Accessibility navigation


Effects of wind power spectrum analysis over resource assessment

Lopez-Villalobos, C. A., Rodriguez-Hernandez, O., Martinez-Alvarado, O. ORCID: https://orcid.org/0000-0002-5285-0379 and Hernandez-Yepes, J. G. (2021) Effects of wind power spectrum analysis over resource assessment. Renewable Energy, 167. pp. 761-773. ISSN 0960-1481

[img]
Preview
Text - Accepted Version
· Available under License Creative Commons Attribution Non-commercial No Derivatives.
· Please see our End User Agreement before downloading.

6MB

It is advisable to refer to the publisher's version if you intend to cite from this work. See Guidance on citing.

To link to this item DOI: 10.1016/j.renene.2020.11.147

Abstract/Summary

Based on the Van der Hoven's seminal work, wind power industry has adopted the 10 minutes mean time as the proper sampling to estimate resource assessment. However, research within the literature questions the generalization of the 10 minutes as a standard measure of minima dispersion due to the particular geographic characteristics where the measurements took place. In this work the power spectrum of a high-frequency wind speed time series is analyzed and its influence over the resource assessment in the region of La Ventosa, Oaxaca, Mexico. Power spectrum analysis from a monthly, seasonal, and annual time series results show a defined synoptic-scale, diurnal, and semi-diurnal variations, which changes in amplitude throughout the year.To study the influence of power spectrum in wind resource assessment were estimated and compared the capacity factors of a typical 2MW wind turbine against measured wind speed with 1, 5, 10, 60, and 360 minutes mean times, we found that a maximum difference of 1.4 %. Resource assessment was also estimated using reanalysis data and WRF results, finding similar to high-resolution estimations, highlighting bias-corrected WRF performance, offering reliable results to model power performance after a statistical correction.

Item Type:Article
Refereed:Yes
Divisions:Science > School of Mathematical, Physical and Computational Sciences > NCAS
ID Code:94572
Publisher:Elsevier

Downloads

Downloads per month over past year

University Staff: Request a correction | Centaur Editors: Update this record

Page navigation