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!

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.

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 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 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

LinkOut is a service that allows you to link directly from PubMed and other NCBI databases to a wide range of information and services beyond the NCBI systems. LinkOut aims to facilitate access to relevant online resources in order to extend, clarify, and supplement information found in NCBI databases.

Third parties can link directly from PubMed and other Entrez database records to relevant Web-accessible resources beyond the Entrez system. Includes full-text publications, biological databases, consumer health information and research tools.

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 v2023.12.01 Data Release

This is a data release from the Public Utility Data Liberation (PUDL) project. It's the first data-only release we've published. All of the tables which were previously only available by using the PUDL software package to process the data we previously published in the PUDL SQLite database are now being written into the database itself. This should make it easier for people to access with minimal setup, using a variety of different tools: Python, R, DuckDB, and many others! We are still committed to keeping the data processing pipeline behind this data free and open and transparent, we just don't want everyone to have to install and work with that software it if all they want is the output data!

We are about to do a major reorganization of the database, renaming almost every table and number of columns. This data release is a snapshot of the database before all that change happens, and is meant to provide continuity for users who are already working with the database, so that they can access to all the final 2022 data and migrate to the new database structure at a time of their own choosing over the coming months. We will do another data release soon, containing data through 2022, but with the new table and column names.

Other PUDL v2023.12.01 Resources

• PUDL v2023.12.01 Release Notes
• PUDL v2023.12.01 Data Dictionary
• PUDL v2023.12.01 Documentation
• PUDL v2023.12.01 on Kaggle (Corresponds to v9 of the PUDL Project dataset)
• PUDL in the AWS Open Data Registry
• PUDL v2023.12.01 in a free, public AWS S3 bucket: s3://pudl.catalyst.coop/v2023.12.01/
• PUDL v2023.12.01 in a requester-pays GCS bucket: gs://pudl.catalyst.coop/v2023.12.01/

PUDL v2023.12.01 Software Release

This is the software that was used to produce the data release. It is not necessary to work with the data, but it's linked here to provide transparency and provenance:

• Zenodo archive of the GitHub repository
• PUDL v2023.12.01 release tag on GitHub
• PUDL v2023.12.1 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
• 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.

There are limited open source data available for determining water production/treatment and required energy for cities across the United States. This database represents the culmination of a two-year effort to obtain data from cities across the United States via open records requests in order to determine the state of the U.S. urban energy-water nexus. Data were requested at the daily or monthly scale when available for 127 cities across the United States, represented by 253 distinct water and sewer districts. Data were requested from cities larger than 100,000 people and from each state. In the case of states that did not have cities that met these criteria, the largest cities in those states were selected. The resulting database represents a drinking water service population of 81.4 million and a wastewater service population of 86.2 million people. Average daily demands for the United States were calculated to be 560 liters per capita for drinking water and 500 liters per capita of wastewater. The embedded energy within each of these resources is 340 kWh/1000 m3 and 430 kWh/1000 m3, respectively. Drinking water data at the annual scale are available for production volume (89 cities) and for embedded energy (73 cities). Annual wastewater data are available for treated volume (104 cities) and embedded energy (90 cities). Monthly data are available for drinking water volume and embedded energy (73 and 56 cities) and wastewater volume and embedded energy (88 and 70 cities). Please see the two related papers for this metadata are included with this submission. Each folder name is a city that contributed data to the collection effort (City+State Abbreviation). Within each folder is a .csv file with drinking water and wastewater volume and energy data. A READ-ME file within each folder details the contents of the folder within any relevant information pertaining to data collection. Data are on the order of a monthly timescale when available, and yearly if not. Please cite the following papers when using the database: Chini, C.M. and Stillwell, A.S. (2017). The State of U.S. Urban Water: Data and the Energy-Water Nexus. Water Resources Research. 54(3). DOI: https://doi.org/10.1002/2017WR022265 Chini, C.M., and Stillwell, A. (2016). Where are all the data? The case for a comprehensive water and wastewater utility database. Journal of Water Resources Planning and Management. 143(3). DOI: 10.1061/(ASCE)WR.1943-5452.0000739

Database of Short Genetic Variations (dbSNP) contains human single nucleotide variations, microsatellites, and small-scale insertions and deletions along with publication, population frequency, molecular consequence, and genomic and RefSeq mapping information for both common variations and clinical mutations.

Contains Petroleum Wells.

Populated from original well completion reports.

This is a different dataset from GEDIS boreholes (purpose = petroleum). The wells in both datasets overlap in most cases. This dataset is actively maintained.

This map is related to HB – 143 § 33.2-280.2 (Effective January 1, 2025) Utility work database which stipulates The Virginia Department of Transportation map any permits issued to utility companies for work in a residential neighborhood . § 33.2-280.2. (Effective January 1, 2025) Utility work database.A. As used in this section:"Service connection" means any utility facility installed overhead or underground between a distribution main, pipelines, conduits, lines, wires, or other sources of supply and the premises of the individual customer."Utility work" means the construction, installation, removal, or substantial maintenance of a privately, publicly, or cooperatively owned line, facility, or system for producing, transmitting, or distributing telecommunications, cable television, electricity, gas, oil, petroleum products, water, steam, storm water not connected with highway drainage, or any other similar commodity, including any fire or police signal system. "Utility work" does not include emergency maintenance or repairs or any work directly related to any individual service connection or service drop.B. The Department shall establish and maintain a publicly accessible database and map of all utility work that has been approved by the Department and will occur within a highway right-of-way in a residential neighborhood, as specified by the utility. Such database shall include the location where such work will occur, the start date of such work, the projected end date of such work, the company administering such work, and any other relevant information; however, under no circumstances shall such database and map provide information on any (i) utility work within a right-of-way not maintained by the Department; (ii) critical utility infrastructure, as designated by the utility, that, upon disclosure, has the potential to jeopardize security or critical services, including Critical Energy Infrastructure Information and Controlled Unclassified Information; or (iii) information the permittee has designated as confidential. Such information shall be available in the database at least seven days prior to the start date of any such utility work and shall be deleted from such database 90 days after the completion of such work.

