The Utility Energy Registry (UER) is a database platform that provides streamlined public access to aggregated community-scale utility-reported energy data. The UER is intended to promote and facilitate community-based energy planning and energy use awareness and engagement. On April 19, 2018, the New York State Public Service Commission (PSC) issued the Order Adopting the Utility Energy Registry under regulatory CASE 17-M-0315. The order requires utilities under its regulation to develop and report community energy use data to the UER.This dataset includes electricity and natural gas usage data reported at the city, town, and village level collected under a data protocol in effect between 2016 and 2021. Other UER datasets include energy use data reported at the county and ZIP code level. Data collected after 2021 were collected according to a modified protocol. Those data may be found at https://data.ny.gov/Energy-Environment/Utility-Energy-Registry-Monthly-Community-Energy-U/4txm-py4p.Data in the UER can be used for several important purposes such as planning community energy programs, developing community greenhouse gas emissions inventories, and relating how certain energy projects and policies may affect a particular community. It is important to note that the data are subject to privacy screening and fields that fail the privacy screen are withheld.

The databases contain all the technical, financial, and tariff data collected through the study "Making power affordable in Africa and viable for its utilities." The final study and background papers are available at http://www.worldbank.org/affordableviablepowerforafrica. The objective of making the database public is to make data collected through the study available to utility companies, regulators, and practitioners to provide benchmarks and help inform analysis. The databases will be updated from time to time to make corrections or updates for latest data available and therefore may differ from data that appears in the reports. This database is a publication of the African Renewable Energy Access Program (AFREA), a World Bank Trust Fund Grant Program funded by the Kingdom of the Netherlands through ESMAP. It was prepared by staff of the International Bank for Reconstruction and Development / The World Bank.

This dataset, compiled by NREL using data from ABB, the Velocity Suite (http://energymarketintel.com/) and the U.S. Energy Information Administration dataset 861 (http://www.eia.gov/electricity/data/eia861/), provides average residential, commercial and industrial electricity rates with likely zip codes for both investor owned utilities (IOU) and non-investor owned utilities. Note: the files include average rates for each utility (not average rates per zip code), but not the detailed rate structure data found in the OpenEI U.S. Utility Rate Database (https://openei.org/apps/USURDB/).

Data about power company service areas and their announcements about outages are critical for the effective coordination of resources after disasters, and also for building community and neighborhood resilience. As part of the 2015 White House Mapathon, the Department of Energy's Office of Electricity created a national geospatial database of power company service areas with pointers to public outage information (eg, through Twitter, web sites, and toll-free telephone numbers).

Mapathon participants researched public outage information state by state, and populated a lookup table so that disaster-impacted residents, tourists, first responders and relief volunteers can easily get to the information they need on scope and estimated restore times for power outages. This project benefited from participation of private and public sector folks who need this data for their work, and of third party app developers such as Red Cross and The Weather Channel who will incorporate this data into the information services they offer their users.

The Utility Rate Database (URDB) is a free storehouse of rate structure information from utilities in the United States. Here, you can search for your utilities and rates to find out exactly how you are charged for your electric energy usage. Understanding this information can help reduce your bill, for example, by running your appliances during off-peak hours (times during the day when electricity prices are less expensive) and help you make more informed decisions regarding your energy usage.

Rates are also extremely important to the energy analysis community for accurately determining the value and economics of distributed generation such as solar and wind power. In the past, collecting rates has been an effort duplicated across many institutions. Rate collection can be tedious and slow, however, with the introduction of the URDB, OpenEI aims to change how analysis of rates is performed. The URDB allows anyone to access these rates in a computer-readable format for use in their tools and models. OpenEI provides an API for software to automatically download the appropriate rates, thereby allowing detailed economic analysis to be done without ever having to directly handle complex rate structures. Essentially, rate collection and processing that used to take weeks or months can now be done in seconds!

NREL’s System Advisor Model (formerly Solar Advisor Model or SAM), currently has the ability to communicate with the OpenEI URDB over the internet. SAM can download any rate from the URDB directly into the program, thereby enabling users to conduct detailed studies on various power systems ranging in size from a small residential rooftop solar system to large utility scale installations. Other applications available at NREL, such as OpenPV and IMBY, will also utilize the URDB data.

Upcoming features include better support for entering net metering parameters, maps to summarize the data, geolocation capabilities, and hundreds of additional rates!

EIA previously collected sales and revenue data in a category called "Other." This category was defined as including activities such as public street highway lighting, other sales to public authorities, sales to railroads and railways, and interdepartmental sales. EIA has revised its survey to separate the transportation sales and reassign the other activities to the commercial and industrial sectors as appropriate.

