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!
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
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.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
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/).
CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
License information was derived automatically
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.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
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, and updated the protocol in a modification order on August 12, 2021. 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 city, town, and village level. Other UER datasets include energy use data reported at the county 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 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.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Japan Energy Consumption: Electric Utilities: Total Electricity (TE) data was reported at 81,911.541 kWh mn in Aug 2018. This records an increase from the previous number of 74,667.854 kWh mn for Jul 2018. Japan Energy Consumption: Electric Utilities: Total Electricity (TE) data is updated monthly, averaging 72,880.268 kWh mn from Mar 1998 (Median) to Aug 2018, with 246 observations. The data reached an all-time high of 90,570.000 kWh mn in Aug 2008 and a record low of 62,020.000 kWh mn in May 1999. Japan Energy Consumption: Electric Utilities: Total Electricity (TE) data remains active status in CEIC and is reported by Agency for Natural Resources and Energy. The data is categorized under Global Database’s Japan – Table JP.RB005: Energy Consumption.
Attribution-NonCommercial 2.0 (CC BY-NC 2.0)https://creativecommons.org/licenses/by-nc/2.0/
License information was derived automatically
The Global Wind Power Tracker (GWPT) is a worldwide dataset of utility-scale wind facilities. It includes wind farm phases with capacities of 10 megawatts (MW) or more. A wind project phase is generally defined as a group of one or more wind turbines that are installed under one permit, one power purchase agreement, and typically come online at the same time. The GWPT catalogs every wind farm phase at this capacity threshold of any status, including operating, announced, under development, under construction, shelved, cancelled, mothballed, or retired. Each wind farm included in the tracker is linked to a wiki page on the GEM wiki.
Global Energy Monitor’s Global Wind Power Tracker uses a two-level system for organizing information, consisting of both a database and wiki pages with further information. The database tracks individual wind farm phases and includes information such as project owner, status, installation type, and location. A wiki page for each wind farm is created within the Global Energy Monitor wiki. The database and wiki pages are updated annually.
The Global Wind Power Tracker data set draws on various public data sources, including:
Global Energy Monitor researchers perform data validation by comparing our dataset against proprietary and public data such as Platts World Energy Power Plant database and the World Resource Institute’s Global Power Plant Database, as well as various company and government sources.
For each wind farm, a wiki page is created on Global Energy Monitor’s wiki. Under standard wiki convention, all information is linked to a publicly-accessible published reference, such as a news article, company or government report, or a regulatory permit. In order to ensure data integrity in the open-access wiki environment, Global Energy Monitor researchers review all edits of project wiki pages.
To allow easy public access to the results, Global Energy Monitor worked with GreenInfo Network to develop a map-based and table-based interface using the Leaflet Open-Source JavaScript library. In the case of exact coordinates, locations have been visually determined using Google Maps, Google Earth, Wikimapia, or OpenStreetMap. For proposed projects, exact locations, if available, are from permit applications, or company or government documentation. If the location of a wind farm or proposal is not known, Global Energy Monitor identifies the most accurate location possible based on available information.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Electricity: Gross Generation: Non Utilities: Industry: Food Products: Goa data was reported at 0.200 GWh in 2022. This stayed constant from the previous number of 0.200 GWh for 2020. Electricity: Gross Generation: Non Utilities: Industry: Food Products: Goa data is updated yearly, averaging 0.200 GWh from Mar 1996 (Median) to 2022, with 25 observations. The data reached an all-time high of 16.540 GWh in 2003 and a record low of 0.000 GWh in 2009. Electricity: Gross Generation: Non Utilities: Industry: Food Products: Goa data remains active status in CEIC and is reported by Central Electricity Authority. The data is categorized under India Premium Database’s Energy Sector – Table IN.RBC035: Electricity: Gross Generation: Non Utilities: by States: Food Products.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Electricity: Gross Generation: Non Utilities: Industry: Iron and Steel: Daman and Diu data was reported at 0.000 GWh in 2022. This stayed constant from the previous number of 0.000 GWh for 2021. Electricity: Gross Generation: Non Utilities: Industry: Iron and Steel: Daman and Diu data is updated yearly, averaging 0.000 GWh from Mar 1996 (Median) to 2022, with 26 observations. The data reached an all-time high of 25.990 GWh in 2004 and a record low of 0.000 GWh in 2022. Electricity: Gross Generation: Non Utilities: Industry: Iron and Steel: Daman and Diu data remains active status in CEIC and is reported by Central Electricity Authority. The data is categorized under India Premium Database’s Energy Sector – Table IN.RBC037: Electricity: Gross Generation: Non Utilities: by States: Iron and Steel.
