The SDG Indicator 7.1.1: Access to Electricity, 2023 Release data set, part of the Sustainable Development Goal Indicators (SDGI) collection, measures the proportion of the population with access to electricity for a given statistical area. UN SDG 7 is "ensure access to affordable, reliable, sustainable and modern energy for all". Tracking SDG 7: The Energy Progress Report estimated that in 2019, 759 million people around the world lacked access to electricity. Moreover, due to current policies and the detrimental effects of the COVID-19 crisis, it is predicted that by 2030, 660 million people will still not have access to electricity, with a majority of these people residing in Sub-Saharan Africa. As one measure of progress towards SDG 7, the UN agreed upon SDG indicator 7.1.1. The indicator was computed as the proportion of WorldPop gridded population located within illuminated areas defined by annual VIIRS Nighttime Lights Version 2 (VNL V2) data. The SDG indicator 7.1.1 data set provides estimates for the proportion of population with access to electricity for 206 countries and 45,979 level 2 subnational Units. The data set is available at both national and level 2 subnational resolutions.
Over the past half a century, the world's electricity consumption has continuously grown, reaching approximately 27,000 terawatt-hours by 2023. Between 1980 and 2023, electricity consumption more than tripled, while the global population reached eight billion people. Growth in industrialization and electricity access across the globe have further boosted electricity demand. China's economic rise and growth in global power use Since 2000, China's GDP has recorded an astonishing 15-fold increase, turning it into the second-largest global economy, behind only the United States. To fuel the development of its billion-strong population and various manufacturing industries, China requires more energy than any other country. As a result, it has become the largest electricity consumer in the world. Electricity consumption per capita In terms of per capita electricity consumption, China and other BRIC countries are still vastly outpaced by developed economies with smaller population sizes. Iceland, with a population of less than half a million inhabitants, consumes by far the most electricity per person in the world. Norway, Qatar, Canada, and the United States also have among the highest consumption rates. Multiple contributing factors such as the existence of power-intensive industries, household sizes, living situations, appliance and efficiency standards, and access to alternative heating fuels determine the amount of electricity the average person requires in each country.
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Access to electricity is the percentage of population with access to electricity. Electrification data are collected from industry, national surveys and international sources.
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United States US: Access to Electricity: % of Population data was reported at 100.000 % in 2016. This stayed constant from the previous number of 100.000 % for 2015. United States US: Access to Electricity: % of Population data is updated yearly, averaging 100.000 % from Dec 1990 (Median) to 2016, with 27 observations. The data reached an all-time high of 100.000 % in 2016 and a record low of 100.000 % in 2016. United States US: Access to Electricity: % of Population data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s United States – Table US.World Bank.WDI: Energy Production and Consumption. Access to electricity is the percentage of population with access to electricity. Electrification data are collected from industry, national surveys and international sources.; ; World Bank, Sustainable Energy for All (SE4ALL) database from the SE4ALL Global Tracking Framework led jointly by the World Bank, International Energy Agency, and the Energy Sector Management Assistance Program.; Weighted average;
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This table expresses the use of renewable energy as gross final consumption of energy. Figures are presented in an absolute way, as well as related to the total energy use in the Netherlands. The total gross final energy consumption in the Netherlands (the denominator used to calculate the percentage of renewable energy per ‘Energy sources and techniques’) can be found in the table as ‘Total, including non-renewables’ and Energy application ‘Total’. The gross final energy consumption for the energy applications ‘Electricity’ and ‘Heat’ are also available. With these figures the percentages of the different energy sources and applications can be calculated; these values are not available in this table. The gross final energy consumption for ‘Transport’ is not available because of the complexity to calculate this. More information on this can be found in the yearly publication ‘Hernieuwbare energie in Nederland’.
Renewable energy is energy from wind, hydro power, the sun, the earth, heat from outdoor air and biomass. This is energy from natural processes that is replenished constantly.
