GDE720 – Week 4: Data Centres as an Alternative Source of Heat

What is a data center? It’s a boxy building that houses servers to store, process, and send data. With the increasing demand for digital services, data centers are more widely spread than ever. There are 7.2 million data centers in the world, with USA, UK, and Germany in the lead. These data centers are also consuming energy at rates even higher than some countries. (Welle (www.dw.com), 2022)

(Welle (www.dw.com), 2022)

While this may seem like a big waste of energy and a definite contributor to our ever-growing climate crisis, there may be an upside to the energy consumption of data centers. Typically, the heat that the IT equipment in these data centers generate is cooled off or removed, there is a possibility that they can be recovered and re-used in nearby buildings. (CelciusCity, 2020)

In a European setting, this is especially relevant at a time when Western Europe is facing off against Russia and the threat of losing a major energy source is looming ahead. Currently, the EU relies on Russia for more than 40% of its natural gas, essentially used for fueling gas boilers that heat homes. (De La Garza, 2022) 

The energy needed to cool off the IT equipment is very high in a data center, often producing air at temperatures of about 25 – 40 °C. (CelciusCity, 2020) In theory, the heat can be transferred to a district heating network’s supply. (CelciusCity, 2020)

In the center of Stockholm is an energy-efficient data center with a cooling system that is linked to the central district’s heating and cooling network. Deliveries of heat to the district heating network using the heat pump facility primarily take place at periods when the outdoor temperature is below 7 degrees Celsius. When the outdoor temperature is at least 20 degrees Celsius, the plant produces district cooling at full capacity for the district cooling system. (Öppen Fjärrvärme, n.d.)


(Öppen Fjärrvärme, n.d.)

For this week’s challenge, it would be interesting to imagine how data centers can be integrated with other major European cities to provide heating (and cooling) solutions in lieu of both the climate crisis and recent political tensions. Part of the European Commissions’ targets and strategies to move to climate neutrality by 2050 is to improve energy efficiency for new and existing buildings, including the shift to electric heating or heat pumps, switch towards more low-carbon fuels, and install district heating systems. (International Energy Agency, 2020) 

I’ll be comparing Google’s data center’s heat outputs to the heating requirements of major European cities to see how much can be benefited from this lost energy.

Inspiration

MVRD – Metacity / Datatown

MVRDV’s Metacity / Datatown is my source of inspiration for this project. Datatown, a data visualization project by this Dutch architecture group, is a city constructed only from the information.

“One way to study the world of numbers is through the use of ‘extremizing scenarios’. They lead to frontiers, edges, and therefore to inventions.” (MVRDV, 1999)

It’s interesting to imagine different scenarios for urban planning based on the optimization of resources through raw data. 

Federica Fragapane

Federica Fragapane is an information designer based in Italy. The beautiful forms she uses to visualize data have helped her stand out as a designer in this field. Fragapane has quoted the book “Data Feminism” by Catherine D’Ignazio and Lauren F. Klein regarding the aesthetics of her work: “In the case of data visualization, what is excluded is emotion and affect, embodiment and expression, embellishment and decoration. These are aspects of the human experience associated with women and thus devalued by the logic of our master stereotype”. In this sense, the beauty of it has helped important information stand out far more than had it followed a more toned-down appearance. 

Google’s Data Centers

Google currently has 6 operational data centers in Europe:

  • Dublin, Ireland
  • Eamshaven, Netherlands
  • Fredericia, Denmark
  • Hamina, Finland
  • Middenmeer, Netherlands
  • St. Ghislain, Belgium

Let’s look at the energy consumption of each data center, as this directly equals the amount of heat that can be recovered. (Dataspan, 2019) If we calculate the heat recovery potential of data centers in Northern/Central Europe, then we need to use the average PUE of a data center in this region, which is 1.72. The average annual electricity consumption is 13,684 MWh, and the average annual IT consumption is 7,871 MWh, which we can safely assume is the output for the purpose of heat recovery for each data center. (Avgerinou, Bertoldi and Castellazzi, 2017)

Heating Residential Districts

If we compare the heating consumption requirements per dwelling in any given European city, we can compare the number of dwellings in that city to the overall heat output of the total number of data centers in that city.

(Odyssee-Mure, 2019)

  • 1 Toe = 11.63 MWh

Brussels, Belgium

1.27 toe / 14.7 MWh, 559,938 dwellings = 8,231,088 MWh

20 Data Centers x 7,871 MWh = 157,410 MWh

Data centers can contribute to 1.9% of the city’s residential heating requirements

Paris, France

0.889 toe / 10.3 MWh, 1,140,772 dwellings = 11,749,951 MWh

71 Data Centers x 7,871 MWh = 558,841 MWh

Data centers can contribute to 4.7% of the city’s residential heating requirements

Frankfurt, Germany

1.03 toe / 11.9 MWh, 395,000 dwellings = 4,731,665 MWh

64 Data Centers x 7,871 MWh = 503,744 MWh

Data centers can contribute to 10.6% of the city’s residential heating requirements

Amsterdam, The Netherlands

0.892 toe / 10.3, 807,876 dwellings = 8,321,122 MWh

52 Data Centers x 7,871 MWh = 409,292 MWh

Data centers can contribute to 4.9% of the city’s residential heating requirements

Visualizing this Data

A large part of this data visualization depends on how we can reimagine these cities based on their current facilities and consumption behaviors. While the heating contributions noted above might seem small, they can essentially heat entire districts, especially in densely populated city centers where a system like this one may be most efficient. The second part of this calculation then would be to estimate how many dwellings can be heated by the total number of data centers listed above. The European average number of people per dwelling is 3 (Eurostat, 2015), so we’ll apply that to then find a suitable district to compare our estimates to.