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
http://data.europa.eu/eli/dec/2011/833/ojhttp://data.europa.eu/eli/dec/2011/833/oj
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
An appropriate deployment of energy storage technologies is of primary importance for the transition towards an energy system. For that reason, this database has been created as a complement for the Study on energy storage - contribution to the security of the electricity supply in Europe.
The database includes three different approaches:
Energy storage technologies: All existing energy storage technologies with their characteristics.
Front of the meter facilities: List of all energy storage facilities in the EU-28, operational or in project, that are connected to the generation and the transmission grid with their characteristics.
Behind the meter energy storage: Installed capacity per country of all energy storage systems in the residential, commercial and industrial infrastructures.
The purpose of this database is to give a global view of all energy storage technologies. They are sorted in five categories, depending on the type of energy acting as a reservoir. Relevant types of data for each technology have been highlighted.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
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.
Open Government Licence - Canada 2.0https://open.canada.ca/en/open-government-licence-canada
License information was derived automatically
The Remote Communities Energy Database is a public resource that provides pertinent factual information about the generation and use of electricity and other energy sources for all remote communities in Canada. Communities are identified as remote communities if they are not currently connected to the North-American electrical grid nor to the piped natural gas network; and is a permanent or long-term (5 years or more) settlement with at least 10 dwellings. The Remote Communities Energy Database is the only national data source on energy in remote communities that is publically available on one centralized site. The Remote Communities Energy Database allows users to search and conduct analyses of remote communities and their energy context. Users are also able download the data from the Remote Communities Energy Database dataset in CSV (i.e., excel compatible) format. This data is collected from a number of sources including the remote communities themselves, local utilities, provincial and territorial government’s, Indigenous and Northern Affairs Canada (INAC), Statistics Canada, Natural Resources Canada (NRCan) and various other stakeholders.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
This database underpins the analysis in the report “More Power to India: The Challenge of Electricity Distribution”. 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.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Electricity: Gross Generation: Non Utilities: Industry: Paper: Uttarakhand data was reported at 636.240 GWh in 2022. This records an increase from the previous number of 512.560 GWh for 2021. Electricity: Gross Generation: Non Utilities: Industry: Paper: Uttarakhand data is updated yearly, averaging 346.690 GWh from Mar 2002 (Median) to 2022, with 20 observations. The data reached an all-time high of 636.240 GWh in 2022 and a record low of 0.000 GWh in 2005. Electricity: Gross Generation: Non Utilities: Industry: Paper: Uttarakhand data remains active status in CEIC and is reported by Central Electricity Authority. The data is categorized under India Premium Database’s Energy Sector – Table IN.RBC043: Electricity: Gross Generation: Non Utilities: by States: Paper.
Attribution-NonCommercial 2.0 (CC BY-NC 2.0)https://creativecommons.org/licenses/by-nc/2.0/
License information was derived automatically
The Global Solar Power Tracker is a worldwide dataset of utility-scale solar PV facilities. It includes solar farm phases with capacities of 20 megawatts (MW) or more (10 MW or more in Arabic-speaking countries). A solar project phase is generally defined as a group of one or more solar units that are installed under one permit, one power purchase agreement, and typically come online at the same time. The Global Solar Power Tracker catalogs every solar farm phase at these capacity thresholds of any status, including operating, announced, under development, under construction, shelved, cancelled, mothballed, or retired. Each solar farm included in the tracker is linked to a wiki page on the GEM wiki.
Global Energy Monitor’s Global Solar Power Tracker uses a two-level system for organizing information, consisting of both a database and wiki pages with further information. The database tracks individual solar farm phases and includes information such as project owner, status, and location. A wiki page for each solar farm is created within the Global Energy Monitor wiki. The database and wiki pages are updated annually.
The Global Solar Power Tracker data set draws on various public data sources, including: - Government data on individual power solar farms (such as India Central Electricity Authority’s “Plant Wise Details of All India Renewable Energy Projects” and the U.S. EIA 860 Electric Generator Inventory), country energy and resource plans, and government websites tracking solar farm permits and applications; - Reports by power companies (both state-owned and private); - News and media reports; - Local non-governmental organizations tracking solar farms or permits.
For each solar farm, a wiki page is created on Global Energy Monitor’s wiki. Under standard wiki convention, all information is linked to a publicly-accessible published reference, such as a news article, company or government report, or a regulatory permit. In order to ensure data integrity in the open-access wiki environment, Global Energy Monitor researchers review all edits of project wiki pages.
