@Article{JacondinoNaCaFiBePa:2021:HoDaWi,
               author = "Jacondino, William Duarte and Nascimento, Ana L{\'u}cia da Silva 
                         and Calvetti, Leonardo and Fisch, Gilberto Fernando and Beneti, 
                         Cesar Augustus Assis and Paz, Sheila Radman da",
          affiliation = "{Universidade Federal de Pelotas (UFPel)} and {Instituto Nacional 
                         de Pesquisas Espaciais (INPE)} and {Universidade Federal de 
                         Pelotas (UFPel)} and {Instituto Nacional de Pesquisas Espaciais 
                         (INPE)} and {Sistema Meteorologico Do Paran a (SIMEPAR)} and 
                         {Sistema Meteorologico Do Paran a (SIMEPAR)}",
                title = "Hourly day-ahead wind power forecasting at two wind farms in 
                         northeast Brazil using WRF model",
              journal = "Energy",
                 year = "2021",
               volume = "230",
                pages = "e120841",
                month = "Sept.",
             keywords = "WRF, Onshore, Forecast, Wind power, Brazil.",
             abstract = "Wind energy is rapidly growing industry in Brazil. Wind speed 
                         forecasting is necessary in the planning, controlling, and 
                         monitoring for the reliable and efficient operation of the wind 
                         power systems. Thus, this study focuses on the impact of different 
                         physics parameterization in forecasting wind speed in two onshore 
                         wind farms using the Weather and Research Forecasting (WRF) model. 
                         The wind farms are located in Parazinho, in the northeast of 
                         Brazil, a region with high wind resource. Hindcasts are performed 
                         for a high (i.e., July 2017) and low (i.e., April 2017) wind speed 
                         regimes using different forecast lead-times (i.e., 2448 h). The 
                         best performing setup consists of Thompson microphysics, 
                         Bougeault-Lacarrere PBL, Betts-Miller cumulus, New Goddard 
                         Longwave/Shortwave radiation, and Pleim-Xiu Land Surface schemes. 
                         Our findings also suggest that the model forecast setting with the 
                         TKE closure scheme, namely BouLac, performed better than that 
                         setting with first-order closure ACM2. The best mean monthly error 
                         (MAE) obtained is 1.1 m s\−1 for wind and 12.6% for wind 
                         power.",
                  doi = "10.1016/j.energy.2021.120841",
                  url = "http://dx.doi.org/10.1016/j.energy.2021.120841",
                 issn = "0360-5442",
             language = "en",
           targetfile = "jacondino_hourly.pdf",
        urlaccessdate = "04 maio 2024"
}