The Use of Gridded Model Output Statistics (GMOS) in Energy Forecasting of a Solar Car [chapter]

Christiaan Oosthuizen, Barend Van Wyk, Yskandar Hamam, Dawood Desai, Yasser Alayli
2020 Advances in Energy Research  
Author contributions: Conceptualization, C.O. and B.V.W.; methodology, B.V.W. and C.O.; software, C.O.; validation, D.D., Y.A., and Y.H.; formal analysis, C.O.; investigation, C.O.; resources, Y.A. and B.V.W.; data curation, C.O.; writingoriginal draft preparation, C.O.; writing-review and editing, D.D., B.V.W., Y.H., and Y.A.; visualization, C.O.; supervision, B.V.W. and Y.H.; project administration, C.O.; funding acquisition, B.V.W., Y.A., and C.O. Acknowledgments: The authors would like to
more » ... ors would like to thank Meteomatics AG for the sponsorship of the forecast data and the merSETA and TUT chair in Intelligent Manufacturing for their financial assistance. Conflicts of Interest: The authors declare no conflict of interest. Abstract (GMOS) Global Horizontal Irradiance (GHI) model developed in this work utilizes historical data from various ground station locations in South Africa to reduce the mean forecast error of the GHI component. An average Root Mean Square Error (RMSE) improvement of 11.28% was shown across all locations and weather conditions. It was also shown how the incorporation of the GMOS model could have increased the accuracy in regard to the State of Charge (SoC) energy simulation of a solar car during the Sasol Solar Challenge 2018 and the possible range benefits thereof.
doi:10.37247/aderes2edn.2.2020.2 fatcat:jottsjxxufdhtku7qjztjvhzre