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.

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 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.

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.

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 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 by zip code for both investor owned utilities (IOU) and non-investor owned utilities. 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.

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).

This feature class represents electric power retail service territories. These are areas serviced by electric power utilities responsible for the retail sale of electric power to local customers, whether residential, industrial, or commercial. The following updates have been made since the previous release: 7 features added, numerous geometries improved, and geographic coverage expanded to include American Samoa, Guam, Northern Mariana Islands, and Virgin Islands.

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

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

Major electric utility lines covering the City of Raleigh jurisdiction. Features are derived from annual aerial photography updates. This layer is updated for a quarter of the city every year and is not a depiction of current conditions.Update Frequency: AnnuallyTime Period: Current as of last flight (see update date on individual features)

Graph and download economic data for Expenditures: Utilities, Fuels, and Public Services: All Consumer Units (CXUUTILSLB0101M) from 1984 to 2023 about consumer unit, public, utilities, fuels, expenditures, services, and USA.

Middlesex Water is a leading regulated water utility company that supplies drinking water to over 900,000 residents in New Jersey and Pennsylvania. Founded in 1859, the company has a rich history of providing essential services to its customers.

Today, Middlesex Water is committed to delivering high-quality water and excellent customer service. The company's data sets reflect its dedication to transparency and openness, offering insights into its operations, management, and infrastructure. Whether you're an analyst, researcher, or simply interested in learning more about the water industry, Middlesex Water's data provides a unique window into the company's activities and operations.

Utility level retail sales of electricity and associated revenue. Organized by reporting month, state, and by end-use sector, i.e., residential, commercial, industrial, and transportation. Based on Form EIA-826 data.

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 set contains data on the consumption of utilities (electric energy, thermal energy, natural gas, solid fuel, cold and hot water)

American Water Works Association is a leading organization in the water industry, dedicated to promoting the safety and reliability of water supplies. Founded in 1881, AWWA has a rich history of providing education, training, and resources to its members and the wider water community. With a global presence, AWWA serves as a valuable resource for water professionals, policymakers, and the public, advocating for the importance of clean water and sustainable water management practices.

Throughout its history, AWWA has been driven by its mission to provide reliable, safe, and sustainable water supplies to communities worldwide. The organization has achieved this through its diverse range of initiatives, including standards development, advocacy, education, and training programs. AWWA's work has a direct impact on the daily lives of millions of people, ensuring that they have access to clean water for drinking, hygiene, and sanitation.

According to Cognitive Market Research, the worldwide Energy and Utilities Analytics market size is USD 3.6 billion in 2024 and will expand at a compounded annual growth rate or CAGR of 16.78% from 2024 to 2031. Market Dynamics of Energy and Utilities Analytics Market

Key Drivers for Energy and Utilities Analytics Market

Increase in the use of analytics - An experienced data analyst may draw inferences from unstructured information, summarise results, and use visual aids to convey the entire narrative in an easy-to-understand manner. It is ensured that any business information is handled safely and that all procedures are in full compliance with applicable laws when a dedicated analyst is on board. The global market for energy & utility analytics is anticipated to be driven by this.
When some devices stay connected for ten years or more, the IoT connection landscape only slowly shifts. On the other hand, new Internet of Things technologies do affect the terrain over time. This would offer the worldwide energy and utility analytics industry greater opportunities.

Key Restraints for Energy and Utilities Analytics Market

The entire tech sector suffers from a skills gap. Still, operations roles are particularly badly affected because of how quickly things are changing and how much regular workforce expansion and upskilling is required. This is anticipated to limit market expansion.
The use of analytics solutions by energy and utility firms is facilitated by the requirement for precise and effective forecasting of power generation and consumption of energy.
Data Privacy and Security Issues hamper the market growth

Data privacy and security issues heavily impede the market for energy and utility analytics. These businesses collect large volumes of data to be analyzed, and the risk of data breaches and abuse is very high. The threat of breached sensitive data may discourage companies from embracing highly advanced analytics software. To counter these threats, energy and utility organizations must heavily invest in powerful security solutions that may be pricey and complicated. The cost of undertaking these protective steps, along with the continuing difficulties of staying in compliance with changing rules, can retard market growth and limit innovation in analytics technology. This market report encompasses news of new recent developments, trade regulations, import-export analysis, production analysis, value chain optimization, market share, effects of domestic and localized market players, examines opportunities in terms of emerging revenue pockets, market regulation changes, strategic market growth analysis, market size, category market growths, application niches and dominance, product approvals, product launches, geographic expansions, technological advancements in the market. To get more information about the market reach Data Bridge Market Research for an Analyst Brief, our experts will assist you in making an informed market decision to gain market growth.

Opportunities for Energy and Utilities Analytics

Growth of AI and Machine Learning Integration is boosting the market growth

One particular trend driving growth in the energy and utility analytics market is the convergence of artificial intelligence (AI) and machine learning (ML) technologies. These sophisticated analytical tools allow utilities to analyze huge volumes of data from smart meters and IoT devices, resulting in improved operational efficiency and predictive maintenance. For example, in August 2022, mCloud Technologies Corp., a pioneer in AI-driven asset management and ESG solutions, revealed a technology continuation partnership with Agnity Global Inc. This partnership will be concentrated on extending their successful collaboration, with emphasis on the enhanced delivery of innovative asset management solutions. By taking advantage of AI and sophisticated analytics, mCloud and Agnity will jointly build next-generation technologies that power operational excellence and enable sustainable behavior within the sector. Introduction of the Energy and Utilities Analytics Market

The term "energy and utility analytics" refers to data solutions that have a direct impact on corporate performance through cost reduction, risk detection, service improvement, and effective customer engagement. Energy and utility firms use these technologies to forecast demand, manage expenses, and make more strategic...

DescriptionThis layer contains regions representing the geographic extent of retail service provided by electric utilities in Colorado. Last Update2022Update FrequencyAs neededData OwnerDivision of Transportation DevelopmentData ContactCDOT Office of Innovative MobilityCollection MethodCDOT Office of Innovative MobilityProjectionNAD83 / UTM zone 13NCoverage AreaStatewideTemporalDisclaimer/LimitationsThere are no restrictions and legal prerequisites for using the data set. The State of Colorado assumes no liability relating to the completeness, correctness, or fitness for use of this data.

The Utilities Data Analytics industry has witnessed significant growth in recent years, driven by increasing demand for improved operational efficiency, customer engagement, and asset management. The market size reached XXX million in 2025 and is projected to expand at a CAGR of XX% during the forecast period (2025-2033). Growing adoption of advanced technologies such as IoT, AI, and machine learning, coupled with government initiatives to modernize utility infrastructure, fuels market expansion. The Utilities Data Analytics market is segmented by type (Energy Analytics, Customer Analytics, Asset Analytics, Operations Analytics, Financial Analytics) and application (Electricity, Water, Gas, Other). Energy Analytics holds a dominant market share due to increased adoption for energy optimization and demand forecasting. Additionally, the market is characterized by key industry players including AspenTech, Vertica, Deloitte, Engineered Intelligence, Heavy.ai, Cloudera, SAS, Oracle, Saviant, Loamics Suite, WNS, Adatis, Keyrus, KNIME, Voltaware, Tantalus, ATS, 4M Analytics, Seeq, TIBCO, Quantzig, SparkBeyond, Live Earth, and others. Geographically, North America and Asia Pacific account for significant market shares, with growing adoption of advanced metering infrastructure (AMI) and smart grid technologies contributing to regional growth.