Hourly electricity consumption in France is highest in November, December, January, and February of each year, while it reaches the lowest levels between May and September. The average annual electricity consumption in France in 2023 was around 445 terawatt-hours, the smallest value in the past decade. Nuclear electricity production in France While the main source of electricity in France is nuclear power, the nuclear share of electricity generation decreased from 78.5 percent in 2005 to 65 percent in 2023. The French electricity company EDF Group had to face unexpected technical issues in its nuclear fleet over the last three years, which caused nuclear outages and loss of electricity production. Renewable sources in France Renewable energy consumption in France has increased over the past few years, coming mainly from hydropower and wind renewable energy sources. Among its renewable energy investments, in 2024 France was developing several offshore wind farm projects. Besides, solar photovoltaic energy capacity in France was expected to grow up to 37 gigawatts by 2027.

Electricity consumption in the United States totaled ***** 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 ** million people, consumed over *** terawatt-hours. California and Florida trailed in second and third, each with an annual consumption of approximately *** terawatt-hours.

Detailed household load and solar generation in minutely to hourly resolution. This data package contains measured time series data for several small businesses and residential households relevant for household- or low-voltage-level power system modeling. The data includes solar power generation as well as electricity consumption (load) in a resolution up to single device consumption. The starting point for the time series, as well as data quality, varies between households, with gaps spanning from a few minutes to entire days. All measurement devices provided cumulative energy consumption/generation over time. Hence overall energy consumption/generation is retained, in case of data gaps due to communication problems. Measurements were conducted 1-minute intervals, with all data made available in an interpolated, uniform and regular time interval. All data gaps are either interpolated linearly, or filled with data of prior days. Additionally, data in 15 and 60-minute resolution is provided for compatibility with other time series data. Data processing is conducted in Jupyter Notebooks/Python/pandas.

United States Electricity Consumption data was reported at 10.243 kWh/Day bn in Mar 2025. This records a decrease from the previous number of 11.765 kWh/Day bn for Feb 2025. United States Electricity Consumption data is updated monthly, averaging 9.940 kWh/Day bn from Jan 1991 (Median) to Mar 2025, with 411 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]

Abstract: Measurements of electric power consumption in one household with a one-minute sampling rate over a period of almost 4 years. Different electrical quantities and some sub-metering values are available.

Source: Georges Hebrail (georges.hebrail '@' edf.fr), Senior Researcher, EDF R&D, Clamart, France Alice Berard, TELECOM ParisTech Master of Engineering Internship at EDF R&D, Clamart, France

Data Set Information: This archive contains 2075259 measurements gathered in a house located in Sceaux (7km of Paris, France) between December 2006 and November 2010 (47 months). Notes:

(global_active_power*1000/60 - sub_metering_1 - sub_metering_2 - sub_metering_3) represents the active energy consumed every minute (in watt hour) in the household by electrical equipment not measured in sub-meterings 1, 2 and 3. The dataset contains some missing values in the measurements (nearly 1,25% of the rows). All calendar timestamps are present in the dataset but for some timestamps, the measurement values are missing: a missing value is represented by the absence of value between two consecutive semi-colon attribute separators. For instance, the dataset shows missing values on April 28, 2007.

Attribute Information:

date: Date in format dd/mm/yyyy time: time in format hh:mm:ss global_active_power: household global minute-averaged active power (in kilowatt) global_reactive_power: household global minute-averaged reactive power (in kilowatt) voltage: minute-averaged voltage (in volt) global_intensity: household global minute-averaged current intensity (in ampere) sub_metering_1: energy sub-metering No. 1 (in watt-hour of active energy). It corresponds to the kitchen, containing mainly a dishwasher, an oven and a microwave (hot plates are not electric but gas powered). sub_metering_2: energy sub-metering No. 2 (in watt-hour of active energy). It corresponds to the laundry room, containing a washing-machine, a tumble-drier, a refrigerator and a light. sub_metering_3: energy sub-metering No. 3 (in watt-hour of active energy). It corresponds to an electric water-heater and an air-conditioner.

Relevant Papers: N/A

Citation Request: This dataset is made available under the “Creative Commons Attribution 4.0 International (CC BY 4.0)” license

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.

based on the ESP32 hardware.

High Frequency Indicator: The dataset contains year-, month- and state-wise compiled data from the year 2012 to till date on electricity (power) met in India

Notes: 1. Daman and Diu and Dadra and Nagar Haveli have been merged into a single entity 'DNHDDPDCL' with effect from 01.06.2022. 2. Data for April 2013 is not public. 3. The power supply figures for Andhra Pradesh until 2015 include both the current states of Andhra Pradesh and Telangana. 4. Power Supply data for Sikkim up to May 2014 and for April 2015 are not available.

China Energy Consumption: Daily Average: Electricity data was reported at 24,210.000 kWh mn in 2022. This records an increase from the previous number of 23,340.000 kWh mn for 2021. China Energy Consumption: Daily Average: Electricity data is updated yearly, averaging 4,270.541 kWh mn from Dec 1980 (Median) to 2022, with 42 observations. The data reached an all-time high of 24,210.000 kWh mn in 2022 and a record low of 82.000 kWh mn in 1980. China Energy Consumption: Daily Average: Electricity 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.

Monthly data since January 1973 and annual data since 1949 on U.S. primary and total energy consumption by end-use sector (residential, commercial, industrial, transportation) and electric power sector.

50Hz standard.

This dataset contains detailed measurements of electric power consumption in a household over a span of nearly four years. Collected at a one-minute sampling rate, the data provides insights into various electrical quantities and sub-metering values for the household. The dataset includes 2,075,259 observations and covers a period from December 2006 to November 2010.

