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@Article{LimaGueFrePanMat:2017:MeMoSh,
               author = "Lima, Jo{\~a}o Marcos and Guetter, Alexandre K. and Freitas, 
                         Saulo R. and Panetta, Jairo and Mattos, Jo{\~a}o Gerd Zell de",
          affiliation = "{Copel Gera{\c{c}}{\~a}o e Transmiss{\~a}o S.A} and 
                         {Universidade Federal do Paran{\'a} (UFPR)} and {USRA/GESTAR at 
                         NASA/GFSC} and {Instituto Tecnol{\'o}gico de Aeron{\'a}utica 
                         (ITA)} and {Instituto Nacional de Pesquisas Espaciais (INPE)}",
                title = "A meteorological–statistic model for short-term wind power 
                         forecasting",
              journal = "Journal of Control, Automation and Electrical Systems",
                 year = "2017",
               volume = "28",
               number = "5",
                pages = "679--691",
                month = "Oct.",
             keywords = "Wind power forecast · Numerical weather prediction models · Kalman 
                         filtering · Power curve.",
             abstract = "The problem of wind power forecasting is addressed in this work, 
                         considering a combination of a numerical weather prediction model 
                         (NWP) and statistical models. Brazilian developments on the 
                         Regional Atmospheric Modeling System is employed in two different 
                         areas in Brazil to simulate forecasts of 72 h ahead of the wind 
                         speed, at each 10 min. In one of the areas studied, the wind speed 
                         is converted into wind power. Different conversion methods are 
                         employed and discussed. Kalman filtering techniques are employed 
                         to reduce systematic error of the forecasts, both wind and 
                         generation. Each 72-h period of the NWP simulations had a 
                         computational time of approximately 6070 min using indicating that 
                         the proposed method can be applied in real time for power system 
                         operation. The results obtained are very encouraging for further 
                         investigation to achieve more accurate wind power researches.",
                  doi = "10.1007/s40313-017-0329-8",
                  url = "http://dx.doi.org/10.1007/s40313-017-0329-8",
                 issn = "21953880 and 21953899",
             language = "en",
           targetfile = "lima_meteorological.pdf",
        urlaccessdate = "05 dez. 2020"
}


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