This API provides state-level and national-level energy consumption data. Data organized by major economic sectors. EIA's State Energy Data System (SEDS) is a comprehensive data set that consists of annual time series estimates of state-level energy use by major economic sectors, energy production and and State-level energy price and expenditure data. The system provides data back from 1960. Data are presented in physical units, Btu, and dollars. Users of the EIA API are required to obtain an API Key via this registration form: http://www.eia.gov/beta/api/register.cfm

Energy Information Administration. State Energy Data System: Electricity Consumption, Prices, and Expenditures | Indicator: Electricity price in the commercial sector., 1970 - 2014. Data-Planet™ Statistical Datasets by Conquest Systems, Inc. Dataset-ID: 004-012-012 Dataset: Reports estimates of electricity consumption, prices, and expenditures for the United States as a whole and for individual states and Washington, DC, as available. The State Energy Data System (SEDS) is maintained and operated by the United States Energy Information Administration (EIA). The goal in maintaining SEDS is to create historical time series of energy production, consumption, prices, and expenditures by state that are defined as consistently as possible over time and across sectors. SEDS is used primarily to provide (1) state energy production, consumption, price, and expenditure estimates to Members of Congress, federal and state agencies, and the general public; and (2) the historical time series necessary to develop EIA’s energy models. Efforts are made to ensure that the sums of the state estimates equal the national totals as closely as possible for each energy type and end-use sector as published in other EIA publications. SEDS state energy consumption estimates are generally comparable to the statistics in EIA's Annual Energy Review and Monthly Energy Review consumption tables. Although SEDS incorporates the most consistent series and procedures possible, users of this report should recognize the limitations of the data that are due to changing and inadequate data sources. See the technical documentation for information on data inconsistencies. http://www.eia.gov/state/seds/seds-data-complete.cfm Category: Energy Resources and Industries Subject: Prices, Energy Expenditures, Electricity, Energy Consumption Source: Energy Information Administration The Energy Information Administration (EIA), created by Congress in 1977, is an independent statistical and analytical agency within the United States Department of Energy. Its mission is to provide policy-independent data, forecasts, and analyses to promote sound policy making, efficient markets, and public understanding regarding energy and its interaction with the economy and the environment. http://www.eia.doe.gov/

The average energy consumption of a ChatGPT request was estimated at *** watt-hours, nearly ** times that of a regular Google search, which reportedly consumes *** Wh per request. BLOOM had a similar energy consumption, at around **** Wh per request. Meanwhile, incorporating generative AI into every Google search could lead to a power consumption of *** Wh per request, based on server power consumption estimations.

These Combined State Energy Data System (CSEDS) files contain data used in the publication "State Energy Data Report 1999, Consumption Estimates" (SEDR) DOE/EIA-0214(99). Each State file and a U.S. file, named with the two-letter U.S. Postal Code listed in Appendix A, contains CSEDS physical unit (i.e., short tons, barrels, cubic feet, etc.) and British thermal unit (Btu) consumption data for all years 1960 through 1999.The data are provided in the full precision units carried to five decimal places.

Global primary energy consumption has increased dramatically in recent years and is projected to continue to increase until 2045. Only hydropower and renewable energy consumption are expected to increase between 2045 and 2050 and reach 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, it was Qatar, Singapore, the United Arab Emirates, and Iceland to have the highest per capita energy consumption. Renewable energy consumption Over the last two decades, renewable energy consumption has increased to reach over 90 exajoules in 2023. Among all countries globally, China had the largest installed renewable energy capacity as of that year, followed by the United States.

