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]

In 2024, consumption of primary energy per capita in the United States amounted to 277 million British thermal units. Per capita consumption of energy has increased since the 1950s in the United States. However, in the advent of vehicle and electricity efficiency standards, this figure has decreased in recent years.

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.

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.

50Hz standard.

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AI Data Center Power Consumption Market Size 2025-2029

The AI data center power consumption market size is forecast to increase by USD 24.03 billion at a CAGR of 38.6% between 2024 and 2029.

The market is experiencing significant growth due to the proliferation and escalating complexity of generative AI. Advanced AI models require immense computational power, leading to increased energy consumption in data centers. This trend is driving the adoption of more efficient cooling technologies, such as liquid cooling, which can reduce power usage effectiveness (PUE) and lower overall energy consumption. However, the market faces challenges in the form of grid constraints and power scarcity. As data centers continue to expand, there is a growing need for reliable and sustainable power sources. 
Companies must navigate these challenges by exploring renewable energy solutions, implementing energy storage systems, and optimizing energy usage through load balancing and power management strategies. By addressing these issues, organizations can effectively capitalize on the opportunities presented by the growing market while minimizing risks and ensuring long-term success. Grid infrastructure may struggle to keep up with the increasing demand for electricity, potentially leading to power outages or brownouts. IT service management and network security protocols are essential for maintaining system resilience and reliability.

What will be the Size of the AI Data Center Power Consumption Market during the forecast period?

Explore in-depth regional segment analysis with market size data - historical 2019-2023 and forecasts 2025-2029 - in the full report.
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In the dynamic data center power consumption market, energy audit services play a crucial role in identifying inefficiencies and optimizing power usage. Power monitoring tools enable real-time tracking of energy consumption, while hardware lifecycle management ensures the efficient use of resources throughout the IT infrastructure. IT load forecasting and capacity planning tools help data center operators anticipate and manage power demands. Remote monitoring systems and thermal modeling facilitate infrastructure upgrades and cooling system design, enhancing data center resiliency. Cooling technology advancements, such as dynamic power allocation and power factor correction, contribute to energy efficiency standards and energy-efficient design. PUE metrics and server utilization rates are essential indicators of data center optimization.

Energy cost reduction strategies, including renewable energy integration and energy procurement, are increasingly popular. AI-powered analytics enable data centers to optimize server power consumption and improve overall energy efficiency. Infrastructure upgrades and power infrastructure design are critical in addressing the growing data center footprint. Real-time monitoring and cooling system design are essential for maintaining optimal conditions and ensuring data center reliability. Capacity planning tools and server power consumption management help data center operators make informed decisions and reduce energy waste. Strategic data center migration and cloud migration services are essential for businesses seeking operational agility and reduced on-premise dependency.

How is this AI Data Center Power Consumption Industry segmented?

The AI data center power consumption industry research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in 'USD million' for the period 2025-2029, as well as historical data from 2019-2023 for the following segments.

Technology

  Above 5 MW
  1 - 5 MW
  Less than 500 kW
  500 kW - 1 MW


Type

  Hyperscale data centers
  Colocation data centers
  Enterprise data centers
  Edge data centers


End-user

  IT and telecom
  BFSI
  Healthcare
  Others


Geography

  North America

    US
    Canada


  Europe

    France
    Germany
    UK


  APAC

    Australia
    China
    India
    Japan


  South America

    Brazil


  Rest of World (ROW)

By Technology Insights

The Above 5 MW segment is estimated to witness significant growth during the forecast period. In the realm of data center power consumption, the market's dynamics are shaped by various interconnected entities. Uninterruptible power supplies ensure uninterrupted operations, while energy consumption monitoring enables efficient usage. DCIM software solutions optimize infrastructure, and energy storage systems provide backup power. HVAC optimization and thermal management solutions enhance operational efficiency, reducing carbon footprints. Data center modernization embraces renewable energy sources and server energy efficiency. Precision cooling systems, waste heat recovery, and liquid cooling systems further optimize power usage effectiveness. Virtualization technology, powe