The figures are broken down into energy source/technique and into energy application (electricity, heat and transport).
This table focuses on the share of renewable energy according to the EU Renewable Energy Directive. Under this directive, countries can apply an administrative transfer by purchasing renewable energy from countries that have consumed more renewable energy than the agreed target. For 2020, the Netherlands has implemented such a transfer by purchasing renewable energy from Denmark. This transfer has been made visible in this table as a separate energy source/technique and two totals are included; a total with statistical transfer and a total without statistical transfer.
Figures for 2020 and before were calculated based on RED I; in accordance with Eurostat these figures will not be modified anymore. Inconsistencies with other tables undergoing updates may occur.
Data available from: 1990
Status of the figures: This table contains definite figures up to and including 2022, figures for 2023 are revised provisional figures and figures for 2024 are provisional.
Changes as of July 2025: Compiling figures on solar electricity took more time than scheduled. Consequently, not all StatLine tables on energy contain the most recent 2024 data on production for solar electricity. This table contains the outdated data from June 2025. The most recent figures are 5 percent higher for 2024 solar electricity production. These figures are in these two tables (in Dutch): - StatLine - Zonnestroom; vermogen en vermogensklasse, bedrijven en woningen, regio - StatLine - Hernieuwbare energie; zonnestroom, windenergie, RES-regio Next update is scheduled in November 2025. From that moment all figures will be fully consistent again. We apologize for the inconvenience.
Changes as of june 2025: Figures for 2024 have been added.
Changes as of January 2025
Renewable cooling has been added as Energy source and technique from 2021 onwards, in accordance with RED II. Figures for 2020 and earlier follow RED I definitions, renewable cooling isn’t a part of these definitions.
The energy application “Heat” has been renamed to “Heating and cooling”, in accordance with RED II definitions.
RED II is the current Renewable Energy Directive which entered into force in 2021
Changes as of November 15th 2024 Figures for 2021-2023 have been adjusted. 2022 is now definitive, 2023 stays revised provisional. Because of new insights for windmills regarding own electricity use and capacity, figures on 2021 have been revised.
Changes as of March 2024: Figures of the total energy applications of biogas, co-digestion of manure and other biogas have been restored for 2021 and 2022. The final energy consumption of non-compliant biogas (according to RED II) was wrongly included in the total final consumption of these types of biogas. Figures of total biogas, total biomass and total renewable energy were not influenced by this and therefore not adjusted.
When will new figures be published? Provisional figures on the gross final consumption of renewable energy in broad outlines for the previous year are published each year in June. Revised provisional figures for the previous year appear each year in June.
In November all figures on the consumption of renewable energy in the previous year will be published. These figures remain revised provisional, definite figures appear in November two years after the reporting year. Most important (expected) changes between revised provisional figures in November and definite figures a year later are the figures on solar photovoltaic energy. The figures on the share of total energy consumption in the Netherlands could also still be changed by the availability of adjusted figures on total energy consumption.
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In 2015, the United Nations established 17 Sustainable Development Goals (SDGs), with Goal 7 focusing on ensuring access to affordable, reliable, and sustainable modern energy for all by 2030. By 2022, approximately 760 million people, or 1 in 11 globally still lacked electricity access according to Tracking SDG7 :The Energy Progress Report 2022, posing significant challenges to achieving this goal. Traditional survey methods for estimating the proportion of people with electricity access are often costly, infrequently updated, and hindered by the need for interpolation of historical data.
To address these challenges, this dataset employs a nighttime light remote sensing estimation framework that integrates DMSP-CCNL and NPP/VIIRS data with GlobPOP population data. This approach produces a global 0.1-degree grid and national-scale electricity access index (EAI) maps from 1992 to 2022.