<p class="Bodypara">This is an electric utility data file that includes

utility level retail sales of electricity and associated revenue by end-use sector, State, and reporting month. The data source is the survey: Form EIA-826, "Monthly Electric Utility Sales and Revenue Report with State Distributions." The Form EIA-826 is used to collect retail sales of electricity and associated revenue, each month, from a statistically chosen sample of electric utilities in the United States. The respondents to the Form EIA-826 are chosen from the Form EIA-861, "Annual Electric Utility Report." The data also include, for each State, a record (UTILITYID "000000") containing data values which represent the arithmetic differences between the "estimated" State totals and the sum of the retail sales and associated revenue data reported by the respondents to the Form EIA-826.

The data are compressed into a self-extracting (f826yyyy.exe) zip file. This self-extracting zip file expands into one DBF file (f826utilyyyy.dbf) that contains the yearly data and an ASCII text file (f826layoutyyyy.txt) that contains the file description and record layout for the data base structure. The current year's file will be a year-to-date file and is maintained in this monthly format until the data for the final month is finalized.

To expand the self-extracting zip file, type f826yyyy.exe from a DOS window, or double click on the file name from File Manager in Windows 3x or Windows Explorer in either Windows 95, Windows 98, Windows 2000, XP, or ME. Or, click Start, then Run, then select name of .EXE file to open, then "OK." (Requires approx. 600K space). Usually, the current year's file will be a "year-to-date" file until the data for the final month is finalized.

^*Note: Substitute the applicable year for "yyyy" in the file name.

File Size: 200 k

Methodology is based on the "Model-Based Sampling, Inference and Imputation."

Contact:

Abstract

This dataset, compiled by NREL using data from ABB, the Velocity Suite and the U.S. Energy Information Administration dataset 861, provides average residential, commercial and industrial electricity rates with likely zip codes for both investor owned utilities (IOU) and non-investor owned utilities. Note: the files include average rates for each utility (not average rates per zip code), but not the detailed rate structure data found in the OpenEI U.S. Utility Rate Database.

PUDL v2025.2.0 Data Release

This is our regular quarterly release for 2025Q1. It includes updates to all the datasets that are published with quarterly or higher frequency, plus initial verisons of a few new data sources that have been in the works for a while.

One major change this quarter is that we are now publishing all processed PUDL data as Apache Parquet files, alongside our existing SQLite databases. See Data Access for more on how to access these outputs.

Some potentially breaking changes to be aware of:

In the EIA Form 930 – Hourly and Daily Balancing Authority Operations Report a number of new energy sources have been added, and some old energy sources have been split into more granular categories. See Changes in energy source granularity over time.

We are now running the EPA’s CAMD to EIA unit crosswalk code for each individual year starting from 2018, rather than just 2018 and 2021, resulting in more connections between these two datasets and changes to some sub-plant IDs. See the note below for more details.

Many thanks to the organizations who make these regular updates possible! Especially GridLab, RMI, and the ZERO Lab at Princeton University. If you rely on PUDL and would like to help ensure that the data keeps flowing, please consider joining them as a PUDL Sustainer, as we are still fundraising for 2025.

New Data

EIA 176

Add a couple of semi-transformed interim EIA-176 (natural gas sources and dispositions) tables. They aren’t yet being written to the database, but are one step closer. See #3555 and PRs #3590, #3978. Thanks to @davidmudrauskas for moving this dataset forward.

Extracted these interim tables up through the latest 2023 data release. See #4002 and #4004.

EIA 860

Added EIA 860 Multifuel table. See #3438 and #3946.

FERC 1

Added three new output tables containing granular utility accounting data. See #4057, #3642 and the table descriptions in the data dictionary:

out_ferc1_yearly_detailed_income_statements

out_ferc1_yearly_detailed_balance_sheet_assets

out_ferc1_yearly_detailed_balance_sheet_liabilities

SEC Form 10-K Parent-Subsidiary Ownership

We have added some new tables describing the parent-subsidiary company ownership relationships reported in the SEC’s Form 10-K, Exhibit 21 “Subsidiaries of the Registrant”. Where possible these tables link the SEC filers or their subsidiary companies to the corresponding EIA utilities. This work was funded by a grant from the Mozilla Foundation. Most of the ML models and data preparation took place in the mozilla-sec-eia repository separate from the main PUDL ETL, as it requires processing hundreds of thousands of PDFs and the deployment of some ML experiment tracking infrastructure. The new tables are handed off as nearly finished products to the PUDL ETL pipeline. Note that these are preliminary, experimental data products and are known to be incomplete and to contain errors. Extracting data tables from unstructured PDFs and the SEC to EIA record linkage are necessarily probabalistic processes.

