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ARPA-E PERFORM datasets
Time-coincident load, wind, and solar data including actual and probabilistic forecast datasets at 5-min resolution for ERCOT, MISO, NYISO, and SPP. Wind and solar profiles are supplied for existing sites as well as planned sites based on interconnection queue projects as of 2021. For ERCOT actuals are provided for 2017 and 2018 and forecasts for 2018, and for the remaining ISOs actuals are provided for 2018 and 2019 and forecasts for 2019.
There datasets were produced by NREL as part of the ARPA-E PERFORM project, an ARPA-E funded program that aim to use time-coincident power and load seeks to develop innovative management systems that represent the relative delivery risk of each asset and balance the collective risk of all assets across the grid. For more information on the datasets and methods used to generate them see https://github.com/PERFORM-Forecasts/documentation.
Complete Metadata
| @type | dcat:Dataset |
|---|---|
| accessLevel | public |
| bureauCode |
[
"019:20"
]
|
| contactPoint |
{
"fn": "Brian Sergi",
"@type": "vcard:Contact",
"hasEmail": "mailto:bsergi@nrel.gov"
}
|
| dataQuality |
true
|
| description | Time-coincident load, wind, and solar data including actual and probabilistic forecast datasets at 5-min resolution for ERCOT, MISO, NYISO, and SPP. Wind and solar profiles are supplied for existing sites as well as planned sites based on interconnection queue projects as of 2021. For ERCOT actuals are provided for 2017 and 2018 and forecasts for 2018, and for the remaining ISOs actuals are provided for 2018 and 2019 and forecasts for 2019. There datasets were produced by NREL as part of the ARPA-E PERFORM project, an ARPA-E funded program that aim to use time-coincident power and load seeks to develop innovative management systems that represent the relative delivery risk of each asset and balance the collective risk of all assets across the grid. For more information on the datasets and methods used to generate them see https://github.com/PERFORM-Forecasts/documentation. |
| distribution |
[
{
"@type": "dcat:Distribution",
"title": "ARPA-E PERFORM Data on AWS",
"format": "HTML",
"accessURL": "https://data.openei.org/s3_viewer?bucket=arpa-e-perform",
"mediaType": "text/html",
"description": "AWS Public Dataset Bucket containing ARPA-E PERFORM data. Includes time-coincident load, wind, and solar generation profiles, as well as actual and forecasting time series data. These data are available for download without login credentials through the free and publicly accessible Open Energy Data Initiative (OEDI) data viewer which allows users to browse and download individual or groups of files."
},
{
"@type": "dcat:Distribution",
"title": "Documentation",
"format": "HTML",
"accessURL": "https://github.com/PERFORM-Forecasts/documentation",
"mediaType": "text/html",
"description": "ARPA-E PERFORM Forecasts Documentation"
},
{
"@type": "dcat:Distribution",
"title": "ARPA-E PERFORM Dataset Registry on AWS",
"format": "HTML",
"accessURL": "https://registry.opendata.aws/arpa-e-perform/",
"mediaType": "text/html",
"description": "AWS Public Dataset page for the ARPA-E PERFORM Program, an ARPA-E funded program that aim to use time-coincident power and load seeks to develop innovative management systems that represent the relative delivery risk of each asset and balance the collective risk of all assets across the grid. A risk-driven paradigm allows operators to: (i) fully understand the true likelihood of maintaining a supply-demand balance and system reliability, (ii) optimally manage the system, and (iii) assess the true value of essential reliability services. This paradigm shift is critical for all power systems and is essential for grids with high levels of stochastic resources. Projects will propose methods to quantify and manage risk at the asset level and at the system level. In support of the ARPA-E PERFORM project, NREL has produced a set of time-coincident load, wind, and solar generation profiles, including actual and forecasting time series. Both actuals and forecasts are provided in form of time-series with high temporal and spatial fidelity. Both deterministic and probabilistic forecasts are contained in the dataset. This page includes information about access to the data via AWS command line interface (CLI) and does not require an AWS account."
}
]
|
| DOI | 10.25984/1891136 |
| identifier | https://data.openei.org/submissions/5772 |
| issued | 2022-08-18T06:00:00Z |
| keyword |
[
"5-min data",
"ARPA-E",
"ERCOT",
"MISO",
"NYISO",
"PERFORM",
"SPP",
"actual",
"balance",
"data",
"delivery",
"forecast",
"generation",
"grid",
"load",
"power",
"power systems",
"probabilistic forecast",
"risk",
"solar",
"time-coincident",
"wind"
]
|
| landingPage | https://data.openei.org/submissions/5772 |
| license | https://creativecommons.org/licenses/by/4.0/ |
| modified | 2022-10-06T19:39:20Z |
| programCode |
[
"019:000",
"019:008",
"019:010"
]
|
| projectNumber | CJ0000701 |
| projectTitle | PERFORM Synthetic Data Support |
| publisher |
{
"name": "National Renewable Energy Laboratory (NREL)",
"@type": "org:Organization"
}
|
| spatial |
"{"type":"Polygon","coordinates":[[[-103.30296250000004,34.94017415874445],[-71.45367500000005,34.94017415874445],[-71.45367500000005,48.80272069819772],[-103.30296250000004,48.80272069819772],[-103.30296250000004,34.94017415874445]]]}"
|
| title | ARPA-E PERFORM datasets |
