Market Snapshot: Energy demand from data centers is steadily increasing, and AI development is a significant factor

Release date: 2024-10-02

There are currently an estimated 239 data centers^Definition* operating across Canada,^{Footnote 1} and the industry is expanding rapidly.^{Footnote 2} Data centers and their data transmission networks consume a lot of energy. According to the International Energy Agency (IEA), in 2022, they consumed an estimated 460 terawatt-hours (TWh) globally, or roughly 1.4-1.7% of global electricity use.^{Footnote 3Footnote 4} That amount of energy is roughly equivalent to 71% of Canada's electricity generation that same year,^{Footnote 5} and the IEA projects global data center energy consumption will double by the end of 2026. The rapid growth of artificial intelligence (AI) applications, particularly large language models and machine learning, is a significant contributor to this rising energy demand, as AI workloads^Definition* require substantial computing power. Multiple factors make Canada an attractive destination for data centers:

1. Relatively low electricity prices in some regions
2. Significant renewable^Definition* and clean electricity resources
3. A relatively cool climate^{Footnote 6}

Figure 1: Data centers in Canadian cities

Source:Data Center Map - Canada Data Centers

Description: This interactive map shows the cities where data centers are located in Canada. The relative size of each circle indicates the number of data centers in each city. Most are found in the southern part of Canada. Toronto and Montreal both have the most (at 81 and 48 respectively) while smaller cities like Halifax and Saskatoon have significantly less (4 and 2 respectively).

Canadian Data Center Landscape

Canada's data center landscape is driven by low electricity costs, particularly in provinces like Quebec and British Columbia, where hydroelectricity is abundant and relatively affordable. The country's clean energy grid, with over 80% of electricity coming from non-emitting sources, can also make it attractive for companies looking to build new data centers with a low carbon footprint. Additionally, Canada's cool climate further enhances the energy efficiency of data centers by reducing cooling costs.^{Footnote 7Footnote 8Footnote 9}

In Canada, utilities and system operators are factoring data center electricity usage into their outlooks. For example, Hydro Québec anticipates an increase of 4.1 TWh in data center demand from 2023 to 2032 in its most recent electricity supply plan.^{Footnote 10} The Ontario Independent Electric System Operator (IESO) lists data center electricity demand growth as a key driver in expected power use in Ontario's commercial sector.^{Footnote 11} The Alberta Electric System Operator (AESO)'s latest outlook includes a High Electrification scenario that includes higher electricity demand from data centers, among other areas of demand growth.^{Footnote 12}

Figure 2: Data centers by province

Source:Data Center Map - Canada Data Centers

Description: This interactive map illustrates the concentration of data centers in each province in Canada. The darkest shade indicates the highest number of data centers, while the lightest shade indicates the fewest number of data centers. Quebec has the highest number followed by Ontario and British Columbia.

Impact of large language models and artificial intelligence on energy demand

Global data center workloads^Definition* nearly tripled between 2015 and 2019, while energy demand remained relatively stable at about 200 terawatt-hours (TWh) per year.^{Footnote 15} This stability is largely due to continuous advancements in energy efficiency. However, since around 2020, these efficiency gains have slowed, contributing to a rapid increase in energy consumption from data centers.^{Footnote 16Footnote 17}

Large Language Models (LLMs), such as ChatGPT and Microsoft Copilot, have transformed the field of artificial intelligence (AI). As these models have expanded in size and capability, the computational^Definition* resources, and consequently the energy required for their training^Definition*, has grown exponentially. As these models are becoming mainstream, the energy demand for processing individual queries has also surged, and AI-enabled queries generally consume more energy compared to traditional and competing technologies. For example, an average ChatGPT query requires about 10 times as much electricity to process as a Google search.^{Footnote 18} By 2030, AI is expected to drive a cumulative 160% increase in data center energy consumption globally.^{Footnote 19}

Training increasingly complex AI models^Definition* has seen computational energy demands doubling approximately every nine months in recent years, and this trend of growth will likely continue.^{Footnote 20Footnote 21} However, efforts to enhance AI efficiency, such as the use of specialized hardware and software optimizations, could mitigate some of this growth.

Date modified: 2024-10-01

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