The digital data was generated from the Geographic Information System of the Railroad Commission of Texas. Base map information was obtained directly from U.S. Geological Survey 7.5 minute quadrangle maps. Patent Survey lines from Texas General Land Office maps were interpreted as accurately as possible over the US Geological Survey base. Oil and gas well data or pipeline data (if included) was obtained from public records at the Railroad Commission. The information provided by this system is being continually updated and refined. The data is intended solely for the internal use of the Railroad Commission, which makes no claim as to its accuracy or completeness.Field Definitions can be found at: https://rrc.texas.gov/media/kmld3uzj/digital-map-information-user-guide.pdf

The GIS Viewer allows you to view information about wells, pipelines, surveys, LPG/CNG/LNG, Operator Cleanup Program, Voluntary Cleanup Program, Brownfield Response Program, Commercial Waste Disposal sites, Discharge Permits and related features in a map view. Contact Email: records@rrc.texas.gov

Geospatial data about Texas Pipelines. Export to CAD, GIS, PDF, CSV and access via API.

This layer is sourced from wwwgisp.rrc.state.tx.us.

The Digital Geologic Map of Big Thicket National Preserve and Vicinity, Texas is composed of GIS data layers complete with ArcMap 9.3 layer (.LYR) files, two ancillary GIS tables, a Map PDF document with ancillary map text, figures and tables, a FGDC metadata record and a 9.3 ArcMap (.MXD) Document that displays the digital map in 9.3 ArcGIS. The data were completed as a component of the Geologic Resources Inventory (GRI) program, a National Park Service (NPS) Inventory and Monitoring (I&M) funded program that is administered by the NPS Geologic Resources Division (GRD). Source geologic maps and data used to complete this GRI digital dataset were provided by the following: Texas Water Development Board and Railroad Commission of Texas. Detailed information concerning the sources used and their contribution the GRI product are listed in the Source Citation sections(s) of this metadata record (bith_metadata.txt; available at http://nrdata.nps.gov/bith/nrdata/geology/gis/bith_metadata.xml). All GIS and ancillary tables were produced as per the NPS GRI Geology-GIS Geodatabase Data Model v. 2.1. (available at: http://science.nature.nps.gov/im/inventory/geology/GeologyGISDataModel.cfm). The GIS data is available as a 9.3 personal geodatabase (bith_geology.mdb), and as shapefile (.SHP) and DBASEIV (.DBF) table files. The GIS data projection is NAD83, UTM Zone 15N. That data is within the area of interest of Big Thicket National Preserve.

This layer is sourced from wwwgisp.rrc.state.tx.us.

Oil and gas pipeline data for Denton County, provided by the Railroad Commission of Texas.

Statewide oil and gas pipelines provided by the Texas Railroad Commission.

Oil and gas well locations in Denton County, provided by the Railroad Commission of Texas.

This layer is sourced from wwwgisp.rrc.state.tx.us.

A 24"x28" PDF map of Oil and Gas wells and pipelines in Denton County, provided by the Railroad Commission of Texas.

This Dataverse Dataset contains final versions of reports and related GIS files and data for: Interagency Cooperation Contract between The Railroad Commission of Texas and The University of Texas at Austin Bureau of Economic Geology for Geophysical Data Acquisition and Fault Mapping, BEG/CISR – Texas Railroad Commission 455-24-1012 Reports Now Complete: 1. Progress Report 1Q2024, Project Introduction, Data Assembly, and Reconnaissance by Elizabeth A. Horne and Peter H. Hennings 2. Progress Report 2Q2024, Fault Interpretation, Characterization, and Fault Slip Potential Analysis by Elizabeth A. Horne and Peter H. Hennings 3. Progress Report 3Q2024, 3D Seismic Interpretation and Rock Properties Distribution in the Delaware Mountain Group for Shallow Injection Capacity Assessment by Amanda Calle, Katie Smye, Peter Hennings, Elizabeth A. Horne

This layer is sourced from wwwgisp.rrc.state.tx.us.

DFD Multifamily location Dallas County with master gas meter. Railroad Commission of Texas Pipeline Evaluation System list

This layer is sourced from wwwgisp.rrc.state.tx.us.