Luxembourg LU: Electric Power Consumption: per Capita data was reported at 13,914.678 kWh in 2014. This records a decrease from the previous number of 14,193.168 kWh for 2013. Luxembourg LU: Electric Power Consumption: per Capita data is updated yearly, averaging 12,632.241 kWh from Dec 1960 (Median) to 2014, with 55 observations. The data reached an all-time high of 16,829.963 kWh in 2010 and a record low of 4,548.205 kWh in 1960. Luxembourg LU: Electric Power Consumption: per Capita data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Luxembourg – Table LU.World Bank: Energy Production and Consumption. Electric power consumption measures the production of power plants and combined heat and power plants less transmission, distribution, and transformation losses and own use by heat and power plants.; ; IEA Statistics © OECD/IEA 2014 (http://www.iea.org/stats/index.asp), subject to https://www.iea.org/t&c/termsandconditions/; Weighted Average; Restricted use: Please contact the International Energy Agency for third-party use of these data.

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.

• Based on gross generation and not accounting for cross-border electricity supply. Converted on the

  basis of thermal equivalence assuming 38% conversion efficiency in a modern thermal power station.

  ^ Less than 0.05 | ♦ Less than 0.05%. | n/a not available.

  Excludes Estonia, Latvia, and Lithuania prior to 1985 and Slovenia prior to 1990.

Notes: Annual changes and shares of total are calculated using terawatt-hours figures.

Growth rates are adjusted for leap years

The United Kingdom’s electricity use has been declining since peaking at *** terawatt-hours in 2005. In 2024, the UK's electricity increased on the previous year, amounting to *** terawatt-hours. Electricity consumption in the UK typically follows a seasonal trend, peaking in the winter months. How electricity-intensive is the UK? Despite the continual decline in electricity consumption, the UK remains one of the largest electricity consumers in the world. In terms of per capita electricity consumption, however, the UK ranks low in comparison to other European countries such as Norway, Germany, and France. In 2023, it registered an average of ***** kilowatt-hours per person. The race towards a clean power mix In 2010, gas and coal accounted for roughly ** percent of the UK's power mix. Since then, alongside the EU Renewables Directive, the UK agreed and created its own National Renewable Energy Plan, to increase the use of renewable sources and decrease its fossil fuel dependence. In the past decade, the share of energy consumption in the UK attributable to renewable energy increased slightly, although it was still a small percentage out of the total in 2023.

Per capita energy consumption averaged ****** kilowatt-hours worldwide in 2023. This was up from a pandemic induced slump in 2020. Qatar has the highest per capita energy consumption of any country worldwide.

This table contains 1155 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; ...); Type of dwelling (7 items: Single-detached; Double; Row or terrace; Duplex; ...); 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).

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/

Croatia HR: Electric Power Consumption: per Capita data was reported at 4,475.520 kWh in 2022. This records a decrease from the previous number of 4,506.596 kWh for 2021. Croatia HR: Electric Power Consumption: per Capita data is updated yearly, averaging 3,744.469 kWh from Dec 1990 (Median) to 2022, with 33 observations. The data reached an all-time high of 4,506.596 kWh in 2021 and a record low of 2,203.127 kWh in 1994. Croatia HR: Electric Power Consumption: per Capita data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Croatia – Table HR.World Bank.WDI: Environmental: Energy Production and Consumption. Electric power consumption measures the production of power plants and combined heat and power plants less transmission, distribution, and transformation losses and own use by heat and power plants.;IEA Energy Statistics Data Browser, https://www.iea.org/data-and-statistics/data-tools/energy-statistics-data-browser;Weighted average;

Data Center Power Market Outlook

The global data center power market size was valued at approximately USD 20 billion in 2023 and is expected to reach around USD 40 billion by 2032, growing at a compound annual growth rate (CAGR) of about 7.5% from 2024 to 2032. This growth can be attributed to the increasing demand for energy-efficient power solutions in data centers, which have become essential for the continuous and reliable operation of IT infrastructure. The rising adoption of cloud computing, the proliferation of big data, and the expansion of edge computing are key factors driving the market's expansion during the forecast period.

One of the primary growth factors in the data center power market is the exponential increase in data generation and storage needs. With the advent of emerging technologies like the Internet of Things (IoT), artificial intelligence (AI), and machine learning (ML), the volume of data generated has skyrocketed, necessitating the development of robust and efficient data center infrastructures. This surge in data has led to a heightened demand for data centers that can handle large-scale processing and storage requirements, subsequently driving the need for advanced power solutions to ensure seamless operations and minimize downtime.