The framework results' correlation coefficient (R) with World Bank survey data from 1992 to 2022 is 0.87, and the RMSE is 15.4, demonstrating its reliability at the national level. By effectively capturing geospatial changes, this dataset supports SDG 7.1.1 monitoring and offers valuable insights for policymakers to address electricity access disparities and promote sustainable energy transitions.
1. This dataset consists of 0.1-degree grid Electricity Access Index (EAI) data in GeoTIFF format, where each pixel value represents the proportion of the population with access to electricity within that area.
Example Filename: EAI_0dot1_Deg_WGS84_F32_1992
2. Aggregated EAI data at the national scale is provided in both Shapefile and CSV formats:
Fields include:
3. The pixel-level (30 arc-seconds) Electricity Accessed Population Density is provided in GeoTIFF format, as identified through nighttime light (NTL) data.
Example Filename: Elec_PopDen_WGS84_30arc_F32_1992
If you encounter any issues, please contact us via email at liu.luling.k2@s.mail.nagoya-u.ac.jp.
The source codes are publicly available at GitHub: https://github.com/lulingliu/EAI.
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Mexico MX: Access to Electricity: % of Population data was reported at 100.000 % in 2016. This records an increase from the previous number of 99.000 % for 2015. Mexico MX: Access to Electricity: % of Population data is updated yearly, averaging 98.007 % from Dec 1990 (Median) to 2016, with 27 observations. The data reached an all-time high of 100.000 % in 2016 and a record low of 93.146 % in 1992. Mexico MX: Access to Electricity: % of Population data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Mexico – Table MX.World Bank: Energy Production and Consumption. Access to electricity is the percentage of population with access to electricity. Electrification data are collected from industry, national surveys and international sources.; ; World Bank, Sustainable Energy for All (SE4ALL) database from the SE4ALL Global Tracking Framework led jointly by the World Bank, International Energy Agency, and the Energy Sector Management Assistance Program.; Weighted average;
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Dataset Description Title: Electricity Market Dataset for Long-Term Forecasting (2018–2024)
Overview: This dataset provides a comprehensive collection of electricity market data, focusing on long-term forecasting and strategic planning in the energy sector. The data is derived from real-world electricity market records and policy reports from Germany, specifically the Frankfurt region, a major European energy hub. It includes hourly observations spanning from January 1, 2018, to December 31, 2024, covering key economic, environmental, and operational factors that influence electricity market dynamics. This dataset is ideal for predictive modeling tasks such as electricity price forecasting, renewable energy integration planning, and market risk assessment.
Features Description Feature Name Description Type Timestamp The timestamp for each hourly observation. Datetime Historical_Electricity_Prices Hourly historical electricity prices in the Frankfurt market. Continuous (Float) Projected_Electricity_Prices Forecasted electricity prices (short, medium, long term). Continuous (Float) Inflation_Rates Hourly inflation rate trends impacting energy markets. Continuous (Float) GDP_Growth_Rate Hourly GDP growth rate trends for Germany. Continuous (Float) Energy_Market_Demand Hourly electricity demand across all sectors. Continuous (Float) Renewable_Investment_Costs Investment costs (capital and operational) for renewable energy projects. Continuous (Float) Fossil_Fuel_Costs Costs for fossil fuels like coal, oil, and natural gas. Continuous (Float) Electricity_Export_Prices Prices for electricity exports from Germany to neighboring regions. Continuous (Float) Market_Elasticity Sensitivity of electricity demand to price changes. Continuous (Float) Energy_Production_By_Solar Hourly solar energy production. Continuous (Float) Energy_Production_By_Wind Hourly wind energy production. Continuous (Float) Energy_Production_By_Coal Hourly coal-based energy production. Continuous (Float) Energy_Storage_Capacity Available storage capacity (e.g., batteries, pumped hydro). Continuous (Float) GHG_Emissions Hourly greenhouse gas emissions from energy production. Continuous (Float) Renewable_Penetration_Rate Percentage of renewable energy in total energy production. Continuous (Float) Regulatory_Policies Categorical representation of regulatory impact on electricity markets (e.g., Low, Medium, High). Categorical Energy_Access_Data Categorization of energy accessibility (Urban or Rural). Categorical LCOE Levelized Cost of Energy by source. Continuous (Float) ROI Return on investment for energy projects. Continuous (Float) Net_Present_Value Net present value of proposed energy projects. Continuous (Float) Population_Growth Population growth rate trends impacting energy demand. Continuous (Float) Optimal_Energy_Mix Suggested optimal mix of renewable, non-renewable, and nuclear energy. Continuous (Float) Electricity_Price_Forecast Predicted electricity prices based on various factors. Continuous (Float) Project_Risk_Analysis Categorical analysis of project risks (Low, Medium, High). Categorical Investment_Feasibility Indicator of the feasibility of energy investments. Continuous (Float) Use Cases Electricity Price Forecasting: Utilize historical and projected price trends to predict future electricity prices. Project Risk Classification: Categorize projects into risk levels for better decision-making. Optimal Energy Mix Analysis: Analyze the balance between renewable, non-renewable, and nuclear energy sources. Policy Impact Assessment: Study the effect of regulatory and market policies on energy planning. Long-Term Strategic Planning: Provide insights into investment feasibility, GHG emission reduction, and energy market dynamics. Acknowledgment This dataset is based on publicly available records and market data specific to the Frankfurt region, Germany. The dataset is designed for research and educational purposes in energy informatics, computational intelligence, and long-term forecasting.
This map shows electricity access in Asia and the Pacific. The data source is from the International Energy Agency’s World Energy Outlook. The International Energy Agency’s World Energy Outlook first constructed a database on electrification rates for WEO-2002. The database once again was updated for WEO-2015, showing detailed data on national, urban and rural electrification.
The general paucity of data on electricity access means that it must be gathered through a combination of sources, including: IEA energy statistics; a network of contacts spanning governments, multilateral development banks and country-level representatives of various international organisations; and, other publicly available statistics, such as US Agency for International Development (USAID) supported DHS survey data, the World Bank’s Living Standards Measurement Surveys (LSMS), the UN Economic Commission for Latin America and the Caribbean’s (ECLAC) statistical publications, and data from national statistics agencies. In the small number of cases where no data could be provided through these channels other sources were used. If electricity access data for 2013 was not available, data for the latest available year was used.
For many countries, data on the urban and rural breakdown was collected, but if not available an estimate was made on the basis of pre-existing data or a comparison to the average correlation between urban and national electrification rates. Often only the percentage of households with a connection is known and assumptions about an average household size are used to determine access rates as a percentage of the population. To estimate the number of people without access, population data comes from OECD statistics in conjunction with the United Nations Population Division reports World Urbanization Prospects: the 2014 Revision Population Database, and World Population Prospects: the 2012 Revision. Electricity access data is adjusted to be consistent with demographic patterns of urban and rural population. Due to differences in definitions and methodology from different sources, data quality may vary from country to country. Where country data appeared contradictory, outdated or unreliable, the IEA Secretariat made estimates based on cross-country comparisons and earlier surveys.
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Georgia GE: Access to Electricity: % of Population data was reported at 100.000 % in 2016. This records an increase from the previous number of 99.993 % for 2015. Georgia GE: Access to Electricity: % of Population data is updated yearly, averaging 98.932 % from Dec 1990 (Median) to 2016, with 27 observations. The data reached an all-time high of 100.000 % in 2016 and a record low of 97.334 % in 1990. Georgia GE: Access to Electricity: % of Population data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Georgia – Table GE.World Bank: Energy Production and Consumption. Access to electricity is the percentage of population with access to electricity. Electrification data are collected from industry, national surveys and international sources.; ; World Bank, Sustainable Energy for All (SE4ALL) database from the SE4ALL Global Tracking Framework led jointly by the World Bank, International Energy Agency, and the Energy Sector Management Assistance Program.; Weighted average;
Global primary energy consumption has increased dramatically in recent years and is projected to continue to increase until 2045. Only renewable energy consumption is expected to increase between 2045 and 2050 and reach almost 30 percent of the global energy consumption. Energy consumption by country The distribution of energy consumption globally is disproportionately high among some countries. China, the United States, and India were by far the largest consumers of primary energy globally. On a per capita basis, Qatar, Singapore, the United Arab Emirates, and Iceland had the highest per capita energy consumption. Renewable energy consumption Over the last two decades, renewable electricity consumption has increased to reach over 48.8 exajoules in 2024. Among all countries globally, China had the largest installed renewable energy capacity as of that year, followed by the United States.
