Análise do Potencial de Previsão da Velocidade do Vento Utilizando Rede Neural Artificial

Santos, Iwldson Guilherme da Silva; Lyra, Roberto Fernando da Fonseca

doi:10.11137/2020_4_11_17

Anu. Inst. Geoc.

2020

DOI: 10.11137/2020_4_11_17

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Análise do Potencial de Previsão da Velocidade do Vento Utilizando Rede Neural Artificial

Iwldson Guilherme da Silva Santos

Roberto Fernando da Fonseca Lyra

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2022

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Performance of the WRF Model in the Wind Speed Simulation in the Semiarid Region of Northeast Brazil

Santos

Lyra

Júnior

et al. 2022

Preprint

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This study aimed to evaluate the performance of the Weather Research and Forecasting (WRF) mesoscale model in the simulation of wind speed in the semiarid region of Northeast Brazil (NEB). The accuracy of the simulations was determined by comparing between forecast (WRF) and observed (OBS) values with an average every 10 minutes. The measurements were made in a 100 m high anemometric tower during the execution of the Project Previsão do Vento em Parques Eólicos do Nordeste Brasileiro – PVPN. The tower was installed in a flat semiarid location in Craíbas, Alagoas - NEB. The period analyzed was five months (2015/03/01 to 2015/07/31). The analysis was performed using descriptive statistics (DS) including central and dispersion measures; bivariate statistics (BS) that includes the correlations (Pearson, Kendall and Spearman) with a t-Student hypothesis test to verify the representativeness of the correlations, and errors statistics (ES) with equations to verify the effectiveness of the simulation; Simple Linear Regression (SLR); Normal and Weibull probability density function (PDF); Principal Component Analysis (PCA). In addition to the temporal assessment of wind speed, temporal distribution of the average daily cycle (ADC), boxplot, scatterplot (1:1) and relative frequency distribution. The results showed that the simulation made by the WRF model reproduced well the daily temporal evolution of the wind in the studied period with a small tendency of underestimation. These results indicate the potential of the WRF model in the modeling of wind speed for the region studied and can contribute to the production of wind energy.

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Performance of the WRF Model in the Wind Speed Simulation in the Semiarid Region of Northeast Brazil

Santos

Lyra

Júnior

et al. 2022

Preprint

Self Cite

View full text Add to dashboard Cite

show abstract

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Análise do Potencial de Previsão da Velocidade do Vento Utilizando Rede Neural Artificial

Cited by 1 publication

References 5 publications

Performance of the WRF Model in the Wind Speed Simulation in the Semiarid Region of Northeast Brazil

Performance of the WRF Model in the Wind Speed Simulation in the Semiarid Region of Northeast Brazil

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Análise do Potencial de Previsão da Velocidade do Vento Utilizando Rede Neural Artificial

Cited by 1 publication

References 5 publications

Performance of the WRF Model in the Wind Speed ​​Simulation in the Semiarid Region of Northeast Brazil

Performance of the WRF Model in the Wind Speed ​​Simulation in the Semiarid Region of Northeast Brazil

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Performance of the WRF Model in the Wind Speed Simulation in the Semiarid Region of Northeast Brazil

Performance of the WRF Model in the Wind Speed Simulation in the Semiarid Region of Northeast Brazil