See PRs #4026, #4031, #4035, #4046, #4048, #4050 and check out the table descriptions in the PUDL data dictionary:

out_sec10k_parents_and_subsidiaries

core_sec10k_quarterly_filings

core_sec10k_quarterly_exhibit_21_company_ownership

core_sec10k_quarterly_company_information

Expanded Data Coverage

EPA CEMS

Added 2024 Q4 of CEMS data. See #4041 and #4052.

EPA CAMD EIA Crosswalk

In the past, the crosswalk in PUDL has used the EPA’s published crosswalk (run with 2018 data), and an additional crosswalk we ran with 2021 EIA 860 data. To ensure that the crosswalk reflects updates in both EIA and EPA data, we re-ran the EPA R code which generates the EPA CAMD EIA crosswalk with 4 new years of data: 2019, 2020, 2022 and 2023. Re-running the crosswalk pulls the latest data from the CAMD FACT API, which results in some changes to the generator and unit IDs reported on the EPA side of the crosswalk, which feeds into the creation of core_epa_assn_eia_epacamd.

The changes only result in the addition of new units and generators in the EPA data, with no changes to matches at the plant level. However, the updates to generator and unit IDs have resulted in changes to the subplant IDs - some EIA boilers and generators which previously had no matches to EPA data have now been matched to EPA unit data, resulting in an overall reduction in the number of rows in the core_epa_assn_eia_epacamd_subplant_ids table. See issues #4039 and PR #4056 for a discussion of the changes observed in the course of this update.

EIA 860M

Added EIA 860m through December 2024. See #4038 and #4047.

EIA 923

Added EIA 923 monthly data through September 2024. See #4038 and #4047.

EIA Bulk Electricity Data

Updated the EIA Bulk Electricity data to include data published up through 2024-11-01. See #4042 and PR #4051.

EIA 930

Updated the EIA 930 data to include data published up through the beginning of February 2025. See #4040 and PR #4054. 10 new energy sources were added and 3 were retired; see Changes in energy source granularity over time for more information.

Bug Fixes

Fix an accidentally swapped set of starting balance / ending balance column rename parameters in the pre-2021 DBF derived data that feeds into core_ferc1_yearly_other_regulatory_liabilities_sched278. See issue #3952 and PRs #3969, #3979. Thanks to @yolandazzz13 for making this fix.

Added preliminary data validation checks for several FERC 1 tables that were missing it #3860.

Fix spelling of Lake Huron and Lake Saint Clair in out_vcerare_hourly_available_capacity_factor and related tables. See issue #4007 and PR #4029.

Quality of Life Improvements

We added a sources parameter to pudl.metadata.classes.DataSource.from_id() in order to make it possible to use the pudl-archiver repository to archive datasets that won’t necessarily be ingested into PUDL. See this PUDL archiver issue and PRs #4003 and #4013.

Other PUDL v2025.2.0 Resources

PUDL v2025.2.0 Data Dictionary

PUDL v2025.2.0 Documentation

PUDL in the AWS Open Data Registry

PUDL v2025.2.0 in a free, public AWS S3 bucket: s3://pudl.catalyst.coop/v2025.2.0/

PUDL v2025.2.0 in a requester-pays GCS bucket: gs://pudl.catalyst.coop/v2025.2.0/

Zenodo archive of the PUDL GitHub repo for this release

PUDL v2025.2.0 release on GitHub

PUDL v2025.2.0 package in the Python Package Index (PyPI)

Contact Us

If you're using PUDL, we would love to hear from you! Even if it's just a note to let us know that you exist, and how you're using the software or data. Here's a bunch of different ways to get in touch:

Follow us on GitHub

Use the PUDL Github issue tracker to let us know about any bugs or data issues you encounter

GitHub Discussions is where we provide user support.

Watch our GitHub Project to see what we're working on.

Email us at hello@catalyst.coop for private communications.

On Mastodon: @CatalystCoop@mastodon.energy

On BlueSky: @catalyst.coop

On Twitter: @CatalystCoop

Connect with us on LinkedIn

Play with our data and notebooks on Kaggle

Combine our data with ML models on HuggingFace

Learn more about us on our website: https://catalyst.coop

Subscribe to our announcements list for email updates.

