[LDES-coremodel] gridded data for California

[russ.jones at ieee.org]

I’d like to share something I’ve been working on. With some initial guidance
from Pedro and Kenji, I wrote a python/geopandas program to extract various
data elements from shapefiles in California at every point on a
0.1x0.1-degree resolution grid in California (4310 coordinates in total).  I
have extracted a number of variables for each coordinate:

*	County
*	Electricity demand forecast zone
*	Elevation
*	Protected areas
*	Census tract
*	Population
*	Utility service area
*	Wind resource area
*	Building climate zone

I’ve attached this data as both a csv and Excel file. The Excel version has
a bespoke color-scale mapping program built-in but I’ve also written a
python mapping program to convert the list of coordinates for any named
variable and plot it with a color-scale. Here are a few examples:

 

Elevation_m
forecast zone                                                 protected area
mask



This has all been placed in my GitHub repository “russ-tools”.

 

I’m currently downloading all of the NSRDB hourly data for these locations
for the entire 22-year history, and will produce daily, monthly, and yearly
aggregations from the hourly archive.  I will plan to make all that
available in a shared folder on my OneDrive. It will take another week or so
to get that, limited by the request rate limit of the NSRDB API.

 

Russ Jones

Jones Solar Engineering

Visiting Scholar — Center for Energy Research, University of California at
San Diego

Senior Member, Institute for Electrical and Electronics Engineers (IEEE)

+1-714-206-2556 (m)  ☼   +1-310-469-9045 (VOIP worldwide)

 

 

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