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.

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!

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.

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 ZIP Code level collected under a data protocol in effect between 2016 and 2021. Other UER datasets include energy use data reported at the city, town, village, and county 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-ZIP-Code-Energy-Us/g2x3-izm4. 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 accelerate economic growth. 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)

Note: Find data at source. ・ 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.

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

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.

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 county level level collected under a data protocol in effect between 2016 and 2021. Other UER datasets include energy use data reported at the city, town, and village, 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-County-Energy-Use-/46pe-aat9.

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 accelerate economic growth. 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.

This dataset, compiled by NREL using data from Ventyx and the U.S. Energy Information Administration dataset 861, provides average residential, commercial and industrial electricity rates by zip code for both investor owned utilities (IOU) and non-investor owned utilities in Utah. Note: the file includes average rates for each utility, but not the detailed rate structure data found in the OpenEI U.S. Utility Rate Database. A more recent version of this data is also available through the NREL Utility Rate API with more search options. This data was released by NREL/Ventyx in February 2011.

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.

Electricity Consumption: Ind: Light Engineering: Delhi data was reported at 2.200 GWh in 2023. This stayed constant from the previous number of 2.200 GWh for 2022. Electricity Consumption: Ind: Light Engineering: Delhi data is updated yearly, averaging 0.000 GWh from Mar 1996 (Median) to 2023, with 27 observations. The data reached an all-time high of 2.200 GWh in 2023 and a record low of 0.000 GWh in 2020. Electricity Consumption: Ind: Light Engineering: Delhi data remains active status in CEIC and is reported by Central Electricity Authority. The data is categorized under Global Database’s India – Table IN.RBE030: Electricity: Consumption: Non Utilities: NCT of Delhi.

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.

NREL has assembled a list of U.S. retail electricity tariffs and their associated demand charge rates for the Commercial and Industrial sectors. The data was obtained from the Utility Rate Database. Keep the following information in mind when interpreting the data: (1) These data were interpreted and transcribed manually from utility tariff sheets, which are often complex. It is a certainty that these data contain errors, and therefore should only be used as a reference. Actual utility tariff sheets should be consulted if an action requires this type of data. (2) These data only contains tariffs that were entered into the Utility Rate Database. Since not all tariffs are designed in a format that can be entered into the Database, this list is incomplete - it does not contain all tariffs in the United States. (3) These data may have changed since this list was developed (4) Many of the underlying tariffs have additional restrictions or requirements that are not represented here. For example, they may only be available to the agricultural sector or closed to new customers. (5) If there are multiple demand charge elements in a given tariff, the maximum demand charge is the sum of each of the elements at any point in time. Where tiers were present, the highest rate tier was assumed. The value is a maximum for the year, and may be significantly different from demand charge rates at other times in the year. Utility Rate Database: https://openei.org/wiki/Utility_Rate_Database

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 at the ZIP Code level. Other UER datasets include energy use data reported at the city, town, village, and county 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.

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.

This database contains information about India's Power Sector Review for 2000-2012.The database is a collection of primary and secondary data on the Indian power sector, collected at the utility and state levels. It covers 87 power utilities and 29 states and spreads over the years 2003 to 2011 across dimensions such as operational and financial performance, market structure, implementation of reforms and corporate and regulatory governance.

Here, we present a database which collates historical, current, and future cost and performance data and assumptions for wind power generation from the open literature. Wind energy supplies 7% of global electricity, and production has grown three-fold in the decade to 2022. The data are global in scope but with regional and national specificity, covers the years 2015 through to 2050, and span 1506 datapoints from 28 sources.

The database enables modellers to select and justify model input data and provides a benchmark for comparing assumptions and projections to other sources across the literature to validate model inputs and outputs. It is designed to be easily updated with new sources of data, ensuring its utility, comprehensiveness, and broad applicability over time. Technoeconomic data on utility-scale wind energy was collected from websites, reports, academic articles and databases of national and international organisations.

The US Federal Energy Regulatory Commission (FERC) Form 1 database, covering the years 1994-2018. Converted from a large collection of annual Microsoft Visual FoxPro databases into a single combined SQLite database. See the README.md file for details.