Dataset from Energy Market Authority. For more information, visit https://data.gov.sg/datasets/d_634194a40f36e5bc11a942ab0164fa9d/view

This table shows regional figures on the average consumption of energy (natural gas and electricity) of private dwellings broken down by type of dwelling and ownership for Nederland, group of provinces, provinces and municipalities. Besides, for total dwellings only, the share of heat distribution (district heating) has been added, because this is relevant for the interpretation of the height of the average consumption of natural gas. Data available from: 2010 Status of the figures: All figures from 2010 - 2021 are definite. Figures of 2022 are provisional. Changes as of October 2023: Provisional figures of 2022 have been added. Figures of 2021 have been updated. The category “Average consumption of electricity” is replaced by “Average supply of electricity” and a category “Average net supply of electricity” has been added. When will new figures be published? A revision to the method of this statistic is currently underway, causing the table to be delayed. New figures will come in the 3rd quarter of the folowing year.

The "Energy Consumption in New York City" dataset provides comprehensive information on the energy usage patterns and trends in City over the past five years. The dataset includes data on electricity consumption, gas consumption, and water consumption in various sectors, such as residential, commercial, and industrial. Attributes: 2020: The year for which the data was recorded. August: The month for which the data was recorded. Sector: The sector (residential, commercial, industrial) of energy consumption. Electricity Consumption (kWh): Total electricity consumption 200,000 kWh for the specific sector. Gas Consumption (m³): Total gas consumption 500 m³ for the residential sector. Water Consumption (m³): Total water consumption 300 m³ for both residential and commercial sector. Data Sources: The data has been collected from industry reports, ensuring its reliability and accuracy. Use Cases: This dataset is valuable for researchers, urban planners, and policymakers to analyze energy consumption patterns, identify trends, and make informed decisions regarding energy efficiency and sustainability initiatives in New York City. Update Frequency: The dataset is updated annually to include the latest available data. License: The dataset is made available under the Creative Commons Attribution License, allowing users to share and adapt the data for non-commercial purposes with appropriate attribution.

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.

China Electricity Consumption: per Capita: Average data was reported at 6,257.000 kWh in 2022. This records an increase from the previous number of 6,032.000 kWh for 2021. China Electricity Consumption: per Capita: Average data is updated yearly, averaging 1,066.997 kWh from Dec 1978 (Median) to 2022, with 45 observations. The data reached an all-time high of 6,257.000 kWh in 2022 and a record low of 261.265 kWh in 1978. China Electricity Consumption: per Capita: Average data remains active status in CEIC and is reported by National Bureau of Statistics. The data is categorized under China Premium Database’s Utility Sector – Table CN.RCB: Electricity Summary.

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.

Annual data on the average price of retail electricity to consumers. Data organized by U.S. state and by provider, i.e., total electric industry, full-service providers, restructured retail service providers, energy-only providers, and delivery-only service. Annual time series extend back to 1990. Based on Form EIA-861 data.

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.

United States Electricity Consumption data was reported at 11.791 kWh/Day bn in Feb 2025. This records a decrease from the previous number of 12.060 kWh/Day bn for Jan 2025. United States Electricity Consumption data is updated monthly, averaging 9.940 kWh/Day bn from Jan 1991 (Median) to Feb 2025, with 410 observations. The data reached an all-time high of 13.179 kWh/Day bn in Jul 2024 and a record low of 7.190 kWh/Day bn in Apr 1991. United States Electricity Consumption data remains active status in CEIC and is reported by U.S. Energy Information Administration. The data is categorized under Global Database’s United States – Table US.RB004: Electricity Supply and Consumption. [COVID-19-IMPACT]

