Evaluation of wind potential in a region of southern Brazil


  • Alisson Nascimento Universidade Federal de Santa Maria - campus Cachoeira do Sul
  • Silvana Maldaner Universidade Federal de Santa Maria - campus Cachoeira do Sul
  • Vinicius Maran Universidade Federal de Santa Maria - campus Cachoeira do Sul https://orcid.org/0000-0003-1916-8893
  • Gervásio Annes Degrazia Universidade Federal de Santa Maria, RS
  • Débora Regina Roberti Universidade Federal de Santa Maria, RS
  • Virnei Silva Moreira Departamento de Engenharia - Universidade Federal do Pampa - Campus Itaqui
  • Marcelo Bortoluzzi Diaz Universidade Federal de Santa Maria, RS
  • Michel Baptistella Stefanello Universidade Federal de Santa Maria, RS
  • Umberto Rizza The Institute of Atmospheric Sciences and Climate




Wind potential, Wind speed, Weibull probability distribution


Knowledge of wind behavior plays a key role in the production of wind energy, in ambient ventilation and in air quality. In this study the wind speed behavior in Cachoeira do Sul (RS) is analyzed. Wind speed data was measured by a sonic anemometer and it was used to estimate the potential for power generation in the period from 2010 to 2014. One of the methodologies used for the study of wind was the statistical analysis using functions of probability density. There are several models of probability distribution in the literature for time series of data. For wind data, the most commonly used distribution is the Weibull function.
This distribution is considered to be the most adequate for wind characterization and is also applied in the analysis of rainfall data,
clarity index, water level prediction, among other applications. Thus, the objective of the present study is to obtain preliminary estimates of the wind potential of Cachoeira do Sul (RS) using the Weibull probability distribution to estimate the wind power. The results show that wind power is below 500W=m2 (in 50 m) which indicates low wind potential.


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Amarante, O. A. e. (2001). Atlas do potencial eólico brasileiro.

ANEEL. Agência Nacional de Energia Elétrica (2017). Big – banco de informações de geração. URL http://www2.aneel.


CHANG, T. P. (2011). Performance comparison of six numerical methods in estimating weibull parameters for wind energy

application. Applied Energy, 88, 272–282.

DALMAZ, A. (2007). Estudo do potencial eólico e previsão de ventos para geração de eletricidade em santa catarina. Doutorado

em engenharia mecânica, Universidade Federal de Santa Catarina, Florianópolis.

Johansson, T. B., Burnham, L. (1993). Renewable energy: sources for fuels and electricity. Island press.

JUSTUS, A., C. G.; MIKHAIL (1976). Height variation of wind speed and wind distributions statistics. Geophysical Research

Letters, 3, 261–264.

KWON, S. D. (2010). Uncertainty analysis of wind energy potential assessment. Applied Energy, 87, 856–86.

Pishgar-Komleh, A. K., S. H., Sefeedpari., P. (2015). Wind speed and power density analysis based on weibull and rayleigh

distributions (a case study: Firouzkooh county of iran). Renewable and Sustainable Energy Reviews, 42, 313–322.

RAMÍREZ, J. A., Penélope; CARTA (2005). Influence of the data sampling interval in the estimation of the parameters of the

weibull wind speed probability density distribution: a case study. Energy Conversion and Management, 46, 2419–2438.

SENA, J. e. a. (2011). Análise das componentes do balanço energético numa lavoura de arroz irrigado. Ciência e Natura, ed.

especial., 143–146.

TAR, K. (2008). Some statistical characteristics of monthly average wind speed at various heights. Renewable and Sustainable

Energy Reviews, 12, 1712–1724.



How to Cite

Nascimento, A., Maldaner, S., Maran, V., Degrazia, G. A., Roberti, D. R., Moreira, V. S., Diaz, M. B., Stefanello, M. B., & Rizza, U. (2018). Evaluation of wind potential in a region of southern Brazil. Ciência E Natura, 40, 100–106. https://doi.org/10.5902/2179460X30711

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