This dataset is ideal for time-series analysis, regression modeling, clustering, and other tasks related to energy consumption forecasting, anomaly detection, and pattern recognition. It provides a valuable resource for understanding household energy usage and behavior.

Column Descriptions Date

Type: Date Description: The date in dd/mm/yyyy format. Missing Values: No Time

Type: Categorical Description: The time in hh:mm:ss format. Missing Values: No Global_active_power

Type: Continuous Description: Household global minute-averaged active power (in kilowatts). Missing Values: No Global_reactive_power

Type: Continuous Description: Household global minute-averaged reactive power (in kilowatts). Missing Values: No Voltage

Type: Continuous Description: Minute-averaged voltage (in volts). Missing Values: No Global_intensity

Type: Continuous Description: Household global minute-averaged current intensity (in amperes). Missing Values: No Sub_metering_1

Type: Continuous Description: Energy sub-metering No. 1 (in watt-hours of active energy), related to the kitchen. Missing Values: No Sub_metering_2

Type: Continuous Description: Energy sub-metering No. 2 (in watt-hours of active energy), related to the laundry room. Missing Values: No Sub_metering_3

Type: Continuous Description: Energy sub-metering No. 3 (in watt-hours of active energy), related to an electric water heater and air-conditioner. Missing Values: No

Consumption of electricity which is produced from the power stations.Source: Electricity and Water Authority

This dataset is part of the Monash, UEA & UCR time series regression repository. http://tseregression.org/

The goal of this dataset is to predict total reactive power consumption in a household. This dataset contains 1440 time series obtained from the Individual household electric power consumption dataset from the UCI repository. The time series has 5 dimensions. This includes measurements for voltage, current annd 3 sub-metering energy usage.

Please refer to https://archive.ics.uci.edu/ml/datasets/Individual+household+electric+power+consumption for more details

Source Georges Hebrail (georges.hebrail '@' edf.fr), Senior Researcher, EDF R&D, Clamart, France Alice Berard, TELECOM ParisTech Master of Engineering Internship at EDF R&D, Clamart, France

China consumes by far the most electricity of any country in the world, with almost 9,000 terawatt-hours equivalent consumed in 2024. The United States ranked as the second-leading electricity consumer that year, with over 4,000 terawatt-hours consumed. India followed, but by a wide margin. Production and consumption disparities China not only leads countries in electricity generation worldwide, it also dominates production, generating over 10 petawatt-hours annually. The United States follows with 4.6 petawatt-hours, significantly more than its consumption of 4,065 terawatt-hours. This disparity underscores the complex relationship between production and consumption, influenced by factors such as energy efficiency, export capabilities, and domestic demand. The global expansion of electricity networks, particularly in Central and Southern Asia, is driving increased production to meet growing access and demand. Shifting energy landscapes The United States, as the second-largest consumer, is experiencing a significant shift in its energy mix. Coal-based electricity has declined by nearly 65 percent since 2010, giving way to natural gas and renewable sources. This transition is evident in recent capacity additions, with renewable energy sources accounting for over 90 percent of new electricity capacity in 2024. The surge in renewable generation, particularly wind power, is reshaping the U.S. energy landscape and influencing consumption patterns. As renewable energy consumption is projected to more than double by 2050, the electricity market is adapting to these changing dynamics.

Hong Kong Electricity Consumption: CLP Power: Per Person data was reported at 5,397.000 kWh/Person mn in 2017. This records a decrease from the previous number of 5,451.000 kWh/Person mn for 2016. Hong Kong Electricity Consumption: CLP Power: Per Person data is updated yearly, averaging 5,072.000 kWh/Person mn from Dec 1989 (Median) to 2017, with 29 observations. The data reached an all-time high of 5,516.000 kWh/Person mn in 2014 and a record low of 3,618.000 kWh/Person mn in 1989. Hong Kong Electricity Consumption: CLP Power: Per Person data remains active status in CEIC and is reported by CLP Power Hong Kong Limited. The data is categorized under Global Database’s Hong Kong SAR – Table HK.RB001: Electricity Production & Consumption.

Electricity Consumption: Utilities: Delhi data was reported at 34,107.000 GWh in 2023. This records an increase from the previous number of 27,625.000 GWh for 2022. Electricity Consumption: Utilities: Delhi data is updated yearly, averaging 18,380.635 GWh from Mar 1996 (Median) to 2023, with 28 observations. The data reached an all-time high of 34,107.000 GWh in 2023 and a record low of 6,580.990 GWh in 1996. Electricity Consumption: Utilities: Delhi data remains active status in CEIC and is reported by Central Electricity Authority. The data is categorized under Global Database’s India – Table IN.RBE002: Electricity: Consumption: Utilities.

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.

In 2023, it was estimated that artificial intelligence represented a power consumption of *** gigawatts worldwide, or eight percent of total power consumption in data centers that year. AI's power consumption is expected to grow significantly in the next five years, forecast at ** to **** gigawatts in 2028. That would account for up to ** percent of data center power consumption that year.

Accurate estimation of electricity consumption at multi-temporal resolutions is crucial for formulating safe and efficient energy management strategies. However, reliable data on daily and monthly urban electricity consumption is often limited. This study develops a top-down approach based on multi-source data to measure the daily and monthly electricity consumption at city-level. Using this method, we calculated the daily and monthly electricity consumption for 296 cities in China. Additionally, we explored the validity of the measurement results from multiple perspectives. This dataset is highly consistent with the officially released national-scale electricity consumption statistics, with a Pearson correlation coefficient of 0.8878. The dataset in this study can be used for analysis in a variety of cutting-edge research fields, such as urban power system resilience assessment, urban power system risk management strategy and policy development.