TY - GEN
T1 - Validation of GHI and DNI predictions from GFS and MACC model in the middle east
AU - Martin-Pomares, Luis
AU - Polo, Jesus
AU - Perez-Astudillo, Daniel
AU - Bachour, Dunia A.
N1 - Publisher Copyright:
© 2016. The Authors.
PY - 2015
Y1 - 2015
N2 - Production of electricity from solar energy is gaining a tremendous significance. The integration of all solar energy power to the electricity grid challenges new horizons. Mainly, the prediction of short-term power generation to optimise its management, avoid situations of load reduction and anticipate supplying problems. This paper presents a methodology to forecast hourly global horizontal solar irradiance (GHI) and direct normal irradiance (DNI) using global forecast system (GFS) model from NOAA and MACC model from ECMWF. Three clear sky models are tested to increase temporal resolution of GFS model from 3 hours to 1 hour. The forecasting horizon of the predictions is six days. The model has been validated using a ground radiometric station in Qatar with data from 2014 to 2015. The errors of the best model tested are 19% in terms of relative RMSD and -1.68% regarding relative bias for GHI. In the case of DNI, relative RMSD is 48.43%, and relative bias is -3.40%.
AB - Production of electricity from solar energy is gaining a tremendous significance. The integration of all solar energy power to the electricity grid challenges new horizons. Mainly, the prediction of short-term power generation to optimise its management, avoid situations of load reduction and anticipate supplying problems. This paper presents a methodology to forecast hourly global horizontal solar irradiance (GHI) and direct normal irradiance (DNI) using global forecast system (GFS) model from NOAA and MACC model from ECMWF. Three clear sky models are tested to increase temporal resolution of GFS model from 3 hours to 1 hour. The forecasting horizon of the predictions is six days. The model has been validated using a ground radiometric station in Qatar with data from 2014 to 2015. The errors of the best model tested are 19% in terms of relative RMSD and -1.68% regarding relative bias for GHI. In the case of DNI, relative RMSD is 48.43%, and relative bias is -3.40%.
KW - Aod forecasting
KW - Atmospheric aerosols
KW - Dni prediction
KW - Solar radiation forecasting
UR - http://www.scopus.com/inward/record.url?scp=85016980552&partnerID=8YFLogxK
U2 - 10.18086/swc.2015.07.12
DO - 10.18086/swc.2015.07.12
M3 - Conference contribution
AN - SCOPUS:85016980552
T3 - ISES Solar World Congress 2015, Conference Proceedings
SP - 236
EP - 247
BT - ISES Solar World Congress 2015, Conference Proceedings
A2 - Renne, David
A2 - Seo, Taebeom
A2 - Romero, Manuel
PB - International Solar Energy Society
T2 - International Solar Energy Society, ISES Solar World Congress 2015, SWC 2015
Y2 - 8 November 2015 through 12 November 2015
ER -