Online Program Home
My Program

Abstract Details

Activity Number: 395 - Statistical Models for High-Dimensional Computer Output
Type: Topic Contributed
Date/Time: Tuesday, July 31, 2018 : 2:00 PM to 3:50 PM
Sponsor: Section on Statistics and the Environment
Abstract #328453 Presentation
Title: A Stochastic Approach for Downscaling Solar Irradiance Data Products
Author(s): Wenqi Zhang* and William Kleiber
Companies: University of Colorado at Boulder and University of Colorado
Keywords: Downscaling; Solar Irradiance; Solar Power; Renewable Energy; High-dimensional computer output

Solar power as a source of electricity is increasingly viable, and solar photovoltaic (PV) installations are becoming more common. However, PV planning studies require high frequency solar irradiance scenarios to understand potential variability and intermittency. Existing remote sensing solar data products are often available over large spatial domains, but are limited in their temporal resolution. For instance, the global horizontal component (GHI) in National Solar Radiation Database (NSRDB) is available at time resolution of 30 min on a 4 km grid. We develop an algorithm to stochastically downscale GHI from the NSRDB to the 1 minute resolution. We illustrate the performance of the algorithm at a set of sample locations around Oregon, US. Simulated ensembles show good coverage properties, and maintain important temporal correlation structures. The resulting downscaled ensembles allow for understanding the nonlinear variability inherent in GHI at locations without direct measurements.

Authors who are presenting talks have a * after their name.

Back to the full JSM 2018 program