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Short-Term Solar Irradiance Forecasting Under Data Transmission Constraints
March 20, 2024, 4:42 a.m. | Joshua Edward Hammond (McKetta Department of Chemical Engineering The University of Texas at Austin), Ricardo A. Lara Orozco (Hildebrand Department of
cs.LG updates on arXiv.org arxiv.org
Abstract: We report a data-parsimonious machine learning model for short-term forecasting of solar irradiance. The model inputs include sky camera images that are reduced to scalar features to meet data transmission constraints. The output irradiance values are transformed to focus on unknown short-term dynamics. Inspired by control theory, a noise input is used to reflect unmeasured variables and is shown to improve model predictions, often considerably. Five years of data from the NREL Solar Radiation Research …
abstract arxiv constraints control cs.lg data dynamics features focus forecasting images inputs machine machine learning machine learning model report solar theory type values
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