Another significant driver of market growth is the shift towards sustainable and energy-efficient solutions. Governments and regulatory bodies worldwide are imposing stringent energy consumption and carbon emissions standards on data centers. This has compelled data center operators to adopt green energy solutions, such as advanced power distribution units (PDUs) and uninterruptible power supply (UPS) systems, to enhance energy efficiency. Moreover, the integration of renewable energy sources, like solar and wind power, into data center operations is gaining traction, further propelling the growth of the data center power market.

The increased focus on edge computing is also playing a crucial role in the market's expansion. As businesses seek to deliver faster and more efficient services to end-users, the deployment of edge data centers closer to the data source has become imperative. These edge data centers necessitate sophisticated power systems that can provide reliable and uninterrupted power supply in remote and often challenging environments. Consequently, the demand for innovative power solutions tailored to the requirements of edge computing is expected to witness significant growth in the coming years.

From a regional perspective, North America continues to dominate the data center power market, driven by the presence of major tech companies and a robust IT infrastructure. However, the Asia Pacific region is anticipated to exhibit the highest growth rate during the forecast period, fueled by the rapid digital transformation initiatives, increasing internet penetration, and the expansion of cloud-based services in countries like China, India, and Japan. Europe, Latin America, and the Middle East & Africa are also expected to witness steady growth, supported by ongoing investments in data center infrastructure and the adoption of advanced power management solutions.

Component Analysis

The data center power market by component is segmented into solutions and services. The solutions segment encompasses products like uninterruptible power supply (UPS) systems, power distribution units (PDUs), generators, and transfer switches and switchgears. These solutions are critical for ensuring the uninterrupted operation of data centers, protecting against power outages, and optimizing energy consumption. The increasing deployment of hyperscale data centers and the rising demand for energy-efficient power solutions are driving the growth of the solutions segment.

UPS systems, in particular, are witnessing substantial demand due to their ability to provide emergency power to data centers during outages and stabilize power fluctuations. Innovations in UPS technology, such as the integration of lithium-ion batteries and modular designs, are further enhancing their efficiency and reliability. Additionally, PDUs are gaining traction for their role in distributing electrical power to various data center components while ensuring optimal load balancing and energy management.

The services segment includes installation, maintenance, and consulting services that ensure the smooth operation

The BuildingsBench datasets consist of: Buildings-900K: A large-scale dataset of 900K buildings for pretraining models on the task of short-term load forecasting (STLF). Buildings-900K is statistically representative of the entire U.S. building stock. 7 real residential and commercial building datasets for benchmarking two downstream tasks evaluating generalization: zero-shot STLF and transfer learning for STLF. Buildings-900K can be used for pretraining models on day-ahead STLF for residential and commercial buildings. The specific gap it fills is the lack of large-scale and diverse time series datasets of sufficient size for studying pretraining and finetuning with scalable machine learning models. Buildings-900K consists of synthetically generated energy consumption time series. It is derived from the NREL End-Use Load Profiles (EULP) dataset (see link to this database in the links further below). However, the EULP was not originally developed for the purpose of STLF. Rather, it was developed to "...help electric utilities, grid operators, manufacturers, government entities, and research organizations make critical decisions about prioritizing research and development, utility resource and distribution system planning, and state and local energy planning and regulation." Similar to the EULP, Buildings-900K is a collection of Parquet files and it follows nearly the same Parquet dataset organization as the EULP. As it only contains a single energy consumption time series per building, it is much smaller (~110 GB). BuildingsBench also provides an evaluation benchmark that is a collection of various open source residential and commercial real building energy consumption datasets. The evaluation datasets, which are provided alongside Buildings-900K below, are collections of CSV files which contain annual energy consumption. The size of the evaluation datasets altogether is less than 1GB, and they are listed out below: ElectricityLoadDiagrams20112014 Building Data Genome Project-2 Individual household electric power consumption (Sceaux) Borealis SMART IDEAL Low Carbon London A README file providing details about how the data is stored and describing the organization of the datasets can be found within each data lake version under BuildingsBench.