To allow easy public access to the results, Global Energy Monitor worked with GreenInfo Network to develop a map-based and table-based interface using the Leaflet Open-Source JavaScript library. In the case of exact coordinates, locations have been visually determined using Google Maps, Google Earth, Wikimapia, or OpenStreetMap. For proposed projects, exact locations, if available, are from permit applications, or company or government documentation. If the location of a solar farm or proposal is not known, Global Energy Monitor identifies the most accurate location possible based on available information.
Estache and Goicoechea present an infrastructure database that was assembled from multiple sources. Its main purposes are: (i) to provide a snapshot of the sector as of the end of 2004; and (ii) to facilitate quantitative analytical research on infrastructure sectors. The related working paper includes definitions, source information and the data available for 37 performance indicators that proxy access, affordability and quality of service (most recent data as of June 2005). Additionally, the database includes a snapshot of 15 reform indicators across infrastructure sectors.
This is a first attempt, since the effort made in the World Development Report 1994, at generating a database on infrastructure sectors and it needs to be recognized as such. This database is not a state of the art output—this is being worked on by sector experts on a different time table. The effort has however generated a significant amount of new information. The database already provides enough information to launch a much more quantitative debate on the state of infrastructure. But much more is needed and by circulating this information at this stage, we hope to be able to generate feedback and fill the major knowledge gaps and inconsistencies we have identified.
The database covers the following countries: - Afghanistan - Albania - Algeria - American Samoa - Andorra - Angola - Antigua and Barbuda - Argentina - Armenia - Aruba - Australia - Austria - Azerbaijan - Bahamas, The - Bahrain - Bangladesh - Barbados - Belarus - Belgium - Belize - Benin - Bermuda - Bhutan - Bolivia - Bosnia and Herzegovina - Botswana - Brazil - Brunei - Bulgaria - Burkina Faso - Burundi - Cambodia - Cameroon - Canada - Cape Verde - Cayman Islands - Central African Republic - Chad - Channel Islands - Chile - China - Colombia - Comoros - Congo, Dem. Rep. - Congo, Rep. - Costa Rica - Cote d'Ivoire - Croatia - Cuba - Cyprus - Czech Republic - Denmark - Djibouti - Dominica - Dominican Republic - Ecuador - Egypt, Arab Rep. - El Salvador - Equatorial Guinea - Eritrea - Estonia - Ethiopia - Faeroe Islands - Fiji - Finland - France - French Polynesia - Gabon - Gambia, The - Georgia - Germany - Ghana - Greece - Greenland - Grenada - Guam - Guatemala - Guinea - Guinea-Bissau - Guyana - Haiti - Honduras - Hong Kong, China - Hungary - Iceland - India - Indonesia - Iran, Islamic Rep. - Iraq - Ireland - Isle of Man - Israel - Italy - Jamaica - Japan - Jordan - Kazakhstan - Kenya - Kiribati - Korea, Dem. Rep. - Korea, Rep. - Kuwait - Kyrgyz Republic - Lao PDR - Latvia - Lebanon - Lesotho - Liberia - Libya - Liechtenstein - Lithuania - Luxembourg - Macao, China - Macedonia, FYR - Madagascar - Malawi - Malaysia - Maldives - Mali - Malta - Marshall Islands - Mauritania - Mauritius - Mayotte - Mexico - Micronesia, Fed. Sts. - Moldova - Monaco - Mongolia - Morocco - Mozambique - Myanmar - Namibia - Nepal - Netherlands - Netherlands Antilles - New Caledonia - New Zealand - Nicaragua - Niger - Nigeria - Northern Mariana Islands - Norway - Oman - Pakistan - Palau - Panama - Papua New Guinea - Paraguay - Peru - Philippines - Poland - Portugal - Puerto Rico - Qatar - Romania - Russian Federation - Rwanda - Samoa - San Marino - Sao Tome and Principe - Saudi Arabia - Senegal - Seychelles - Sierra Leone - Singapore - Slovak Republic - Slovenia - Solomon Islands - Somalia - South Africa - Spain - Sri Lanka - St. Kitts and Nevis - St. Lucia - St. Vincent and the Grenadines - Sudan - Suriname - Swaziland - Sweden - Switzerland - Syrian Arab Republic - Tajikistan - Tanzania - Thailand - Togo - Tonga - Trinidad and Tobago - Tunisia - Turkey - Turkmenistan - Uganda - Ukraine - United Arab Emirates - United Kingdom - United States - Uruguay - Uzbekistan - Vanuatu - Venezuela, RB - Vietnam - Virgin Islands (U.S.) - West Bank and Gaza - Yemen, Rep. - Yugoslavia, FR (Serbia/Montenegro) - Zambia - Zimbabwe
Aggregate data [agg]
Face-to-face [f2f]
Sector Performance Indicators
Energy The energy sector is relatively well covered by the database, at least in terms of providing a relatively recent snapshot for the main policy areas. The best covered area is access where data are available for 2000 for about 61% of the 207 countries included in the database. The technical quality indicator is available for 60% of the countries, and at least one of the perceived quality indicators is available for 40% of the countries. Price information is available for about 41% of the countries, distinguishing between residential and non residential.