This is grouped and aggregated electricity consumption data from the EtudELEC study conducted by the Observatoire du Transition Energétique Grenoble (OTE-UGA). If you find this dataset useful and like different groupings to be published or have any questions, please feel free to comment on the discussion dedicated to this dataset on the OTE forum . The EtudELEC study only studies electricity consumption from residential dwellings around France. The study involved over 400 homes (individual houses and apartments) and spanned ~11 months from 25th October 2022 to 1st October 2023. The data is collected from the smart meter data (Linky data) which is only available with a time-step of 30 minutes. The data is in average watts consumed in a half-hour period. For reasons for privacy in line with GDPR laws, personal data such as individual home consumption will be shared as aggregated datasets as opposed to individual data points. The data from the participants were aggregated based on the following groupings: - Type of heating used and type of residence (stand-alone house vs apartment) This dataset is best viewed in the "Tree" view below. A folder is created for each of the groupings and sub-folders exist for all the subsequent groups. Each group folder contains: - a table of the minimum, mean, and maximum of the average power consumed for each 30-minute period (W), and - a JSON file with aggregated demographics information (number of inhabitants in different age backets, socio-professional category, year of construction etc.) of the group The datasets will be updated on a yearly basis following the renewal of consent of the panel members. Il s'agit de données de consommation électriques groupées et agrégées issues de l'étude EtudELEC menée par l'Observatoire de la Transition Energétique (OTE-UGA). Si vous trouvez ce jeu de données utile et souhaitez que différents regroupements soient publiés, n'hésitez pas à écrire dans le topic sur le forum OTE. L'étude EtudELEC est une étude sur la consommation d'électricité des logements résidentiels en France. L'étude porte sur plus de 400 logements (maisons individuelles et appartements) et s'étend sur 11 mois du 25 octobre 2022 au 1 octobre 2023. Les données sont collectées à partir des données des compteurs intelligents (données Linky) qui ne sont disponibles qu'avec un pas de temps de 30 minutes. Les données sont exprimées en watts consommés en moyenne sur une période d'une demi-heure. Pour des raisons de confidentialité conformes aux lois RGPD, les données personnelles telles que la consommation individuelle des maisons seront partagées sous forme d'ensembles de données agrégées plutôt que de points de données individuels. Les données des participants ont été agrégées sur la base des regroupements suivants : - Type de chauffage utilisé et type de résidence (maison individuelle ou appartement). Cet ensemble de données est mieux visualisé dans l'arborescence ci-dessous. Un dossier est créé pour chaque groupe et des sous-dossiers existent pour tous les groupes suivants. Chaque dossier de groupe contient : - un tableau du minimum, de la moyenne et du maximum de la puissance moyenne consommée pour chaque période de 30 minutes (W), et - un fichier JSON avec des informations démographiques agrégées (nombre d'habitants dans différentes tranches d'âge, catégorie socioprofessionnelle, année de construction, etc. Les jeux de données seront mis à jour chaque année après le renouvellement du consentement des membres du panel.

This table contains 165 series, with data for years 2011-2019 (not all combinations necessarily have data for all years). This table contains data described by the following dimensions (Not all combinations are available): Geography (11 items: Canada; Newfoundland and Labrador; Prince Edward Island; Nova Scotia; ...) ; Energy type (4 items: Total, all energy types; Electricity; Natural gas; Heating oil) ; Energy consumption (4 items: Gigajoules; Gigajoules per household; Proportion of total energy; Number of households).

Electricity consumption in the United States totaled 4,000 terawatt-hours in 2023, one of the highest values in the period under consideration. Figures represent energy end use, which is the sum of retail sales and direct use of electricity by the producing entity. Electricity consumption in the U.S. is expected to continue increasing in the next decades. Which sectors consume the most electricity in the U.S.? Consumption has often been associated with economic growth. Nevertheless, technological improvements in efficiency and new appliance standards have led to a stabilizing of electricity consumption, despite the increased ubiquity of chargeable consumer electronics. Electricity consumption is highest in the residential sector, followed by the commercial sector. Equipment used for space heating and cooling account for some of the largest shares of residential electricity end use. Leading states in electricity use Industrial hub Texas is the leading electricity-consuming U.S. state. In 2022, the Southwestern state, which houses major refinery complexes and is also home to nearly 30 million people, consumed over 470 terawatt-hours. California and Florida trailed in second and third, each with an annual consumption of approximately 250 terawatt-hours.