This database represents a list of community solar projects identified through various sources as of Spring 2018. The list has been reviewed but errors may exist and the list may not be comprehensive. Errors in the souces e.g. press releases may be duplicated in the list. Blank spaces represent missing information. NREL invites input to improve the database including to - correct erroneous information - add missing projects - fill in missing information - remove inactive projects. Updated information can be submitted to Eric O'Shaughnessy at eric.oshaughnessy@nrel.gov.

India Electricity: Consumption: Utilities: Industry data was reported at 645,000.000 GWh in 2024. This records an increase from the previous number of 593,895.000 GWh for 2023. India Electricity: Consumption: Utilities: Industry data is updated yearly, averaging 104,809.500 GWh from Mar 1971 (Median) to 2024, with 54 observations. The data reached an all-time high of 645,000.000 GWh in 2024 and a record low of 29,579.000 GWh in 1971. India Electricity: Consumption: Utilities: Industry data remains active status in CEIC and is reported by Ministry of Statistics and Programme Implementation. The data is categorized under Global Database’s India – Table IN.RBE002: Electricity: Consumption: Utilities.

The Utility Energy Registry (UER) is a database platform that provides streamlined public access to aggregated community-scale energy data. The UER is intended to promote and facilitate community-based energy planning and energy use awareness and engagement. On April 19, 2018, the New York State Public Service Commission (PSC) issued the Order Adopting the Utility Energy Registry under regulatory CASE 17-M-0315. The order requires utilities and CCA administrators under its regulation to develop and report community energy use data to the UER.

This dataset includes electricity and natural gas usage data reported by utilities at the county level. Other UER datasets include energy use data reported at the city, town, and village, and ZIP code level.

Data in the UER can be used for several important purposes such as planning community energy programs, developing community greenhouse gas emissions inventories, and relating how certain energy projects and policies may affect a particular community. It is important to note that the data are subject to privacy screening and fields that fail the privacy screen are withheld.

The New York State Energy Research and Development Authority (NYSERDA) offers objective information and analysis, innovative programs, technical expertise, and support to help New Yorkers increase energy efficiency, save money, use renewable energy, and reduce reliance on fossil fuels. To learn more about NYSERDA’s programs, visit nyserda.ny.gov or follow us on X, Facebook, YouTube, or Instagram.

Investments in infrastructure have been on the development agenda of Latin American and Caribbean (LCR) countries as they move towards economic and social progress. Investing in infrastructure is investing in human welfare by providing access to and quality basic infrastructure services. Improving the performance of the electricity sector is one such major infrastructure initiative and the focus of this benchmarking data. A key initiative for both public and private owned distribution utilities has been to upgrade their efficiency as well as to increase the coverage and quality of service. In order to accomplish this goal, this initiative serves as a clearing house for information regarding the country and utility level performance of electricity distribution sector. This initiative allows countries and utilities to benchmark their performance in relation to other comparator utilities and countries. In doing so, this benchmarking data contributes to the improvement of the electricity sector by filling in knowledge gaps for the identification of the best performers (and practices) of the region.

This benchmarking database consists of detailed information of 25 countries and 249 utilities in the region. The data collected for this benchmarking project is representative of 88 percent of the electrification in the region. Through in-house and field data collection, consultants compiled data based on accomplishments in output, coverage, input, labor productivity, operating performance, the quality of service, prices, and ownership. By serving as a mirror of good performance, the report allows for a comparative analysis and the ranking of utilities and countries according to the indicators used to measure performance.

Although significant efforts have been made to ensure data comparability and consistency across time and utilities, the World Bank and the ESMAP do not guarantee the accuracy of the data included in this work.

Acknowledgement:
This benchmarking database was prepared by a core team consisting of Luis Alberto Andres (Co-Task Team Leader), Jose Luis Guasch (Co-Task Team Leader), Julio A. Gonzalez, Georgeta Dragoiu, and Natalie Giannelli. The team was benefited by data contributions from Jordan Z. Schwartz (Senior Infrastructure Specialist, LCSTR), Lucio Monari (Lead Energy Economist, LCSEG), Katharina B. Gassner (Senior Economist, FEU), and Martin Rossi (consultant).
Funding was provided by the Energy Sector Management Assistance Program (ESMAP) and the World Bank.