Water & Sanitation Because the sector is part of the Millennium Development Goals (MDGs), it enjoys a lot of effort on data generation in terms of the access rates. The WHO is the main engine behind this effort in collaboration with the multilateral and bilateral aid agencies. The coverage is actually quite high -some national, urban and rural information is available for 75 to 85% of the countries- but there are significant concerns among the research community about the fact that access rates have been measured without much consideration to the quality of access level. The data on technical quality are only available for 27% of the countries. There are data on perceived quality for roughly 39% of the countries but it cannot be used to qualify the information provided by the raw access rates (i.e. access 3 hours a day is not equivalent to access 24 hours a day).
Information and Communication Technology The ICT sector is probably the best covered among the infrastructure sub-sectors to a large extent thanks to the fact that the International Telecommunications Union (ITU) has taken on the responsibility to collect the data. ITU covers a wide spectrum of activity under the communications heading and its coverage ranges from 85 to 99% for all national access indicators. The information on prices needed to make assessments of affordability is also quite extensive since it covers roughly 85 to 95% of the 207 countries. With respect to quality, the coverage of technical indicators is over 88% while the information on perceived quality is only available for roughly 40% of the countries.
Transport The transport sector is possibly the least well covered in terms of the service orientation of infrastructure indicators. Regarding access, network density is the closest approximation to access to the service and is covered at a rate close to 90% for roads but only at a rate of 50% for rail. The relevant data on prices only cover about 30% of the sample for railways. Some type of technical quality information is available for 86% of the countries. Quality perception is only available for about 40% of the countries.
Institutional Reform Indicators
Electricity The data on electricity policy reform were collected from the following sources: ABS Electricity Deregulation Report (2004), AEI-Brookings telecommunications and electricity regulation database (2003), Bacon (1999), Estache and Gassner (2004), Estache, Trujillo, and Tovar de la Fe (2004), Global Regulatory Network Program (2004), Henisz et al. (2003), International Porwer Finance Review (2003-04), International Power and Utilities Finance Review (2004-05), Kikukawa (2004), Wallsten et al. (2004), World Bank Caribbean Infrastructure Assessment (2004), World Bank Global Energy Sector Reform in Developing Countries (1999), World Bank staff, and country regulators. The coverage for the three types of institutional indicators is quite good for the electricity sector. For regulatory institutions and private participation in generation and distribution, the coverage is about 80% of the 207 counties. It is somewhat lower on the market structure with only 58%.
Water & Sanitation The data on water policy reform were collected from the following sources: ABS Water and Waste Utilities of the World (2004), Asian Developing Bank (2000), Bayliss (2002), Benoit (2004), Budds and McGranahan (2003), Hall, Bayliss, and Lobina (2002), Hall and Lobina (2002), Hall, Lobina, and De La Mote (2002), Halpern (2002), Lobina (2001), World Bank Caribbean Infrastructure Assessment (2004), World Bank Sector Note on Water Supply and Sanitation for Infrastructure in EAP (2004), and World Bank staff. The coverage for institutional reforms in W&S is not as exhaustive as for the other utilities. Information on the regulatory institutions responsible for large utilities is available for about 67% of the countries. Ownership data are available for about 70% of the countries. There is no information on the market structure good enough to be reported here at this stage. In most countries small scale operators are important private actors but there is no systematic record of their existence. Most of the information available on their role and importance is only anecdotal.
Information and Communication Technology The report Trends in Telecommunications Reform from ITU (revised by World Bank staff) is the main source of information for this sector. The information on institutional reforms in the sector is however not as exhaustive as it is for its sector performance indicators. While the coverage on the regulatory institutions is 100%, it varies between 76 and 90% of the countries for more of the other indicators. Quite surprisingly also, in contrast to what is available for other sectors, it proved difficult to obtain data on the timing of reforms and of the creation of the regulatory agencies.
Transport Information on transport institutions and reforms is not systematically generated by any agency. Even though more data are needed to have a more comprenhensive picture of the transport sector, it was possible to collect data on railways policy reform from Janes World Railways (2003-04) and complement it with
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!