Using the WRF numerical model for the purpose of generation eolioelÃtrica: case study for MaracanaÃ, CearÃ.

• Autor(a) principal: Camylla Maria Narciso de Melo
• Data de Publicação: 2013
• Tipo de documento: Dissertação
• Idioma: por
• Título da fonte: Biblioteca Digital de Teses e Dissertações da UFC
• Texto Completo: http://www.teses.ufc.br/tde_busca/arquivo.php?codArquivo=14606
• topic: Modelagem atmosfÃrica; WRF; Wind energy; Atmospheric Modeling; WRF; ENGENHARIA ELETRICA

This paper analyzes the mesoscale model WRF (Weather Research And Forecast) to verify its reliability in use as a research tool in areas with potential for eolioeletric generation. The area chosen for study was a farm located in Maracanaà in the state of CearÃ. On the farm was installed an anemometer tower of 80 meters high with three anemometers, 1 windsock, 1 temperature sensor and a pyranometer, all sensors connected to a datalogger. The data collected in this tower were used for comparison with the data obtained through simulations in WRF. In the simulations the model was evaluated for two different climatic conditions in the region, the rainy and the dry seasons. The periods chosen to perform the simulations are: March/2012 (representing the rainy season) and November/2011 (representing the dry season). Was performed five sensitivity tests, which were exchanged in the parameterizations of the Planetary Boundary Layer (PBL), Surface Layer (CS) and Ground Surface Model (GSM). The simulation results were evaluated according to the Pearson's correlation method, that one has parameter values from -1 to 1 which presents an index of correlations ranging from bad (-1) to great (1). The simulation with the best performance in the dry and rainy periods presented values for correlations of 0.76 and 0.58, respectively, considered good and fair to the Pearson's parameters. The model was able to satisfactorily represent the local wind behavior for the dry season of the year, and more research is needed in the area to analyze how the model behaves in the representation of the rainy season. Thus, this model provides satisfactory results to be used as a tool for evaluate areas with potential for eolioeletric generation, more research is needed to fit better.