Bias Correction and Statistical Downscaling of Solar Radiation Using NA-CORDEX and the NSRDB

Maggie Bailey, Soutir Bandyopadhyay, Aron Habte, Douglas Nychka, Manajit Sengupta, Yu Xie

Research output: NRELPoster

Abstract

The current state-of-art for estimating long-term PV production uses long-term estimates of solar radiation variables, such as global horizontal irradiance (GHI), from previous years. This data is used in models such as the System Advisor Model (SAM) or PYSyst to predict annual production for a PV plant. This information is then used to estimate the production over the next 20 years (a typical plant lifetime) under the assumption that the variability over the current period is representative of the future. As the PV industry moves to extend plant lifetimes to 50 years the current assumptions of representativeness of weather may not be appropriate. This is especially true as our climate changes rapidly. To assess long-term PV production, future projections for solar radiation based on projected carbon emissions are readily available in regional and global climate models. However, climate model projections contain inherent biases that may need to be corrected for accurate analysis of future projections of climate variables. Several studies have analyzed projections of solar radiation for future years, however the accuracy of the model output compared to current and historic data has not been widely studied. Chen (2021) showed that available climate models do not accurately represent solar radiation in some cases, over-projecting GHI at the surface while under-projecting its obstructions, such as clouds and aerosols. This works aims to (1) increase understanding of the accuracy of solar radiation currently available in global and regional climate models and (2) implement bias correction through linear models based on reanalysis data compared to observed solar radiation. The latter aim will be conducted using available observed solar radiation data and modeled data from several regional climate models (RCMs). The bias correction method will be applied to projections of solar radiation resulting in a more accurate representation of the future of solar production.
Original languageAmerican English
PublisherNational Renewable Energy Laboratory (NREL)
StatePublished - 2023

Publication series

NamePresented at the European Photovoltaic Solar Energy Conference and Exhibition 2023 (EU PVSEC), 18-23 September 2023, Lisbon, Portugal

NREL Publication Number

  • NREL/PO-5D00-87445

Keywords

  • climate data
  • future projection
  • solar irradiance
  • statistical downscaling

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