Brussels, Belgium

1.9% of 559,938 dwellings is 10,638 dwellings = 31,914 people

This is the equivalent to 18% of the City of Brussels (153,483 in total)

Paris, France

4.7%  of 1,140,772 dwellings is 53,616 dwellings = 160,848 people

This is the equivalent of the Arrondissements 1, 2. 3, 4, and 5 (160,333 in total)

Frankfurt, Germany

10.6% of 395,000 dwellings is 41,870 dwellings = 125,610 people

This is the equivalent of the Innenstadt I, II, and III (153,483 in total)

Amsterdam, The Netherlands

4.9% of 807,876 dwellings is 39,585 dwellings = 118,744 people

This is equivalent to 137% of the Center of Amsterdam (86,422 in total)

For the purpose of the visualization, only the dwellings and the borders of these city districts will be visualized. Every 1,000 dwellings are represented by a thin line, offset to the interior (or exterior) of the district borders.

Other distinguishing features, like the River Seine in Paris for example, will be added to give viewers a familiar perspective. Data Centers are represented by dark squares, to scale. They are based on the average Data Center floor area, which is 2,616m2. (Avgerinou, Bertoldi and Castellazzi, 2017)

They will be placed within the district borders to visualize how much space such data centers occupy in real life. 

A legend or key is placed to give viewers a better understanding of what they’re looking at, while still keeping some elements of vagueness to allow for a bit of study of the visual.

In summary, the practice of mapping heating alternatives also gives a visual perspective of approximately how much potential there is in rethinking the usage of one of the most valuable building typologies in the digital age: the data center.

Reference list

Avgerinou, M., Bertoldi, P. and Castellazzi, L. (2017). Trends in Data Centre Energy Consumption under the European Code of Conduct for Data Centre Energy Efficiency. Energies, [online] 10(10), p.1470. Available at: https://www.mdpi.com/1996-1073/10/10/1470.

CelciusCity (2020). Waste heat from data centres. [online] Available at: https://celsiuscity.eu/wp-content/uploads/2020/06/Waste-heat-from-data-centres.pdf.

Dataspan. (2019). How to Calculate Cooling Requirement for your Data Center. [online] Available at: https://dataspan.com/blog/how-to-calculate-cooling-requirements-for-a-data-center/.

De La Garza, A. (2022). Heat Pumps Are a Weapon in the E.U.’s Face-Off With Russia. [online] Time. Available at: https://time.com/6157947/heat-pumps-europe-russia/ [Accessed 12 Apr. 2022].

European Commission (2020). Energy-efficient Cloud Computing Technologies and Policies for an Eco-friendly Cloud Market | Shaping Europe’s digital future. [online] digital-strategy.ec.europa.eu. Available at: https://digital-strategy.ec.europa.eu/en/library/energy-efficient-cloud-computing-technologies-and-policies-eco-friendly-cloud-market [Accessed 12 Apr. 2022].

Eurostat (2015). Archive:People in the EU – statistics on housing conditions. [online] ec.europa.eu. Available at: https://ec.europa.eu/eurostat/statistics-explained/index.php?title=People_in_the_EU_%E2%80%93_statistics_on_housing_conditions&oldid=266849.

Google (2021). Efficiency – Data Centers – Google. [online] Google Data Centers. Available at: https://www.google.com/about/datacenters/efficiency/.

International Energy Agency (2020). European Union 2020 – Energy Policy Review. [online] https://www.iea.org/. Available at: https://iea.blob.core.windows.net/assets/ec7cc7e5-f638-431b-ab6e-86f62aa5752b/European_Union_2020_Energy_Policy_Review.pdf.

Masanet, E., Shehabi, A., Lei, N., Smith, S. and Koomey, J. (2020). sciencemag.org SCIENCE PHOTO: GOOGLE POLICY FORUM Downloaded from. Science, [online] 367(6481), p.6481. Available at: https://datacenters.lbl.gov/sites/default/files/Masanet_et_al_Science_2020.full_.pdf.

MVRDV (1999). MVRDV – Metacity / Datatown. [online] http://www.mvrdv.nl. Available at: https://www.mvrdv.nl/projects/147/metacity–datatown-.

Odyssee-Mure (2019). Heating consumption per m2 | Heating energy consumption | ODYSSEE-MURE. [online] http://www.odyssee-mure.eu. Available at: https://www.odyssee-mure.eu/publications/efficiency-by-sector/households/heating-consumption-per-m2.html [Accessed 16 Apr. 2022].

Öppen Fjärrvärme. (n.d.). Bahnhof data centre Thule. [online] Available at: https://www.opendistrictheating.com/case/bahnhof_thule/ [Accessed 12 Apr. 2022].

Welle (www.dw.com), D. (2022). Big data centers are power-hungry, but increasingly efficient | DW | 24.01.2022. [online] DW.COM. Available at: https://www.dw.com/en/data-centers-energy-consumption-steady-despite-big-growth-because-of-increasing-efficiency/a-60444548.

http://www.enerdata.net. (2021). Evolution of households energy consumption patterns across the EU. [online] Available at: https://www.enerdata.net/publications/executive-briefing/households-energy-efficiency.html [Accessed 12 Apr. 2022].

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