Vibrant Clean Energy Resource Adequacy Renewable Energy (RARE) Power Dataset¶

Source URL	https://vibrantcleanenergy.com/products/datasets/
Source Description	This dataset was produced by Vibrant Clean Energy and is licensed to the public under the Creative Commons Attribution 4.0 International license (CC-BY-4.0). The data consists of hourly, county-level renewable generation profiles in the continental United States and was compiled based on outputs from the NOAA HRRR weather model. Profiles are stated as a capacity factor (a percentage of nameplate capacity) and exist for onshore wind, offshore wind, and fixed-tilt solar generation types.
Source Format	Comma Separated Value (.csv)
Download Size	3744 MB
Temporal Coverage	2014-2023
PUDL Code	`vcerare`
Issues	Open Vibrant Clean Energy Resource Adequacy Renewable Energy (RARE) Power Dataset issues

PUDL Database Tables¶

We’ve segmented the processed data into the following normalized data tables. Clicking on the links will show you a description of the table as well as the names and descriptions of each of its fields.

Data Dictionary	Browse Online
out_vcerare__hourly_available_capacity_factor	Table not published to Datasette.

Background¶

The data in the Resource Adequacy Renewable Energy (RARE) Power Dataset was produced by Vibrant Clean Energy based on outputs from the NOA HRRR model and are licensed to the public under the Creative Commons Attribution 4.0 International license (CC-BY-4.0).

See the README archived on Zenodo for more detailed information.

Download additional documentation¶

Data available through PUDL¶

Hourly, county-level data from 2014 - 2023 is integrated into PUDL. Annual releases of the data are expected in Q1 while the high resolution rapid refresh (HRRR) remains an operational model at the National Oceanic and Atmospheric Administration (NOAA), with 2024 data expected in Q1 of 2026. New releases will be integrated into PUDL pending funding availability.

You can explore the VCE RARE dataset with this Jupyter notebook on Kaggle.

Who submits this data?¶

This data does not come from a government agency, and is not the result of compulsory data reporting.

What does the original data look like?¶

The contents of the original CSVs are formatted so that Excel can display the data without crashing. There’s one file per year per generation type, and each file contains an index column for time (simply 1, 2, 3…8760 to represent the hours in a year) and columns for each county populated with capacity factor values as a percentage from 0-100.

Notable Irregularities¶

Non-county regions¶

The original data include capacity factors for some non-county areas including the Great Lakes and 2 small cities (Bedford City, VA and Clifton Forge City, VA). It associated “county” FIPS IDs with those areas, meaning that there was not a 1:1 relationship between the FIPS IDs and the named areas, and the geographic region implied by the FIPS IDs did not correspond to the named area. We’ve dropped the cities – one of which contained no data – and set the FIPS codes for the Great Lakes to NA. Note that lakes bordering multiple states will appear more than once in the data. VCE used a nearest neighbor technique to assign the state waters to the counties (this pertains to coastal areas as well).

Name and ID issues¶

The place name for Lake Huron is misspelled “Hurron” in the original data.
We update the place_name column using the latest Census PEP vintage data, to ensure consistency of place names between this dataset and other PUDL data.

Capacity factors > 1¶

There are a couple of capacity factor values for the solar pv data that exceed the maximum value of 1 for capacity factor (or 100 for the raw data–PUDL converts the data from a percentage to a fraction to match other reported capacity factor data). This is due to power production performance being correlated with panel temperatures. During cold sunny periods, some solar capacity factor values are greater than 1 (but less that 1.1). In 2016, 365 solar values exceeded 1.1 in the raw data and were clipped to 1.1.

Null values¶

In the original data, 1,320 solar capacity values were reported as null in the year 2015. In conversation with the data providers, it was determined that these values should have been reported as zero and accordingly they have been updated as part of the transformation process.

8760-hour years¶

This data is primarily used for modeling purposes and conforms to the 8760 hour/year standard regardless of leap years. This means that 2020 is missing data for December 31st.

PUDL Data Transformations¶

To see the transformations applied to the data in each table, you can read the docstrings for pudl.transform.vcerare created for each table’s respective transform function.