This table contains consumer prices for electricity and gas. Weighted average monthly prices are published broken down into transport rate, delivery rates and taxes, both including and excluding VAT. These prices are published on a monthly basis. The prices presented in this table were used to compile the CPI up to May 2023. Prices for newly offered contracts were collected. Contract types that are no longer offered, but have been in previous reporting periods, are imputed. The average can therefore diverge from the prices paid for energy contracts by Dutch households. Data available from January 2018 up to May 2023. Status of the figures: The figures are definitive. Changes as of 17 July 2023: This table will no longer be updated. Due to a change in the underlying data and accompanying method for calculcating average energy prices, a new table was created. See paragraph 3. Changes as of 13 February: Average delivery rates are not shown in this table from January 2023 up to May 2023. With the introduction of the price cap, the average energy rates (delivery rates) of fixed and variable energy contracts together remained useful for calculating a development for the CPI. However, as a pricelevel, they are less useful. Average energy prices from January 2023 up to May 2023 are published in a customized table. In this publication, only data concerning new variable contracts are taken into account When will new figures be published? Does not apply.

Note: This dataset has been superseded by the dataset found at "End-Use Load Profiles for the U.S. Building Stock" (submission 4520; linked in the submission resources), which is a comprehensive and validated representation of hourly load profiles in the U.S. commercial and residential building stock. The End-Use Load Profiles project website includes links to data viewers for this new dataset. For documentation of dataset validation, model calibration, and uncertainty quantification, see Wilson et al. (2022).

These data were first created around 2012 as a byproduct of various analyses of solar photovoltaics and solar water heating (see references below for are two examples). This dataset contains several errors and limitations. It is recommended that users of this dataset transition to the updated version of the dataset posted in the resources. This dataset contains weather data, commercial load profile data, and residential load profile data.

Weather The Typical Meteorological Year 3 (TMY3) provides one year of hourly data for around 1,000 locations. The TMY weather represents 30-year normals, which are typical weather conditions over a 30-year period.

Commercial The commercial load profiles included are the 16 ASHRAE 90.1-2004 DOE Commercial Prototype Models simulated in all TMY3 locations, with building insulation levels changing based on ASHRAE 90.1-2004 requirements in each climate zone. The folder names within each resource represent the weather station location of the profiles, whereas the file names represent the building type and the representative city for the ASHRAE climate zone that was used to determine code compliance insulation levels. As indicated by the file names, all building models represent construction that complied with the ASHRAE 90.1-2004 building energy code requirements. No older or newer vintages of buildings are represented.

Residential The BASE residential load profiles are five EnergyPlus models (one per climate region) representing 2009 IECC construction single-family detached homes simulated in all TMY3 locations. No older or newer vintages of buildings are represented. Each of the five climate regions include only one heating fuel type; electric heating is only found in the Hot-Humid climate. Air conditioning is not found in the Marine climate region.

One major issue with the residential profiles is that for each of the five climate zones, certain location-specific algorithms from one city were applied to entire climate zones. For example, in the Hot-Humid files, the heating season calculated for Tampa, FL (December 1 - March 31) was unknowingly applied to all other locations in the Hot-Humid zone, which restricts heating operation outside of those days (for example, heating is disabled in Dallas, TX during cold weather in November). This causes the heating energy to be artificially low in colder parts of that climate zone, and conversely the cooling season restriction leads to artificially low cooling energy use in hotter parts of each climate zone. Additionally, the ground temperatures for the representative city were used across the entire climate zone. This affects water heating energy use (because inlet cold water temperature depends on ground temperature) and heating/cooling energy use (because of ground heat transfer through foundation walls and floors). Representative cities were Tampa, FL (Hot-Humid), El Paso, TX (Mixed-Dry/Hot-Dry), Memphis, TN (Mixed-Humid), Arcata, CA (Marine), and Billings, MT (Cold/Very-Cold).

The residential dataset includes a HIGH building load profile that was intended to provide a rough approximation of older home vintages, but it combines poor thermal insulation with larger house size, tighter thermostat setpoints, and less efficient HVAC equipment. Conversely, the LOW building combines excellent thermal insulation with smaller house size, wider thermostat setpoints, and more efficient HVAC equipment. However, it is not known how well these HIGH and LOW permutations represent the range of energy use in the housing stock.