Comments and suggestion are welcome by contacting Luis Andres (landres@worldbank.org)

The databases contain all the technical, financial, and tariff data collected through the study "Making power affordable in Africa and viable for its utilities." The WB study uses national household expenditure surveys conducted since 2008 in 22 countries; it makes use of tariff schedules in effect as of July 2014 in 39 countries, including all of the 22 countries with household surveys. The objective of making the database public is to make data collected through the study available to utility companies, regulators, and practitioners to provide benchmarks and help inform analysis. The databases will be updated from time to time to make corrections or updates for latest data available and therefore may differ from data that appears in the reports. This database is a publication of the African Renewable Energy Access Program (AFREA), a World Bank Trust Fund Grant Program funded by the Kingdom of the Netherlands through ESMAP. It was prepared by staff of the International Bank for Reconstruction and Development / The World Bank. The full report is available at https://openknowledge.worldbank.org/handle/10986/25091 Last Updated 26-Oct-2016 Citation: Trimble, Chris; Kojima, Masami; Perez Arroyo, Ines; Mohammadzadeh, Farah. 2016. Financial Viability of Electricity Sectors in Sub-Saharan Africa: Quasi-Fiscal Deficits and Hidden Costs. Policy Research Working Paper; No. 7788.

This data is usually updated quarterly by February 1st, May 1st, August 1st, and November 1st.The CEC Power Plant geospatial data layer contains point features representing power generating facilities in California, and power plants with imported electricity from Nevada, Arizona, Utah and Mexico.The transmission line, substation and power plant mapping database were started in 1990 by the CEC GIS staffs. The final project was completed in October 2010. The enterprise GIS system on CEC's critical infrastructure database was leaded by GIS Unit in November 2014 and was implemented in May 2016. The data was derived from CEC's Quarterly Fuel and Energy Report (QFER), Energy Facility Licensing (Siting), Wind Performance Reporting System (WPRS), and Renewable Energy Action Team (REAT). The sources for the power plant point digitizing are including sub-meter resolution of Digital Globe, Bing, Google, ESRI and NAIP aerial imageries, with scale at least 1:10,000. Occasionally, USGS Topographic map, Google Street View and Bing Bird's Eye are used to verify the precise location of a facility.Although a power plant may have multiple generators, or units, the power plant layer represents all units at a plant as one feature. Detailed attribute information associated with the power plant layer includes CEC Plant ID, Plant Label, Plant Capacity (MW), General Fuel, Plant Status, CEC Project Status, CEC Docket ID, REAT ID, Plant County, Plant State, Renewable Energy, Wind Resource Area, Local Reliability Area, Sub Area, Electric Service Area, Service Area Category, California Balancing Authorities, California Air District, California Air Basin, Quad Name, Senate District, Assembly District, Congressional District, Power Project Web Link, CEC Link, Aerial, QRERGEN Comment, WPRS Comment, Geoscience Comment, Carto Comment, QFERGEN Excel Link, WPRS Excel Link, Schedule 3 Excel Link, and CEC Data Source. For power plant layer which is joined with QFer database, additional fields are displayed: CEC Plant Name (full name), Plant Alias, EIA Plant ID, Plant City, Initial Start Date, Online Year, Retire Date, Generator or Turbine Count, RPS Eligible, RPS Number, Operator Company Name, and Prime Mover ID. In general, utility and non-utility operated power plant spatial data with at least 1 MW of demonstrated capacity and operating status are distributed. Special request is required on power plant spatial data with all capacities and all stages of status, including Cold Standby, Indefinite Shutdown, Maintenance, Non-Operational, Proposed, Retired, Standby, Terminated, and Unknown.For question on power generation or others, please contact Michael Nyberg at (916) 654-5968.California Energy Commission's Open Data Portal.

Electricity Consumption: Utilities: Meghalaya data was reported at 1,719.000 GWh in 2023. This records an increase from the previous number of 1,507.000 GWh for 2022. Electricity Consumption: Utilities: Meghalaya data is updated yearly, averaging 921.960 GWh from Mar 1996 (Median) to 2023, with 28 observations. The data reached an all-time high of 1,719.000 GWh in 2023 and a record low of 281.140 GWh in 1996. Electricity Consumption: Utilities: Meghalaya data remains active status in CEIC and is reported by Central Electricity Authority. The data is categorized under Global Database’s India – Table IN.RBE002: Electricity: Consumption: Utilities.

Electric utilities report a huge amount of information to the US government and other public agencies. This includes yearly, monthly, and even hourly data about fuel burned, electricity generated, operating expenses, power plant usage patterns and emissions. Unfortunately, much of this data is not released in well documented, ready-to-use, machine readable formats. Data from different agencies tends not to be standardized or easily used in tandem. Several commercial data services clean, package, and re-sell this this data, but at prices which are too high to be accessible to many smaller stakeholders.

