Coastal Wind Power in Southern Santa Catarina, Brazil

César Henrique Mattos Pires, Felipe M. Pimenta, Carla A. D'Aquino, Osvaldo R. Saavedra, Xuerui Mao and Arcilan T. Assireu
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César Henrique Mattos Pires: Centro de Ciências Físicas e Matemáticas, Programa de Pós-Graduação em Oceanografia, Campus Trindade, Universidade Federal de Santa Catarina, Florianópolis, SC 88010-970, Brazil
Felipe M. Pimenta: Centro de Ciências Físicas e Matemáticas, Programa de Pós-Graduação em Oceanografia, Campus Trindade, Universidade Federal de Santa Catarina, Florianópolis, SC 88010-970, Brazil
Carla A. D'Aquino: Departamento de Energia e Sustentabilidade, Centro de Ciências, Tecnologias e Saúde, Unidade Jardim das Avenidas, Campus Araranguá, Universidade Federal de Santa Catarina, Araranguá, SC 88906-072, Brazil
Osvaldo R. Saavedra: Instituto de Energia Elétrica, Universidade Federal do Maranhão, Av. dos Portugueses s/n, Bacanga, São Luís, MA 65080-040, Brazil
Xuerui Mao: Faculty of Engineering, University Park, Room B109 Coates Building, Nottingham NG7 2RD, UK
Arcilan T. Assireu: Instituto de Recursos Naturais, Universidade Federal de Itajubá, Av. BPS 1303, Pinheirinho, Itajubá, MG 37500-903, Brazil

Energies, 2020, vol. 13, issue 19, 1-23

Abstract: A light detection and ranging (LIDAR) wind profiler was used to estimate the wind speed in the southern coast of Santa Catarina State, Brazil. This profiler was installed on a coastal platform 250 m from the beach, and recorded wind speed and direction from January 2017 to December 2018. The power generation from three wind turbines was simulated, to obtain estimations of the average power, energy generation and capacity factor, as well as to assess the performance of a hypothetical wind farm. The scale and shape parameters of the Weibull distribution were evaluated and compared with those of other localities in the state. The prevailing winds tend to blow predominantly from the northeast and southwest directions. Wind magnitudes are higher for the NE and SW ocean sectors where the average wind power density can reach 610–820 W m −2 . The Vestas 3.0 turbine spent the largest percentage of time in operation (>76%). The higher incidence of strong northeasterly winds in 2017 and more frequent passage of cold fronts in 2018 were attributed to the cycle of the South Atlantic subtropical high. The results demonstrate a significant coastal wind power potential, and suggest that there is a significant increase of resources offshore.

Keywords: wind power; LIDAR; coastal platform; offshore wind energy; Southern Brazil; Santa Catarina; South Atlantic subtropical high (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

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