Note that on July 2nd, 2013, the Residential High and Low load files were updated from 366 days in a year for leap years to the more general 365 days in a normal year. The archived residential load data is included from prior to this date.

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/).

Residential customers use an average of about 1,000 kWh of electricity per month, with usage higher during hot summer months and lower in the winter. View tables show monthly average usage in kWh by month for residential customers starting in 2000. Tables include monthly fuel charges and electric bill amounts.

The dataset contains electrical consumption data from a three months living lab experiment in the Energy Smart Home Lab (ESHL) at Karlsruhe Institute of Technology. During the experiment two tenants lived their daily life in the ESHL, a smart home consisting of a 60m² living area and a 20m² technical room. The dataset contains the electrical consumption data for every device and socket in the living area as well as the technical room. There is one set for the average electricity demand per 15min for all devices in the living room, one set for the average demand per 15min for all devices in the technical room, one set for the maximum demand per 15min for the devices in the living room and one set for the maximum demand per 15min for the devices in the technical room. Due to technical difficulties the recording for the devices in the technical room started two weeks after the recording of the living area. There are also some shorter gaps in the data due to power outages. In addition to the electrical consumption data, a timeseries for the outdoor temperature with a temporal resolution of 15min is included in the dataset.

The average for 2022 based on 190 countries was 139.5 billion kilowatthours. The highest value was in China: 8349.31 billion kilowatthours and the lowest value was in Montserrat: 0.02 billion kilowatthours. The indicator is available from 1980 to 2023. Below is a chart for all countries where data are available.

Ausgrid is providing the following data on electricity consumption within our network area for the 2010/2011 financial year to be used in developing applications. The data is from customer billing data and grouped by local government areas (LGA) in Ausgridas network.

Average electricity consumption by geographic area can vary significantly due to a number of factors. These include differences in climate, the use of natural gas, the type of housing (house or apartment), type of business (commercial or industrial), and varying household socio-demographics or business types.

These figures also do not necessarily include the electricity used in common areas of apartments like halls, garages or pools. About 20% of energy in an apartment building is typically used in these sorts of areas.

This data does not include high voltage customers and supply to services such as public lighting and bus shelters.

For help in interpreting the data, please contact sharinginformation@ausgrid.com.au.

This table shows the supply of electricity. Consumption of electricity is calculated from the supply variables. The supply of electricity primarily includes production plus imports minus exports. The majority of the electricity produced is supplied to the public electricity grid by, for example, power stations and wind turbines. A smaller part is generated by companies themselves for the benefit of their own business processes. For example, many greenhouse companies generate their own electricity for the lighting of their greenhouses.

The net production is determined as gross production minus the own consumption of electricity. Own consumption is the amount of electricity that a producer or installation consumes during electricity production. The net production is broken down in this table into the following energy sources from which the electricity is produced: nuclear energy, coal, petroleum products, natural gas, biomass, other fuels (non-renewable), hydro power, wind energy, solar photovoltaic and other sources.

Imports and exports are further broken down by country of origin or destination.

The total net consumption of electricity in the Netherlands is calculated as the net production plus imports minus exports and distribution losses.

Data available: Annual figures are available from 1929 onwards. Monthly figures on total electricity production, import and export are available from 1976. Full data per month is available from 2015.

Status of the figures: - All figures up to and including reporting year 2022 are definite. - Figures for 2023 are revised provisional. - Figures for 2024 are provisional.

Changes as of February 28th of 2025: Figures of December 2024 have been added. This table has been revised for 2015 to 2021 as a result of new methods that have also been applied for 2022 and 2023. This concerns changes of a maximum of a few PJ of the total supply and consumption on an annual basis.

Changes as of January 31st of 2025: Figures of November 2024 have been added.

When will new figures be published? Provisional figures: the second month after the end of the reporting period. Revised provisional figures: June of the year following the reporting year. Definite figures: not later than November of the second following year.