Open AccessEvaluating the Global Forecast System (GFS) for energy management over Minas Gerais State (Brazil) against in-situ observations
Author(s) -
Rafael Arcanjo de Oliveira Filho,
Vanessa Silveira Barreto Carvalho,
Michelle Simões Reboita
Publication year - 2022
Publication title -
atmósfera
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.344
H-Index - 29
eISSN - 2395-8812
pISSN - 0187-6236
DOI - 10.20937/atm.52916
Subject(s) - renewable energy , environmental science , wind power , context (archaeology) , meteorology , wind speed , hydropower , hydroelectricity , climatology , geography , engineering , geology , archaeology , electrical engineering
Several regions of Brazil have experienced periods of intense drought in the last decades. Hydropower plants produce most of the country’s energy and a reduction in reservoir flow can compromise the energy sector. Therefore, the Brazilian government has sought the diversification of energy production with other renewable sources. The introduction of new renewable sources, such as wind and solar, requires detailed studies of the local weather conditions usually through historical data analysis. However, several areas in Brazil lack weather stations. In this context, this study aims to assess the ability of the Global Forecast System (GFS) reanalysis product to represent wind, in the state of Minas Gerais (MG) which has 79.5% of energy production associated with water resources. Although the study considers a specific region, it presents a methodology that can be replicated in regions where data is not available. Over most areas, 10 m wind speed values of the GFS reanalysis were similar to those registered by weather stations. Results at 10 and 100 m of altitude show high wind speed values in the north of the state, a region where the highest power densities are also recorded (approximately 150 W m–2 during winter and spring). In conclusion, the GFS reanalysis product, albeit with the biases reported here, can be used in regions with scarce meteorological data to estimate the potential for wind energy production as a complementary source of hydroelectricity.