A comprehensive dataset for the accelerated development and benchmarking of solar forecasting methods

Pedro, Hugo T.  C.; Larson, David P.; Coimbra, Carlos F.  M.

doi:10.1063/1.5094494

Title: A comprehensive dataset for the accelerated development and benchmarking of solar forecasting methods

Journal Article · 24 June 2019 · Journal of Renewable and Sustainable Energy

DOI: https://doi.org/10.1063/1.5094494 · OSTI ID:1613506

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Univ. of California, San Diego, CA (United States). Dept. of Mechanical and Aerospace Engineering

We describe and release a comprehensive solar irradiance, imaging, and forecasting dataset. Our goal with this release is to provide standardized solar and meteorological datasets to the research community for the accelerated development and benchmarking of forecasting methods. The data consist of three years (2014–2016) of quality-controlled, 1-min resolution global horizontal irradiance and direct normal irradiance ground measurements in California. In addition, we provide overlapping data from commonly used exogenous variables, including sky images, satellite imagery, and Numerical Weather Prediction forecasts. We also include sample codes of baseline models for benchmarking of more elaborated models.

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Research Organization:: Univ. of California, San Diego, CA (United States)

Sponsoring Organization:: USDOE Office of Energy Efficiency and Renewable Energy (EERE)

Grant/Contract Number:: EE0008216

OSTI ID:: 1613506

Alternate ID(s):: OSTI ID: 1529032

Journal Information:: Journal of Renewable and Sustainable Energy, Vol. 11, Issue 3; ISSN 1941-7012

Publisher:: American Institute of Physics (AIP)Copyright Statement

Country of Publication:: United States

Language:: English

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Cited by: 57 works

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