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El Salvador SV: Access to Electricity: % of Population data was reported at 98.619 % in 2016. This records an increase from the previous number of 95.400 % for 2015. El Salvador SV: Access to Electricity: % of Population data is updated yearly, averaging 87.357 % from Dec 1990 (Median) to 2016, with 27 observations. The data reached an all-time high of 98.619 % in 2016 and a record low of 69.608 % in 1991. El Salvador SV: Access to Electricity: % of Population data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s El Salvador – Table SV.World Bank: Energy Production and Consumption. Access to electricity is the percentage of population with access to electricity. Electrification data are collected from industry, national surveys and international sources.; ; World Bank, Sustainable Energy for All (SE4ALL) database from the SE4ALL Global Tracking Framework led jointly by the World Bank, International Energy Agency, and the Energy Sector Management Assistance Program.; Weighted average;
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The “Sustainable Energy for all (SE4ALL)” initiative, launched in 2010 by the UN Secretary General, established three global objectives to be accomplished by 2030: to ensure universal access to modern energy services, to double the global rate of improvement in global energy efficiency, and to double the share of renewable energy in the global energy mix. SE4ALL database supports this initiative and provides country level historical data for access to electricity and non-solid fuel; share of renewable energy in total final energy consumption by technology; and energy intensity rate of improvement
This layer displays the percentage of the population with access to electricity. Source: The World Bank
This dataset displays the amount of hydroelectric power that was consumed on a nation level. The dataset covers the time period spanning from 1980 to 2005. Data is available for 200+ countries. This data is scalled at: Billion Kilowatt hours. Data references:Energy Information Administration International Energy Annual 2005 Table Posted: September 11, 2007 Next Update: June 2008 This data is available directly at: http://www.eia.doe.gov/fuelrenewable.html Access Date: November 8, 2007.
All the data for this dataset is provided from CARMA: Data from CARMA (www.carma.org) This dataset provides information about Power Plant emissions and power plant types around the world by country. This information was obtained by CARMA for the past (2000 Annual Report), the present (2007 data), and the future. CARMA determine data presented for the future to reflect planned plant construction, expansion, and retirement. The location of the countries is placed by lat/lon coordinates that was provided by CARMA. The dataset provides the country, region type, plant count, and lat/lon for each individual country. The dataset reports for the three time periods: Intensity: Pounds of CO2 emitted per megawatt-hour of electricity produced. Energy: Annual megawatt-hours of electricity produced. Carbon: Annual carbon dioxide (CO2) emissions. The units are short or U.S. tons. Multiply by 0.907 to get metric tons. % Fossil: The percentage of total electricity that is generated by the combustion of coal, oil, or natural gas. % Hydro: The percentage of total electricity that is generated by hydroelectric power facilities. % Nuclear: The percentage of total electricity that is generated by nuclear power facilities. % Other Renewable: The percentage of total electricity that is generated by the use of wind, solar, biomass, geothermal, captured heat, or hydrogen energy. The objective of CARMA.org is to equip individuals with the information they need to forge a cleaner, low-carbon future. By providing complete information for both clean and dirty power producers, CARMA hopes to influence the opinions and decisions of consumers, investors, shareholders, managers, workers, activists, and policymakers. CARMA builds on experience with public information disclosure techniques that have proven successful in reducing traditional pollutants. Please see carma.org for more information
