@misc{6d8fb05bc3014f97ada2d8737cb0c520,
title = "Development of a 95-Year Solar Dataset for Resource Adequacy Studies",
abstract = "Long-term high-resolution solar data provides enhanced understanding of variability of solar generation and enhances our ability to develop strategies for a resilient and reliable electric grid under high deployment of solar energy. Therefore, it is important to develop long-term synthetic datasets that can provide multiple occurrences of various severe weather scenarios that are expected to test the limits of resource adequacy under scenarios contain various energy generation sources. Examples of such scenarios could be long periods of high temperatures when demand for electricity is high or periods where high winds could lead to a shut-down of transmission lines for long periods of time to ensure fire safety. NREL has developed the first version of such a dataset covering a 95-year period covering 2006-2100 at a 4km hourly resolution. This dataset contains all variables necessary to calculate solar generation. During development of this dataset, we focused on creating unbiased, high-resolution solar irradiance through statistical downscaling methods, using Regional Climate Model (RCM) simulations from the North American Coordinated Regional Climate Downscaling Experiment (NA-CORDEX) as input. The National Solar Radiation Database (NSRDB) containing over 25 years of observations was used to calibrate the statistical downscaling models. This presentation will outline the primary steps in developing this dataset, including (1) regridding RCM data to a common grid at 20-km resolution, (2) correcting RCM biases with NSRDB, (3) applying temporal and spatial downscaling methods to generate high-resolution (4-km, hourly) solar and ancillary data. Additionally, we will present an evaluation of the downscaled data against the NSRDB across various zones in the CONUS. Lastly, we will present a user guide for accessing the datasets.",
keywords = "downscaling, ESM, resource adequacy, solar",
author = "Jaemo Yang and Manajit Sengupta and Aron Habte and Yu Xie and Maggie Bailey and Douglas Nychka and Soutir Bandyopadhyay",
year = "2025",
doi = "10.2172/3016083",
language = "American English",
series = "Presented at the 2025 PV Performance Modeling Collaborative (PVPMC) Workshop, 13-15 May 2025, Albuquerque, New Mexico",
publisher = "National Renewable Energy Laboratory (NREL)",
address = "United States",
type = "Other",
}