Encontro de Energia no Meio Rural

Resumen

LIBERMAN, Bernardo, BATISTA, Vicente Teixera y OCACIA, Gilnei Carvalho. Estimativa de velocidade média do vento a partir de dados de estações meteorológicas com três registros diários. In Anales del 4º Encontro de Energia no Meio Rural, 2002, Campinas (SP) [online]. 2002 [citado 07 Mayo 2024]. Disponible en: <http://www.proceedings.scielo.br/scielo.php?script=sci_arttext&pid=MSC0000000022002000100066&lng=es&nrm=iso> .

There is a network of 22 agricultural weather stations in Rio Grande do Sul - a southern Brazilian State. They present extensive historical series of climatic/weather data, such as wind direction and wind speed daily measured at 9:00 a.m., 3 p.m., and 9:00 p.m. The estimate of local monthly, quarterly or annual average of the wind speed, obtained from the data, leads to overestimated values, since none of these measurements occur during the night when average wind speed is less intense. In order to minimize that error, one proposes a new method of estimating the average local wind speed based on the estimate of the wind speed at 3:00 a.m. To do this one take into account the gradients between 3:00 p.m. and 9:00 p.m., as well as between 3:00 p.m. and 9:00 a.m. Average speed is considered as a combination of the values obtained from two extrapolations. The contribution of the first value is taken as α (between 0 and 1) and from the second one as 1- α. This method was validated against the results from 10 anemological stations in the coastal plain of Rio Grade do Sul. In this region, using α as 0.5, the results were considered satisfactory. For values of annual average speed, the average error was 1.7%; minimum error, 0.5%; and maximum error, 3.6 %. The average error pointed out by the use of arithmetic average only of the measurements in the three moments of the historical series was 6.8 %, being 2.6%, the minimum error and 9.7%, the maximum error. For periods of one or three months, the method also presents satisfactory results. However, it is not adapted to calculate the daily averages.

Palabras llave : Velocidade do vento; planície costeira; energia eólica.