The Public Utility Data Liberation (PUDL) project takes information that’s already publicly available, and makes it publicly usable, by cleaning, standardizing, and cross-linking utility data from different sources in a single database. Thus far our primary focus has been on fuel use, generation, operating costs, and operation history. It currently includes data from:

• EIA Form 860: 2001-2022
• EIA Form 860m: 2023-09
• EIA Form 861: 2001-2022
• EIA Form 923: 2001-2022
• EPA Continuous Emissions Monitoring System (CEMS): 1995-2022
• FERC Form 1: 1994-2021
• FERC Form 714: 2006-2020
• US Census Demographic Profile 1 Geodatabase: 2010

We archive snapshots of the raw inputs on Zenodo and all our data processing uses those snapshots as a starting place for reproducibility.

You can find the source code that generates this database in the PUDL repository on GitHub. The PUDL project is coordinated by Catalyst Cooperative.

The data is updated nightly by our automated nightly builds. When they are successful, new data is uploaded to the AWS Open Data Registry

We publish PUDL Data Dictionaries on Read the Docs which provide more descriptive information about the data.

Dataset header image courtesy of Gerry Machen via Flickr under a CC-BY-ND license

This spreadsheet contains information reported by over 200 investor-owned utilities to the Federal Energy Regulatory Commission in the annual filing FERC Form 1 for the years 1994-2019. It contains 1) annual capital costs for new transmission, distribution, and administrative infrastructure; 2) annual operation and maintenance costs for transmission, distribution, and utility business administration; 3) total annual MWh sales and sales by customer class; 4) annual peak demand in MW; and 5) total customer count and the number of customers by class.

Annual spending on new capital infrastructure is read from pages 204 to 207 of FERC Form 1, titled Electric Plant in Service. Annual transmission capital additions are recorded from Line 58, Column C - Total Transmission Plant Additions. Likewise, annual distribution capital additions are recorded from Line 75, Column C - Total Distribution Plant Additions. Administrative capital additions are recorded from Line 5, Column C - Total Intangible Plant Additions, and Line 99, Column C - Total General Plant Additions.

Operation and maintenance costs associated with transmission, distribution, and utility administration are read from pages 320 to 323 of FERC Form 1, titled Electric Operation and Maintenance Expenses. Annual transmission operation and maintenance are recorded from Line 99, Column B - Total Transmission Operation Expenses for Current Year, and Line 111, Column B - Total Transmission Maintenance Expenses for Current Year. Likewise, annual distribution operation and maintenance costs are recorded from Line 144, Column B - Total Distribution Operation Expenses, and Line 155, Column B - Total Distribution Maintenance Expenses. Administrative operation and maintenance costs are recorded from: Line 164, Column B - Total Customers Accounts Expenses; Line 171, Column B - Total Customer Service and Information Expenses; Line 178, Column B - Total Sales Expenses; and Line 197, Column B - Total Administrative and General Expenses.

The annual peak demand in MW over the year is read from page 401, titled Monthly Peaks and Output. The monthly peak demand is listed in Lines 29 to 40, Column D. The maximum of these monthly reports during each year is taken as the annual peak demand in MW. The annual energy sales and customer count data come from page 300, Electric Operating Revenues. The values are provided in Line 2 - Residential Sales, Line 4 - Commercial Sales, Line 5 - Industrial Sales, and Line 10 - Total Sales to Ultimate Consumers.

More information about the database is available in an associated report published by the University of Texas at Austin Energy Institute: https://live-energy-institute.pantheonsite.io/sites/default/files/UTAustin_FCe_TDA_2016.pdf

Also see an associated paper published in the journal Energy Policy:

Fares, Robert L., and Carey W. King. "Trends in transmission, distribution, and administration costs for US investor-owned electric utilities." Energy Policy 105 (2017): 354-362. https://doi.org/10.1016/j.enpol.2017.02.036

All data come from the Federal Energy Regulatory Commission FERC Form 1 Database available in Microsoft Visual FoxPro Format: https://www.ferc.gov/docs-filing/forms/form-1/data.asp

Abstract

Estache and Goicoechea present an infrastructure database that was assembled from multiple sources. Its main purposes are: (i) to provide a snapshot of the sector as of the end of 2004; and (ii) to facilitate quantitative analytical research on infrastructure sectors. The related working paper includes definitions, source information and the data available for 37 performance indicators that proxy access, affordability and quality of service (most recent data as of June 2005). Additionally, the database includes a snapshot of 15 reform indicators across infrastructure sectors.