Profitability and investment risk of Texan power system winterization

This data repository contains interim and final results of the paper “Profitability and investment risk of Texan power system winterization” published in Nature Energy. Code used to generate these results can be found at github

Abstract

A lack of winterization of power system infrastructure resulted in significant rolling blackouts in Texas in 2021 though debate about the cost of winterization continues. Here, we assess if incentives for winterization on the energy only market are sufficient. We combine power demand estimates with estimates of power plant outages to derive power deficits and scarcity prices. Expected profits from winterization of a large share of existing capacity are positive. However, investment risk is high due to the low frequency of freeze events, potentially explaining under-investment, as do high discount rates and uncertainty about power generation failure under cold temperatures. As the social cost of power deficits is one to two orders of magnitude higher than winterization cost, regulatory enforcement of winterization is welfare enhancing. Current legislation can be improved by emphasizing winterization of gas power plants and infrastructure.

Date and time format

Please observe that we omit the date column from the description of columns below for all datasets. The ERA5 data in input/ is in UTC, all other input datasets are in local Texas time (GMT-6). In interim, temperatures/temppop/, temperatures/temp_gas_powerplant.csv, temperatures/temp_gas_outages.csv, temperatures/temp_coal_powerplant.csv, temperatures/temp_coal_outages.csv and the wind power simulation output (windpower/) is in UTC. All other datasets are in local Texas time.

Data

cache/

Data cache used by the scripts analyzing the extreme events: extreme temperatures, loss of load, their return periods, durations, maxima/minima (the cached files are not included, but can be generated with scripts/R/events.R)

figures/

Figures shown in the manuscript

• raw_data: includes raw data for reproducing the figures in the main part of the manuscript
• outage_model: figures representing the outage function as derived with our model

input/

Input data from external sources (with exception of orcd not included due to licensing issues)

• ERA5_windspeeds_USA: available from the CDS. Download with scripts/download_era5_USA.py
• gas_production: available from the Texas Railroad Commission in PDF format here. We extracted the data manually.
• Load: available from ERCOT here
• orcd: Scarcity prices as regulated by ERCOT. Manually extracted from J. Zarnikau et al.
• outages: Outage Events from ERCOT with geo locations provided by Edgar Virguez here resulting from unit outage data provided by Ercot
• population: population density data provided by arcgis here
• powerplants: locations of power plants in Texas provided by the Energy Information Administration here
• shp: shapefile of Texas state boundaries provided by arcgis here
• temperatures: available from the CDS here. Can be downloaded with script scripts/download_era5_TX_temp.py
• USWTDB: US wind turbine data base provided by the US Geological Service here. We used version: uswtdb_v3_3_20210114
• GWA2: Global Wind Atlas Version 2.1 accessible here

interim/

Intermediary files from the analysis

• bootstrap_year.csv: 30 randomly selected years between 1950 and 2021, 10,000 times used for bootstrapping
  Generated by notebooks/outages_reduced_bootstrap_LR24temptrend_Hook-8.ipynb
• bootstrap_year2020.csv: 30 randomly selected years between 1950 and 2020, 10,000 times used for bootstrapping without 2021 event
  Generated by outages_reduced_bootstrap_LR24temptrend_Hook-8.ipynb
• turbine_data.csv: turbine data for Texan wind turbines
  Generated by scripts/prepare_TX_turbines.py
  Columns:
  • capacity: turbine capacity (kW)
  • height: turbine height (m)
  • lon: longitude coordinate (°)
  • lat: latitude coordinate (°)
  • sp: specific power (W/m²)
  • ind: running index

interim/load/

Temperature dependent estimates of electricity load for Texas.