Industrial activities are the greatest energy end-user sector in the United States, reaching a consumption of some 31 quadrillion British thermal units in 2024, followed by the transportation sector. The U.S. is the second-largest energy consumer in the world, after China. Energy source in the United States Consumption of fossil fuels still accounts for the majority of U.S. primary energy consumption. The transportation and industrial sectors are the sectors with the largest fossil fuel consumption in the country, the former relying on oil-based motor fuels. Electricity generation in the United States Although around 60 percent of the electricity generated in the U.S. is derived from natural gas and coal, the use of renewable sources is becoming more common in electricity production, with the largest increase in wind and solar power. These two clean energy resources are projected to generate as much power as natural gas by 2030.

description: The State Energy Data System (SEDS) is compiled by the U.S. Energy Information Administration's (EIA); it is a comprehensive database of energy statistics by state (and includes totals for the entire US). SEDS includes estimates of energy production, consumption, prices, and expenditures broken down by energy source and sector. Annual estimates are available from 1960 2009 for production and consumption estimates and from 1970 2009 for price and expenditure estimates. The multi-dimensional nature of this EIA dataset allows users to make comparisons across States, energy sources, sectors, and over time. Related Links Link to state SEDS SEDS documentation Complete SEDS data tables and files; abstract: The State Energy Data System (SEDS) is compiled by the U.S. Energy Information Administration's (EIA); it is a comprehensive database of energy statistics by state (and includes totals for the entire US). SEDS includes estimates of energy production, consumption, prices, and expenditures broken down by energy source and sector. Annual estimates are available from 1960 2009 for production and consumption estimates and from 1970 2009 for price and expenditure estimates. The multi-dimensional nature of this EIA dataset allows users to make comparisons across States, energy sources, sectors, and over time. Related Links Link to state SEDS SEDS documentation Complete SEDS data tables and files

EIA's State Energy Data System (SEDS) is a comprehensive data set that consists of annual time series estimates of state-level energy use by major economic sectors, energy production and and State-level energy price and expenditure data. The system provides data back from 1960. Data are presented in physical units, BTUs, and dollars. While some SEDS data series come directly from surveys conducted by EIA, many are estimated using other available information. These estimations are necessary for the compilation of "total energy" estimates.

This dataset presents water withdrawal estimates, consumption estimates, and associated information for 1,122 water-using, utility-scale thermoelectric power plants in the United States for 2015. The U.S. Geological Survey (USGS) developed models to estimate thermoelectric water use based on linked heat-and-water budgets, including thermodynamically plausible ranges of minimum and maximum withdrawal and consumption, to provide a consistent method for water-use estimation across the fleet of U.S. thermoelectric plants. Historically, thermoelectric water withdrawal and consumption has been estimated by the Department of Energy's Energy Information Administration (EIA) based on surveys of plant operator-reported data, and the USGS's 5-year water-use reports based on compiling data from State water agencies, plant operators, and the EIA. The USGS models provide independent estimates from plant operator-reported data. The total estimated withdrawal for 2015 was about 103 billion gallons per day (Bgal/d), and total estimated consumption was about 2.7 Bgal/d. This data release supports the findings published in Harris and Diehl (2019).

These State Energy Data System (SEDS) files contain data from the publication "State Energy Data Report 1995, Consumption Estimates." Each State file, named with a two-letter U.S. Postal Code, contains SEDS physical unit and Btu consumption, as well as State-level conversion factors used in the SEDS system. In addition, there is an executable file containaing the physical unit data for all States, and an executable file containing Btu data for all States.

The Renewable Energy Directive 2009/28/EC and its recast 2018/2001/EU commit the EU to achieving a 20 % share of renewable energy sources (RES) in its gross final energy consumption by 2020, and 32 % by 2030. They also set a target of 10 % share of renewable energy in transport by 2020, and 14% by 2030. Since early access to the most recent information on the growth of RES is relevant for all stakeholders, the EEA and its European Topic Centre for Climate Change Mitigation and Energy (ETC/CME) produce each year a set of early estimates concerning the RES shares achieved by the countries and the EU as a whole in the previous year. The current data set concerns the EEA 2020 RES share proxies. The cut-off date for most data sources incorporated in the calculation of the approximated RES shares is 31 July of the publication year.