This is a first attempt, since the effort made in the World Development Report 1994, at generating a database on infrastructure sectors and it needs to be recognized as such. This database is not a state of the art output—this is being worked on by sector experts on a different time table. The effort has however generated a significant amount of new information. The database already provides enough information to launch a much more quantitative debate on the state of infrastructure. But much more is needed and by circulating this information at this stage, we hope to be able to generate feedback and fill the major knowledge gaps and inconsistencies we have identified.

Geographic coverage

The database covers the following countries: - Afghanistan - Albania - Algeria - American Samoa - Andorra - Angola - Antigua and Barbuda - Argentina - Armenia - Aruba - Australia - Austria - Azerbaijan - Bahamas, The - Bahrain - Bangladesh - Barbados - Belarus - Belgium - Belize - Benin - Bermuda - Bhutan - Bolivia - Bosnia and Herzegovina - Botswana - Brazil - Brunei - Bulgaria - Burkina Faso - Burundi - Cambodia - Cameroon - Canada - Cape Verde - Cayman Islands - Central African Republic - Chad - Channel Islands - Chile - China - Colombia - Comoros - Congo, Dem. Rep. - Congo, Rep. - Costa Rica - Cote d'Ivoire - Croatia - Cuba - Cyprus - Czech Republic - Denmark - Djibouti - Dominica - Dominican Republic - Ecuador - Egypt, Arab Rep. - El Salvador - Equatorial Guinea - Eritrea - Estonia - Ethiopia - Faeroe Islands - Fiji - Finland - France - French Polynesia - Gabon - Gambia, The - Georgia - Germany - Ghana - Greece - Greenland - Grenada - Guam - Guatemala - Guinea - Guinea-Bissau - Guyana - Haiti - Honduras - Hong Kong, China - Hungary - Iceland - India - Indonesia - Iran, Islamic Rep. - Iraq - Ireland - Isle of Man - Israel - Italy - Jamaica - Japan - Jordan - Kazakhstan - Kenya - Kiribati - Korea, Dem. Rep. - Korea, Rep. - Kuwait - Kyrgyz Republic - Lao PDR - Latvia - Lebanon - Lesotho - Liberia - Libya - Liechtenstein - Lithuania - Luxembourg - Macao, China - Macedonia, FYR - Madagascar - Malawi - Malaysia - Maldives - Mali - Malta - Marshall Islands - Mauritania - Mauritius - Mayotte - Mexico - Micronesia, Fed. Sts. - Moldova - Monaco - Mongolia - Morocco - Mozambique - Myanmar - Namibia - Nepal - Netherlands - Netherlands Antilles - New Caledonia - New Zealand - Nicaragua - Niger - Nigeria - Northern Mariana Islands - Norway - Oman - Pakistan - Palau - Panama - Papua New Guinea - Paraguay - Peru - Philippines - Poland - Portugal - Puerto Rico - Qatar - Romania - Russian Federation - Rwanda - Samoa - San Marino - Sao Tome and Principe - Saudi Arabia - Senegal - Seychelles - Sierra Leone - Singapore - Slovak Republic - Slovenia - Solomon Islands - Somalia - South Africa - Spain - Sri Lanka - St. Kitts and Nevis - St. Lucia - St. Vincent and the Grenadines - Sudan - Suriname - Swaziland - Sweden - Switzerland - Syrian Arab Republic - Tajikistan - Tanzania - Thailand - Togo - Tonga - Trinidad and Tobago - Tunisia - Turkey - Turkmenistan - Uganda - Ukraine - United Arab Emirates - United Kingdom - United States - Uruguay - Uzbekistan - Vanuatu - Venezuela, RB - Vietnam - Virgin Islands (U.S.) - West Bank and Gaza - Yemen, Rep. - Yugoslavia, FR (Serbia/Montenegro) - Zambia - Zimbabwe

Kind of data

Aggregate data [agg]

Mode of data collection

Face-to-face [f2f]

Response rate

Sector Performance Indicators

Energy The energy sector is relatively well covered by the database, at least in terms of providing a relatively recent snapshot for the main policy areas. The best covered area is access where data are available for 2000 for about 61% of the 207 countries included in the database. The technical quality indicator is available for 60% of the countries, and at least one of the perceived quality indicators is available for 40% of the countries. Price information is available for about 41% of the countries, distinguishing between residential and non residential.

