%0 Journal Article
%@nexthigherunit 8JMKD3MGPCW/3F35TRS
%@nexthigherunit 8JMKD3MGPCW/46KUATE
%3 jacondino_hourly.pdf
%4 sid.inpe.br/mtc-m21c/2021/05.21.18.19
%8 Sept.
%9 journal article
%@issn 0360-5442
%A Jacondino, William Duarte,
%A Nascimento, Ana Lúcia da Silva,
%A Calvetti, Leonardo,
%A Fisch, Gilberto Fernando,
%A Beneti, Cesar Augustus Assis,
%A Paz, Sheila Radman da,
%@secondarytype PRE PI
%B Energy
%D 2021
%K WRF, Onshore, Forecast, Wind power, Brazil.
%@archivingpolicy denypublisher denyfinaldraft24
%P e120841
%@secondarymark A1_INTERDISCIPLINAR A1_GEOGRAFIA A1_GEOCIÊNCIAS A1_ENGENHARIAS_III A1_ENGENHARIAS_I A1_CIÊNCIAS_AMBIENTAIS A1_CIÊNCIA_DE_ALIMENTOS A2_QUÍMICA A2_MEDICINA_II A2_MATERIAIS A2_ENGENHARIAS_IV A2_ENGENHARIAS_II A2_ECONOMIA C_CIÊNCIAS_AGRÁRIAS_I
%T Hourly day-ahead wind power forecasting at two wind farms in northeast Brazil using WRF model
%V 230
%X 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.
%@area MET
%@electronicmailaddress williamjacondinoufpel@gmail.com
%@electronicmailaddress analuciasne@gmail.com
%@electronicmailaddress
%@electronicmailaddress fisch.gilberto@gmail.com
%@documentstage not transferred
%@group
%@group MET-MET-DIPGR-INPE-MCTI-GOV-BR
%@group
%@group MET-MET-DIPGR-INPE-MCTI-GOV-BR
%@dissemination WEBSCI; PORTALCAPES.
%@usergroup simone
%@affiliation Universidade Federal de Pelotas (UFPel)
%@affiliation Instituto Nacional de Pesquisas Espaciais (INPE)
%@affiliation Universidade Federal de Pelotas (UFPel)
%@affiliation Instituto Nacional de Pesquisas Espaciais (INPE)
%@affiliation Sistema Meteorologico Do Paran  a (SIMEPAR)
%@affiliation Sistema Meteorologico Do Paran  a (SIMEPAR)
%@versiontype publisher
%@holdercode {isadg {BR SPINPE} ibi 8JMKD3MGPCW/3DT298S}
%@doi 10.1016/j.energy.2021.120841
%2 sid.inpe.br/mtc-m21c/2021/05.21.18.19.18