This table contains 511 series, with data for years 1990 - 1990 (not all combinations necessarily have data for all years), and is no longer being released. This table contains data described by the following dimensions (Not all combinations are available): Geography (1 item: Canada); Fuel type (14 items: Total, energy consumed as fuel (higher heating value);Coal;Coal coke;Coke oven gas; ...); North American Industry Classification System (NAICS) (66 items: Manufacturing;Food manufacturing;Fruit and vegetable preserving and specialty food manufacturing;Dairy product manufacturing; ...).

Abstract

Dataset quality **: Medium/high quality dataset, not quality checked or modified by the EIDC team

RECS measures the usage of energy in primary, occupied housing units, in 2020. This is the raw dataset measured at the household level.

It covers the following topics:

• the physical characteristics of the home (housing types, size, and age);
• the use of electronic devices and appliances;
• the use of heating and air conditioning systems;
• energy usage behaviors (frequency of usage, temperature setpoints);
• challenges associated with paying utility bills or keeping homes at healthy temperatures;
• total household energy consumption and expenditures; and
• their breakdown by energy end-use (modeled/estimated), such as by space heating, water heating, air conditioning, cooking, laundry, TV, lighting, and other end-uses.

Methodology

• **Target population: **all a) occupied housing units in b) the 50 states & DC that are used as c) primary residences.
• Sample: Homes that are occupied as a primary residence
• Excludes vacant homes, seasonal housing units, group quarters (e.g. dormitories, nursing homes, prisons, military barracks), and common areas in apartment buildings.

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• Includes housing units located on military installations.
• **Sampling method: **Unclustered sampling, Jackknife method
• **Mode of survey: **self-administered questionnarie via 1) the web or 2) mail/paper
• **Sample size: **18,496 households (72% via web questionnaire; 27.2% via paper questionnaire)
• Response rate: Unweighted, 38.6%; Weighted, 37.9%

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Usage

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• RECS is best suited for comparison across different characteristics of homes within the residential sector.

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• **RECS is **%3Cu%3E%3Cstrong%3Enot%3C/strong%3E%3C/u%3E

** appropriate for comparing EIA's other residential energy data** as the scope of RECS is limited to homes occupied as a primary residence. As a result, RECS estimates are not comparable with sector-level totals defined in other EIA datasets

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The Foundational Industry Energy Dataset (FIED) addresses several of the areas of growing disconnect between the demands of industrial energy analysis and the state of industrial energy data by providing unit-level characterization by facility. Each facility is identified by a unique registryID, based on the U.S. Environmental Protection Agency (EPA) Facility Registry Service, and includes its coordinates and other geographic identifiers. Energy-using units are characterized by design capacity, as well as their estimated energy use, greenhouse gas emissions, and physical throughput using 2017 data from the EPA's National Emissions Inventory and Greenhouse Gas Reporting Program. An overview of the derivation methods is provided in a separate technical report which will be linked after publication. The Python code used to compile the dataset is available in a GitHub repository. An updated 2020 version is under development.

This document estimates the energy consumption of various transportation sectors based on the energy balance sheet published by the Ministry of Economic Affairs.

Domestic electricity consumption estimates for Glasgow based on the Intermediate Geography areas. In England the equivalent is the Middle Layer Super Output Area (MLSOA). Data is provided for ordinary domestic and Economy 7 electricity consumption (kWh) , the number of ordinary domestic and Economy 7 meters and average consumption for ordinary domestic or economy 7 consumption (kWh) for Intermediate Geography areas in Glasgow. DECC provide a methodology and guidance chapter and an accompanying factsheet The data for Scotland in this dataset should be considered as provisional because DECC report a small inconsistency (-0.01% of total consumption) between the data contained in this dataset compared to the local authority dataset for Scottish geographical codes. Data extracted 2014-03-06 from gov.uk MLSOA electricity and gas:2010 Licence: None