This Time series data includes the Date, Time, Active power and Reactive power, Voltage, and Global intensity including the number of metering devices.

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

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.

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.

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/).

The underground utilities survey layer contains the extents of underground utilities survey completed to Main Roads specifications and standards for use in project planning, design, construction and asset management.This data is used for road investigation, planning, design, construction and asset management.The data within this layer is continually maintained and edited on a daily basis.Data Dictionary: https://bit.ly/3dxlVM0 Show full description

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.

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.

Supply and disposition characteristics of electric power are presented, such as generation, imports, exports, sales and others. Data are presented at the national and provincial levels, not all combinations are available. These data include estimates (Electricity quantity and Electricity value).

Monthly utility data for all City of Boston accounts. This data comes from Boston’s Enterprise Energy Management System. This software tool serves as the system of record for all municipal utility expenditures and energy/water use.

Global Data Analytics for Electric Utilities Market is segmented by Application (Grid stability_ Load forecasting_ Demand response_ Energy theft detection_ Asset performance_ Renewable integration), Type (Load forecasting tools_ Grid monitoring analytics_ Predictive maintenance platforms_ Consumer usage analytics_ Renewable energy forecasting_ Real-time fault analysis systems), and Geography (North America_ LATAM_ West Europe_Central & Eastern Europe_ Northern Europe_ Southern Europe_ East Asia_ Southeast Asia_ South Asia_ Central Asia_ Oceania_ MEA)

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.

Applications: Energy Utilities and Gaming Simulation - This dataset tracks real energy utilities application, usage, and online/mobile applications data from cities that have been renamed to futuristic Hellenic cities, while the user data have been altered and anonymized. - The dataset was based on 2014-2017 consumption data from utilities companies training datasets and was originally intended to be fused with multiple other datasets for a massive economy simulation. - The dataset can be used for training in actual energy utilities analyses but is also robust enough for other endeavors, one of which was to be used to simulate an energy economy for a realistic utilities management game.

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:

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 data shows the utilities grid for the City of Winchester, Virginia and in the areas where utilities are located outside the city limits.

Customer Data Access Portals for Utilities Market Outlook

According to our latest research for 2024, the global customer data access portals for utilities market size stands at USD 2.68 billion. With the sector witnessing strong digital transformation, the market is projected to grow at a robust CAGR of 13.2% from 2025 to 2033, reaching a forecasted value of USD 7.57 billion by 2033. This growth is primarily driven by the increasing need for utilities to enhance customer experience, streamline operations, and comply with evolving regulatory requirements around data transparency and energy consumption.

The surge in demand for customer data access portals for utilities is largely attributed to the global shift towards digitalization and smart infrastructure. Utility companies are rapidly adopting advanced digital platforms to provide customers with real-time access to data, including billing, usage, and service updates. This digital transformation is not only improving customer satisfaction but also enabling utilities to optimize their internal processes, reduce operational costs, and enhance grid management. Moreover, the integration of smart meters and IoT devices has further accelerated the need for robust data access solutions, allowing customers to make informed decisions about their consumption patterns and supporting utilities in demand-side management.

Another significant growth factor is the increasing regulatory focus on consumer rights and data transparency. Governments and regulatory bodies across North America, Europe, and Asia Pacific are mandating utilities to provide customers with easy access to their consumption data and billing information. These regulations are pushing utilities to invest in sophisticated customer data access portals that can securely manage and present large volumes of data. Additionally, the growing emphasis on energy efficiency and sustainability is encouraging utilities to offer value-added services through these portals, such as personalized energy-saving recommendations and carbon footprint tracking, further driving market expansion.

The proliferation of cloud-based solutions has also played a pivotal role in scaling the customer data access portals for utilities market. Cloud deployment offers utilities the flexibility, scalability, and cost-efficiency required to manage massive datasets and support a growing user base. Cloud-based portals facilitate seamless integration with existing utility systems and third-party platforms, enabling utilities to deliver a unified and intuitive customer experience. Furthermore, advancements in cybersecurity and data privacy technologies are bolstering the confidence of utilities and end-users in adopting cloud-based customer data portals, thereby accelerating market growth.

Regionally, North America leads the market, driven by early adoption of digital technologies, strong regulatory frameworks, and significant investments in smart grids. Europe follows closely, propelled by stringent data protection laws and aggressive sustainability targets. The Asia Pacific region is witnessing the fastest growth, fueled by rapid urbanization, infrastructure development, and government-led smart city initiatives. Latin America and the Middle East & Africa are gradually catching up, with utilities in these regions increasingly recognizing the benefits of digital customer engagement and data-driven operations.

Component Analysis

The component segment of the customer data access portals for utilities market is bifurcated into software and services, each playing a crucial role in the ecosystem. Software solutions form the backbone of these portals, providing utilities with the necessary tools to aggregate, process, and present customer data in an accessible format. These platforms are designed to handle vast amounts of real-time data, ensuring accuracy, security, and scalability. The growing demand for customized and user-friendly interfaces is prompting software vendors to continuously innovate, incorporating advanced analytics, AI-driven insights, and mobile compatibility to enhance user experience.

Service offerings, which include consulting, implementation, maintenance, and support, are equally vital for the successful deployment and operation of customer data access portals. Utilities often require expert guidance to navigate the complexities of integrating new digital solu

Summary of the NYS gas and electric utilities’ customer service performance indicators for each of the last three calendar years. Reported by the utilities on a uniform basis, these performance indicators allow comparative analysis of customer service, identification of overall trends in customer service, and identification of service deficiencies.

These districts are used to identify service areas for Power Companies.

Data on the consumption of utilities (electricity, thermal energy, natural gas, solid fuel, cold and hot water) by public health facilities and health management of the Kamiansk City Council