Taupō District Council stormwater point layer derived from the AssetFinda database. Stormwater point assets include grates, manholes, soakholes, inlets and outlets.Selected asset inventory data from the Taupō District council AssetFinda database has been made available for download to the public. Note that the AssetFinda database is a live database with updates and modifications to asset information occurring on a frequent basis. Taupō District Council does not make any representation or give any warranty as to the accuracy or exhaustiveness of the AssetFinda data released for public download. The data provided is indicative only and does not purport to be a complete database of all information in Taupō District Council's possession or control. Taupō District Council shall not be liable for any loss, damage, cost or expense (whether direct or indirect) arising from reliance upon or use of any data provided, or Council's failure to provide this data.While you are free to crop, export and repurpose the data, we ask that you attribute the Taupō District Council and clearly state that your work is a derivative and not the authoritative data source. Please include this statement when distributing any work derived from this data:This work is a derivative of the data in the Taupō District Council AssetFinda database; the provided information may be updated at any time, and may be, at times, out of date, inaccurate and/or incomplete.

Database of Genomic Structural Variation (dbVar) is NCBI's database of human genomic Structural Variation — large variants >50 bp including insertions, deletions, duplications, inversions, mobile elements, translocations, and complex variants.

Database of Genotype and Phenotype (dbGaP) was developed to archive and distribute the data and results from studies that have investigated the interaction of genotype and phenotype in Humans.

This database contains unit cost information for different components that may be used to integrate distributed photovotaic (D-PV) systems onto distribution systems. Some of these upgrades and costs may also apply to integration of other distributed energy resources (DER). Which components are required, and how many of each, is system-specific and should be determined by analyzing the effects of distributed PV at a given penetration level on the circuit of interest in combination with engineering assessments on the efficacy of different solutions to increase the ability of the circuit to host additional PV as desired. The current state of the distribution system should always be considered in these types of analysis.

The data in this database was collected from a variety of utilities, PV developers, technology vendors, and published research reports. Where possible, we have included information on the source of each data point and relevant notes. In some cases where data provided is sensitive or proprietary, we were not able to specify the source, but provide other information that may be useful to the user (e.g. year, location where equipment was installed). NREL has carefully reviewed these sources prior to inclusion in this database.

Additional information about the database, data sources, and assumptions is included in the "Unit_cost_database_guide.doc" file included in this submission. This guide provides important information on what costs are included in each entry. Please refer to this guide before using the unit cost database for any purpose.

The United States Wind Turbine Database (USWTDB) provides the locations of land-based and offshore wind turbines in the United States, corresponding wind project information, and turbine technical specifications. Wind turbine records are collected and compiled from various public and private sources, digitized and position-verified from aerial imagery, and quality checked. The USWTDB is available for download in a variety of tabular and geospatial file formats, to meet a range of user/software needs. Dynamic web services are available for users that wish to access the USWTDB as a Representational State Transfer Services (RESTful) web service. Archived from https://energy.usgs.gov/uswtdb/

This archive contains raw input data for the Public Utility Data Liberation (PUDL) software developed by Catalyst Cooperative. It is organized into "https://specs.frictionlessdata.io/data-package/">Frictionless Data Packages. For additional information about this data and PUDL, see the following resources:

• The PUDL Repository on GitHub
• PUDL Documentation
• Other Catalyst Cooperative data archives

Taupō District Council stormwater pipe polyline layer derived from the AssetFinda database. Stormwater pipe assets include gravity mains, rising mains, service connections and lined channels. Selected asset inventory data from the Taupō District council AssetFinda database has been made available for download to the public. Note that the AssetFinda database is a live database with updates and modifications to asset information occurring on a frequent basis. Taupō District Council does not make any representation or give any warranty as to the accuracy or exhaustiveness of the AssetFinda data released for public download. The data provided is indicative only and does not purport to be a complete database of all information in Taupō District Council's possession or control. Taupō District Council shall not be liable for any loss, damage, cost or expense (whether direct or indirect) arising from reliance upon or use of any data provided, or Council's failure to provide this data.While you are free to crop, export and repurpose the data, we ask that you attribute the Taupō District Council and clearly state that your work is a derivative and not the authoritative data source. Please include this statement when distributing any work derived from this data:This work is a derivative of the data in the Taupō District Council AssetFinda database; the provided information may be updated at any time, and may be, at times, out of date, inaccurate and/or incomplete.

BD-L-TC - point objects of the transformators from the official carto-/topographic database. The BD-L-TC is a vector dataset at the scale 1:5000 which represents the earth surface's objects on the national territory, with attributes in german, french and english. Data transformed into INSPIRE data model Description copied from catalog.inspire.geoportail.lu.