Influence of input costs and levelised cost of energy on wind power growth

Johnston, Barry; Foley, Aoife; Doran, John; Littler, Timothy; McAleer, Michael

doi:10.1016/j.jclepro.2022.133407

Cited by 6 publications

(1 citation statement)

References 16 publications

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“…With this in mind, we intended to use reanalysis data to obtain an idea of the wind and atmospheric conditions at the sites. This led to the search for new, alternative sources of information that allowed for a preliminary evaluation of the wind resource, in order to reduce uncertainty in the selection of sites and avoid incurring unrecoverable costs [3]. An alternative is the use of reanalysis meteorological data, which are generated from models that take into account the specific characteristics of the atmosphere and the surface, in terms of orography and roughness.…”

Section: Introductionmentioning

confidence: 99%

Microscale Wind Assessment, Comparing Mesoscale Information and Observed Wind Data

et al. 2022

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One of the most common problems in wind resource assessment is that measured data are not always available at the site of interest. That is why, in several studies, reanalysis data have been used as an alternative, which, in some cases, have been validated by measured data. Mexico is no exception, since there are not many measurement towers in the country that provide valid records throughout the country. In view of the above, in this study a comparison was made between the measurements observed in six anemometric towers, located in different locations in the United Mexican States; data from the MERRA-2 and ERA-5 reanalysis; and data from the generalized wind climates (GWC), available in the Global Wind Atlas. The study was conducted at 80 m, which is the highest height at which data were recorded on the measurement towers at each site. In the case of the MERRA-2 and ERA-5 data, extrapolation of the data series to 80 m was required. In the case of the towers, a comparison of the two data sets measured at 80 m and the height at which two anemometers were available, was performed. This analysis was supported by Windographer version 4 software designed by the company UL solutions, from which *.tab files were exported at 80 m, which were then imported from the WAsP 10.0 program to perform the microscale modeling. The comparison variable was the mean power density, for which the relative deviations between the measured values and those obtained from the reanalysis data and the GWCs were determined. For a better interpretation of the relative errors calculated, an analysis of the orographic characteristics of all the sites was performed using the roughness index (RIX). The results obtained showed that the behavior of the reanalysis and the GWC data was not homogeneous in the sites studied; therefore, an adequate relationship between the magnitudes of the ΔRIX and the relative deviations was not observed, especially for the ERA5 and GWC. The ERA5 data were the furthest from the measured data, with relative deviations greater than 50% at five of the six sites; however, the MERRA-2 and GWC data were the closest to the measured data. The MERRA-2 data showed deviations of less than 11%, except at the La Venta site, where it was 29.5%—a site where the GWC also had a high deviation of 139.4%. The latter is attributable to the effects caused by the nearby wind farms on the wind flow measured by the La Venta station. In general, the MERRA-2 data are an alternative to performing a pre-analysis of the wind resource in Mexico.

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Section: Introductionmentioning

confidence: 99%