|
Activity Number:
|
620
- Spatial and Spatiotemporal Modeling in Climate and Meteorology
|
|
Type:
|
Contributed
|
|
Date/Time:
|
Thursday, August 1, 2019 : 8:30 AM to 10:20 AM
|
|
Sponsor:
|
Section on Statistics and the Environment
|
|
Abstract #301792
|
|
|
Title:
|
Stochastically Downscaling High-Frequency Solar Irradiance Data
|
|
Author(s):
|
Wenqi Zhang* and William Kleiber and Bri-Mathias Hodge
|
|
Companies:
|
University of Colorado, Boulder and University of Colorado and University of Colorado, Boulder
|
|
Keywords:
|
Jump diffusion;
Non-Gaussian;
Time series
|
|
Abstract:
|
Solar power is increasingly cost viable with solar photovoltaic (PV) installations becoming commonplace. PV planning and operational studies, however, require high-frequency solar irradiance scenarios to understand potential electric grid impacts due to the variability and uncertainty of the underlying solar resource. Existing remote sensing solar data products are often available over large spatial domains, but are limited in temporal resolution. We introduce and discuss a new stochastic jump diffusion process to temporally downscale a popular satellite-based irradiance data product and validate it on multiple challenging datasets.
|
Authors who are presenting talks have a * after their name.