• load_est70_LR24_temptrend_Hook-8.csv
  Generated by notebooks/load_estimation_LR24_temptrend_Hook-8.ipynb
  Columns:
  • load_est: load estimated for the period 1950-2021 assuming an average load level as in 2021 (MWh)
  • temp: population weighted temperature (°C)
• load_est10_LR24_temptrend_Hook-8.csv
  Generated by notebooks/load_estimation_LR24_temptrend_Hook-8.ipynb
  Columns:
  • load: observed load in period 2012-2021 as published by ERCOT (MWh)
  • load_est: load estimated for period 2012-2021 considering time trend, i.e. this is a replication of the observed load without outages with our model for validation purposes (MWh)
• load_est9_LR24temptrend2021_Hook-8.csv
  Generated by notebooks/load_estimation_LR24_temptrend_Hook-8.ipynb
  Columns:
  • load: observed load in period 2004-2021/01 and load forecast 2021/02 as published by ERCOT (MWh)
  • load_est: load estimated for the years 2012-2020 for cross validation of load model. For training, the years 2012-2021 (2021/02 forecast) were used, except the predicted year, i.e. this is a replication of the observed load with our model for validation purposes. (MWh)
• load_est17_crossvalidation_LR24temptrend_Hook-8.csv Generated by notebooks/load_estimation_LR24_temptrend_Hook-8.ipynb
  Columns:
  • load: observed load 2004 - 2021/01 and load forecast 2021/02 as published by ERCOT (MWh)
  • load_est: load estimated for cross validation for years 2004-2021, training years 2012-2020, trained with each year in traning period except modelled year with variable load level, i.e. this is a replication of the observed load with our model for validation purposes(MWh)
• load_est_LR24temptrend_Hook-8.csv Generated by notebooks/load_estimation_LR24_temptrend_Hook-8.ipynb
  Columns:
  • load: observed load 2004 - 2021 as published by ERCOT (MWh)
  • load_est: years 2004-2021 predicted with a model which was trained for the years 2012-2020 considering time trend, i.e. this is a replication of the observed load without outages with our temperature dependent model with our model for validation purposes (MWh)

interim/outages

• outages.feather Outage by minute of all generation units in Texas in February 2021. Created by scripts/R/create-ercot-outage-timeseries.R In Texas local time.
  Columns:
  • station: name of power plant
  • unit: name of generation unit
  • fullname: concatenated string of station and name
  • dataset: ercot or edgar. ercot refers to the raw dataset provided by ERCOT, Edgar to the dataset provided by Edgar Virguez (for details see above in section input/)
  • Longitude: Longitude of location of power plant
  • Latitude: Latitude of location of power plant
  • reduction: hourly reduction of capacity due to outage in this minute (MW)
  • cap_available: available capacity in this minute (MW)
  • cap_max: maximum capacity of unit (MW)

  </li>
  <li><strong>outages-hourly.feather</strong> Hourly outages at all generation units in Texas in February 2021. Created by scripts/R/create-ercot-outage-timeseries.R In Texas local time.<br>
  Columns:
  <ul>
    <li>station: name of power plant</li>
    <li>unit: name of generation unit</li>
    <li>fullname: concatenated string of station and name</li>
    <li>dataset: ercot or edgar. ercot refers to the raw dataset provided by ERCOT, Edgar to the dataset provided by Edgar Virguez (for details see above in section <strong>input/</strong>)</li>
    <li>Longitude: Longitude of location of power plant</li>
    <li>Latitude: Latitude of location of power plant</li>
    <li>reduction: hourly reduction of capacity due to outage in this time step
  

This layer is sourced from wwwgisp.rrc.state.tx.us.

In compliance with OPP 8.11 and 8.12, the alias for the AGENCY, LATITUDE, and LONGITUDE, and fields have been set to the agency’s spatial data standards of HORZ_ORG, LAT_DD, and LONG_DD, respectively. Similarly, the HORZ_METH, HORZ_ACC, HORZ_REF, HORZ_DESC, HORZ_DATE, and HORZ_DATUM fields have also been added; however, their values of UNKNOWN, -9999, OTHER, UNKNOWN, 01/01/1900, and UNKNOWN, respectively, for every record are not precise because these records were provided by the Railroad Commission of Texas (RRC) and multiple programs within TCEQ. The data owner of this feature class cannot determine the actual values for these six added fields. You can obtain more spatial information about a specific record by going to https://www.tceq.texas.gov/groundwater/groundwater-planning-assessment/sfr-056-joint-groundwater-monitoring-contamination-report and following the instructions under the Requesting Information heading.

This layer is sourced from wwwgisp.rrc.state.tx.us.

This layer is sourced from wwwgisp.rrc.state.tx.us.