A cyclostationary model for temporal forecasting and simulation of solar global horizontal irradiance
KAUST DepartmentStatistics Program
Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
Physical Science and Engineering (PSE) Division
Earth Science and Engineering Program
Embargo End Date2022-08-04
Permanent link to this recordhttp://hdl.handle.net/10754/670481
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AbstractAs part of Saudi Vision 2030, a major strategic framework developed by the Council of Economic and Development Affairs of Saudi Arabia, the country aims to reduce its dependency on oil and promote renewable energy for domestic power generation. Among the sustainable energy resources, solar energy is one of the leading resources because of the endowment of Saudi Arabia with plentiful sunlight exposure and year-round clear skies. This essentializes to forecast and simulate solar irradiance, in particular global horizontal irradiance (GHI), as accurately as possible, mainly to be utilized by the power system operators among many others. Motivated by a dataset of hourly solar GHIs, this article proposes a model for short-term point forecast and simulation of GHIs. Two key points, that make our model competent, are: (1) the consideration of the strong dependency of GHIs on aerosol optical depths and (2) the identification of the periodic correlation structure or cyclostationarity of GHIs. The proposed model is shown to produce better forecasts and more realistic simulations than a classical model, which fails to recognize the GHI data as cyclostationary. Further, simulated samples from both the models as well as the original GHI data are used to calculate the corresponding photovoltaic power outputs to provide a comprehensive comparison among them.
CitationDas, S., Genton, M. G., Alshehri, Y. M., & Stenchikov, G. L. (2021). A cyclostationary model for temporal forecasting and simulation of solar global horizontal irradiance. Environmetrics. doi:10.1002/env.2700
SponsorsThe authors thank the King Abdullah City for Atomic and Renewable Energy (K.A.CARE) for providing the solar irradiance observational dataset.