Verlag:
Instituto de Pesquisa Econômica Aplicada, Brasília
Wind power generation is essential to reduce the use of fossil resources and, consequently, the emission of greenhouse gases (GHG). Currently, the National Interconnected System (SIN) has about 9971 wind turbines in operation, the sixth largest...
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ZBW - Leibniz-Informationszentrum Wirtschaft, Standort Kiel
Signatur:
DS 194
Fernleihe:
keine Fernleihe
Wind power generation is essential to reduce the use of fossil resources and, consequently, the emission of greenhouse gases (GHG). Currently, the National Interconnected System (SIN) has about 9971 wind turbines in operation, the sixth largest network in the world ranking, and 80% of Brazilian wind parks are located in the Northeast. However, due to the intermittency of wind generation, the large-scale entry of the wind source in the planning of hydrothermal systems implies challenges for its integration into the system. For this reason, there is a need to treat wind speed uncertainty in the chain of computational models that support operational decisions. Thus, in order to contribute to the modeling of wind uncertainty in the operation planning (medium term), this paper proposes a methodology that consists of the application of the dynamic factorial model (DFM) for the generation of synthetic series of monthly averages of wind speed in locations with wind farms. The proposed methodology is applied to a set of wind speed reanalysis series from MERRA-2. The results obtained for the eight wind farms of the SIN analyzed show that the methodology is promising, given the good quality of the monthly average wind speed forecasts up to 2 years ahead and, above all, the good representativeness of the synthetic series generated by the model.
