Analysis of the wind average speed in different Brazilian states using the nested GR&R measurement system

•Wind power has exponentially grown in the Brazilian electric power matrix.•Wind stations at four Brazilian states have been assessed as a measurement system.•Nested analysis of variance has calculated repeatability and reproducibility variations.•Repeatability due to the wind speed range by state b...

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Veröffentlicht in:Measurement : journal of the International Measurement Confederation 2018-02, Vol.115, p.217-222
Hauptverfasser: Aquila, Giancarlo, Peruchi, Rogério Santana, Rotela Junior, Paulo, Rocha, Luiz Célio Souza, Queiroz, Anderson Rodrigo de, Pamplona, Edson de Oliveira, Balestrassi, Pedro Paulo
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Sprache:eng
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Zusammenfassung:•Wind power has exponentially grown in the Brazilian electric power matrix.•Wind stations at four Brazilian states have been assessed as a measurement system.•Nested analysis of variance has calculated repeatability and reproducibility variations.•Repeatability due to the wind speed range by state by month was significant.•Reproducibility due to wind mean speed between states was also relevant. Brazil presents remarkable potential for wind power generation. This study aims to evaluate the behavior of wind average speed at the four major wind energy-producing states. The main contribution of this research is to use the NGR&R study (Nested Gage Repeatability & Reproducibility), generally applied on manufacturing quality management. Wind average speeds were collected for each month in four states, between the years of 2012 and 2015. Seasonality impact, measurements recurrence over the years and difference between states on wind average speed were assessed in this research. Time series, boxplot and control charts have been used to investigate not only wind average speed between months and states, but also range variation for each state by month. Study results show that the impact of these three factors is statistically significant and that the different location of these states presents the most relevant impact to wind mean speed variation in the country.
ISSN:0263-2241
1873-412X
DOI:10.1016/j.measurement.2017.10.048