can be predicted accurately, although this approach has serious shortcomings. (au)}
place = {Denmark}
year = {1999}
month = {Mar}
}