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Ivory Coast CI: Access to Electricity: % of Population data was reported at 64.300 % in 2016. This records an increase from the previous number of 64.086 % for 2015. Ivory Coast CI: Access to Electricity: % of Population data is updated yearly, averaging 51.400 % from Dec 1990 (Median) to 2016, with 27 observations. The data reached an all-time high of 64.300 % in 2016 and a record low of 36.500 % in 1994. Ivory Coast CI: Access to Electricity: % of Population data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Ivory Coast – Table CI.World Bank: Energy Production and Consumption. Access to electricity is the percentage of population with access to electricity. Electrification data are collected from industry, national surveys and international sources.; ; World Bank, Sustainable Energy for All (SE4ALL) database from the SE4ALL Global Tracking Framework led jointly by the World Bank, International Energy Agency, and the Energy Sector Management Assistance Program.; Weighted average;
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Kazakhstan KZ: Access to Electricity: Rural: % of Population data was reported at 100.000 % in 2016. This stayed constant from the previous number of 100.000 % for 2015. Kazakhstan KZ: Access to Electricity: Rural: % of Population data is updated yearly, averaging 98.569 % from Dec 1990 (Median) to 2016, with 27 observations. The data reached an all-time high of 100.000 % in 2016 and a record low of 93.900 % in 1999. Kazakhstan KZ: Access to Electricity: Rural: % of Population data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Kazakhstan – Table KZ.World Bank: Energy Production and Consumption. Access to electricity, rural is the percentage of rural population with access to electricity.; ; World Bank, Sustainable Energy for All (SE4ALL) database from the SE4ALL Global Tracking Framework led jointly by the World Bank, International Energy Agency, and the Energy Sector Management Assistance Program.; Weighted average;
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!
Google’s energy consumption has increased over the last few years, reaching 25.9 terawatt hours in 2023, up from 12.8 terawatt hours in 2019. The company has made efforts to make its data centers more efficient through customized high-performance servers, using smart temperature and lighting, advanced cooling techniques, and machine learning. Datacenters and energy Through its operations, Google pursues a more sustainable impact on the environment by creating efficient data centers that use less energy than the average, transitioning towards renewable energy, creating sustainable workplaces, and providing its users with the technological means towards a cleaner future for the future generations. Through its efficient data centers, Google has also managed to divert waste from its operations away from landfills. Reducing Google’s carbon footprint Google’s clean energy efforts is also related to their efforts to reduce their carbon footprint. Since their commitment to using 100 percent renewable energy, the company has met their targets largely through solar and wind energy power purchase agreements and buying renewable power from utilities. Google is one of the largest corporate purchasers of renewable energy in the world.
The SDG Indicator 7.1.1: Access to Electricity, 2023 Release data set, part of the Sustainable Development Goal Indicators (SDGI) collection, measures the proportion of the population with access to electricity for a given statistical area. UN SDG 7 is "ensure access to affordable, reliable, sustainable and modern energy for all". Tracking SDG 7: The Energy Progress Report estimated that in 2019, 759 million people around the world lacked access to electricity. Moreover, due to current policies and the detrimental effects of the COVID-19 crisis, it is predicted that by 2030, 660 million people will still not have access to electricity, with a majority of these people residing in Sub-Saharan Africa. As one measure of progress towards SDG 7, the UN agreed upon SDG indicator 7.1.1. The indicator was computed as the proportion of WorldPop gridded population located within illuminated areas defined by annual VIIRS Nighttime Lights Version 2 (VNL V2) data. The SDG indicator 7.1.1 data set provides estimates for the proportion of population with access to electricity for 206 countries and 45,979 level 2 subnational Units. The data set is available at both national and level 2 subnational resolutions.