Estimating Wind Speed And Capacity Factors In Mexico Using Reanalysis Data

In the fundamental stage of resource assessment, high-quality wind speed measurements are required to estimate power production. However, this high-quality data is not always available, and therefore the analysis of alternative sources becomes essential. In this work, we analyze the ability of MERRA-2 to represent wind speed characteristics at 24 anemometric stations in Mexico. The assessment was carried out using the Pearson correlation coefficient between the observed time series, and the obtained by interpolating bias-corrected reanalysis-estimated wind speed to all locations for different time-averaging periods. Results showed that the reanalysis' performance is not uniform throughout the country; it depends on the time resolution, local orographic conditions, and the relationship between the local flow and the large-scale circulation. Based on these results, the country was subdivided into eight regions. The best-represented region was the Chivela Pass, where the winds are tightly linked to the interaction between the large-scale circulation and the local orography. The worst performing regions were located where the land sea-mask and orography at the reanalysis resolution may not be accurate enough to reproduce the station's wind speeds. Reanalysis-estimated capacity factors exhibit large interannual variability in some stations, which can have significant consequences for the operation of individual wind farms and the power grid. The results show that, while caution should be exercised when applying reanalyses to wind resource assessment in Mexico, reanalysis wind power estimates can be a valuable tool to investigate the feasibility and installed capacity requirements for Mexico to meet its renewable energy targets. (C) 2020 International Energy Initiative. Published by Elsevier Inc. All rights reserved.