Water & Sanitation Because the sector is part of the Millennium Development Goals (MDGs), it enjoys a lot of effort on data generation in terms of the access rates. The WHO is the main engine behind this effort in collaboration with the multilateral and bilateral aid agencies. The coverage is actually quite high -some national, urban and rural information is available for 75 to 85% of the countries- but there are significant concerns among the research community about the fact that access rates have been measured without much consideration to the quality of access level. The data on technical quality are only available for 27% of the countries. There are data on perceived quality for roughly 39% of the countries but it cannot be used to qualify the information provided by the raw access rates (i.e. access 3 hours a day is not equivalent to access 24 hours a day).

Information and Communication Technology The ICT sector is probably the best covered among the infrastructure sub-sectors to a large extent thanks to the fact that the International Telecommunications Union (ITU) has taken on the responsibility to collect the data. ITU covers a wide spectrum of activity under the communications heading and its coverage ranges from 85 to 99% for all national access indicators. The information on prices needed to make assessments of affordability is also quite extensive since it covers roughly 85 to 95% of the 207 countries. With respect to quality, the coverage of technical indicators is over 88% while the information on perceived quality is only available for roughly 40% of the countries.

Transport The transport sector is possibly the least well covered in terms of the service orientation of infrastructure indicators. Regarding access, network density is the closest approximation to access to the service and is covered at a rate close to 90% for roads but only at a rate of 50% for rail. The relevant data on prices only cover about 30% of the sample for railways. Some type of technical quality information is available for 86% of the countries. Quality perception is only available for about 40% of the countries.

Institutional Reform Indicators

Electricity The data on electricity policy reform were collected from the following sources: ABS Electricity Deregulation Report (2004), AEI-Brookings telecommunications and electricity regulation database (2003), Bacon (1999), Estache and Gassner (2004), Estache, Trujillo, and Tovar de la Fe (2004), Global Regulatory Network Program (2004), Henisz et al. (2003), International Porwer Finance Review (2003-04), International Power and Utilities Finance Review (2004-05), Kikukawa (2004), Wallsten et al. (2004), World Bank Caribbean Infrastructure Assessment (2004), World Bank Global Energy Sector Reform in Developing Countries (1999), World Bank staff, and country regulators. The coverage for the three types of institutional indicators is quite good for the electricity sector. For regulatory institutions and private participation in generation and distribution, the coverage is about 80% of the 207 counties. It is somewhat lower on the market structure with only 58%.

Water & Sanitation The data on water policy reform were collected from the following sources: ABS Water and Waste Utilities of the World (2004), Asian Developing Bank (2000), Bayliss (2002), Benoit (2004), Budds and McGranahan (2003), Hall, Bayliss, and Lobina (2002), Hall and Lobina (2002), Hall, Lobina, and De La Mote (2002), Halpern (2002), Lobina (2001), World Bank Caribbean Infrastructure Assessment (2004), World Bank Sector Note on Water Supply and Sanitation for Infrastructure in EAP (2004), and World Bank staff. The coverage for institutional reforms in W&S is not as exhaustive as for the other utilities. Information on the regulatory institutions responsible for large utilities is available for about 67% of the countries. Ownership data are available for about 70% of the countries. There is no information on the market structure good enough to be reported here at this stage. In most countries small scale operators are important private actors but there is no systematic record of their existence. Most of the information available on their role and importance is only anecdotal.

Information and Communication Technology The report Trends in Telecommunications Reform from ITU (revised by World Bank staff) is the main source of information for this sector. The information on institutional reforms in the sector is however not as exhaustive as it is for its sector performance indicators. While the coverage on the regulatory institutions is 100%, it varies between 76 and 90% of the countries for more of the other indicators. Quite surprisingly also, in contrast to what is available for other sectors, it proved difficult to obtain data on the timing of reforms and of the creation of the regulatory agencies.

Transport Information on transport institutions and reforms is not systematically generated by any agency. Even though more data are needed to have a more comprenhensive picture of the transport sector, it was possible to collect data on railways policy reform from Janes World Railways (2003-04) and complement it with

Power plants of at least 1 MW are required to report data. Counties in gray had no utility scale (commercial) renewable electric generation. Distributed generation (for example, rooftop solar) is not included. Data is classified using the Jenks Natural Breaks method. Projection: NAD 1983 California (Teale) Albers (Intl Feet). Data Sources: California Energy Commission. Energy production data is from the Quarterly Fuel and Energy Report, and the Wind Generation Reporting System databases. Data is for 2021 and is current as of July 8, 2022. For more information, please contact Rebecca Vail at (916) 477-0738 or John Hingtgen at (916) 510-9747.