Plot EIA data on distributed and centralized generation capacity

This code creates plots for an upcoming UCS blog series showing

• The comparitive growth of centralized and distributed generation
• The growth of distributed generation by technology type
• Comparison of installed cost of PV systems vs electricity prices for residential

Sources

EIA, collected via the following PUDL data sets:

• Core EIA 861 Yearly distributed generation tech
• Core EIA 861 Yearly net metering customer fuel class
• Core EIA 861 Yearly non-net metering customer fuel class
• Out EIA yearly generators

EIA, collected via API:

• Average Price of Electricity to Ultimate Customers

Data that must be downloaded manually

LBNLs "Tracking the Sun" data is only available programmatically in a raw format in a datalake. To run this code, a subsest of the data must be downloaded manually:

1. Go to the Tracking the Sun shiny app
2. Go to the tab "Installed Prices"
3. Download the csv file for the first graph, "Installed Prices"
4. Save the csv to the directory <path-to-repo>/workflow_solution/data/National_Residential_Installed Prices (2000-2023).csv

Using

The repo contains both a snakemake workflow and Jupyter notebooks. The Jupyter notebooks produce additional plots.

Dependencies

Both the notebook and snakemake workflow utilize a private repo to apply UCS styles to the final plots (UCSmpl). Two lines in the code will need to be removed to run the project without this library:

import UCSmpl
...
with plt.style.context('ucs_light'):

After removing the second line be sure to adjust indentation accordingly.