Tag: eia923

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updates

PUDL v0.5.0: 2020 and Beyond

It’s been almost a month since we pushed out our first actual quarterly software and data release: PUDL v0.5.0! The main impetus for this release was to get the final annual 2020 data integrated for the FERC and EIA datasets we process. We also pulled in the EIA 860 data for 2001-2003, which is only available as DBF files, rather than Excel spreadsheets. This means we’ve got coverage going back to 2001 for all of our data now! Twenty years! We don’t have 100% coverage of all of the data contained in those datasets yet, but we’re getting closer.

Beyond simply updating the data, we’ve also been making some significant changes to how our ETL pipeline works under the hood. This includes how we store metadata, how we generate the database schema, and what outputs we’re generating. The release notes contain more details on the code changes, so here I want to talk a little bit more about why, and where we are hopefully headed.

If you just want to download the new data release and start working with it, it’s up here on Zenodo. The same data for FERC 1 and EIA 860/923 can also be found in our Datasette instance at https://data.catalyst.coop

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Categories
updates

New PUDL Software & Data Release: v0.4.0

In August we put out a new PUDL software and data release for the first time in 18 months. We had a lot of client work, and kept putting off doing the release, so a whole lot of changes accumulated. Some highlights, mostly based on the continuously updated release notes in our documentation:

New Data Coverage

  • EIA Form 860 added coverage for 2004-2008, as well as 2019.
  • EIA Form 860m has been integrated (through Nov 2020). Note that it only adds up-to-date information about generators (especially their operational status).
  • EIA Form 923 added the 2001-2008 data, as well as 2019.
  • EPA CEMS Hourly Emissions covering 2019-2020.
  • FERC Form 714 covering 2006-2019, but only the table of hourly electricity demand by planning area. This data is still in beta and the data hasn’t been integrated into the core SQLite database, but you can process it on the fly if you want to work with it in Pandas.
  • EIA Form 861 for 2001-2019. Similar to the FERC Form 714, this ETL runs on the fly and the outputs aren’t integrated into the database yet, but it’s available for experimental use.
  • US Census Demographic Profile 1 (DP1) for 2010. This is a separate SQLite database, generated from a US Census Geodatabase, which includes census tract, county, and state level demographic information, as well as spatial boundaries of those jurisdictions.
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analysis

Boiler Generator Associations from EIA 923 and 860

In working to calculate the marginal cost of electricity of all of the generating units across the country, we first had to calculate the heat rate (MMBtu per MWhr) for each generating unit. The heat rate allows us to attribute the fuel costs, reported at the plant level, to the electric generation, reported at the generating unit level. The heat rate is derived from fuel consumption (MMBtu), reported at the boiler level, and electricity generation (MWh), reported at the generating unit level. To understand the heat rate, one must link up all the boilers with the generators in a given generating unit. Our work to this end uncovered a hole in EIA’s 860 reported boiler generator associations. We filled this hole through a series of matching cartwheels and network analysis.

We’ve recently reconfigured our database ingest process to move the new and improved boiler generator associations into its own table in PUDL. You can also read through this process as a Github Gist.

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analysis

Heat Rate Calculation for EIA Generators

Catalyst is pulling together an estimate of the marginal cost of electricity (MCOE) for every natural gas and coal fired power plant in the US whose data we can get our hands on. We’re using data from the EIA 923, EIA 860, and FERC Form 1 to do it.  Getting the heat rate right for each generator is an important part of this calculation, but a lot of the required data is… not perfect. Here’s how we’re working through it.

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