Abstract

This article presents an algorithmic solution for calculating the heating efficiency of an industrial facility when water cooling is used as the setup for mining farm equipment. Crypto mining belongs to industries that are actively developing, and a high volume of electricity consumption is generated. Efficient usage of wasted heat is a key factor in energy efficiency improvement, and also contributes to sustainability within energy systems. In this paper, this study occupies a vital place, as an increase in the more efficient exploitation of thermal resources leads not only to reduced consumption but also to reduced carbon emissions. That means dual targets-environmental and economic are achieved.  The novelty lies in collecting and applying an integrated methodology for assessing the effectiveness of heating systems while addressing water cooling for mining equipment. It will use the three approaches: energy balance, exergy analysis, and CFD technology simulation, together with a short review of regulatory requirements such as ASHRAE and Energy Reuse Factor, to give an appropriate thermal potential assessment and loss source identification, hence optimization of design and operation for heating systems based on mining farms. The main conclusions are that a simple energy balance is sufficient for small-scale facilities. At the same time, more complex methods, such as exergy analysis and CFD simulation, are required for large data centers and industrial sites with higher loads. System efficiency improves drastically with the application of heat pumps, along with a reduction in hydraulic and pump equipment losses. The economic benefits of heat utilization from mining farms will be able to compete with traditional heat sources, such as gas boilers. This will be of interest to engineers, designers, and researchers working on energy efficiency. This will attract investors interested in sustainable yet economically viable solutions that can be used for heating industrial facilities.

Keywords

  • heat recovery
  • mining
  • water cooling
  • exergy analysis
  • energy balance
  • CFD modeling
  • heat pumps
  • energy saving
  • sustainable development

References

  1. 1. Ashrae. (2016). Data Center Power Equipment Thermal Guidelines and Best Practices. Ashrae.
  2. https://www.ashrae.org/File%20Library/Technical%20Resources/Bookstore/ASHRAE_TC0909_Power_White_Paper_22_June_2016_REVISED.pdf
  3. 2. Ashrae. (2021). Emergence and Expansion of Liquid Cooling in Mainstream Data Centers. Ashrae.
  4. https://www.ashrae.org/file%20library/technical%20resources/bookstore/emergence-and-expansion-of-liquid-cooling-in-mainstream-data-centers_wp.pdf
  5. 3. Bryant, M. (2025, March 28). The heat you need at a reasonable price: how district heating can speed the switch to clean energy. The Guardian.
  6. https://www.theguardian.com/environment/2025/mar/28/the-heat-you-need-at-a-reasonable-price-how-district-heating-can-speed-the-switch-to-clean-energy
  7. 4. Danfoss. (2023). Data center policies in the EU. Danfoss.
  8. https://www.danfoss.com/en/markets/buildings-commercial/shared/data-centers/data-center-policies-in-the-eu/
  9. 5. Danfoss. (2024). Next Generation Decarbonized Data Center System Design. FDCA.
  10. https://www.fdca.fi/wp-content/uploads/2024/10/DC-Sustain_Decarb-Future-Data-Summit-Final.pdf
  11. 6. Digiconomist. (2025). Bitcoin Energy Consumption Index. Digiconomist.
  12. https://digiconomist.net/bitcoin-energy-consumption
  13. 7. European Commission. (2023). Heating and Cooling Degree Days - Statistics. European Commission.
  14. https://ec.europa.eu/eurostat/statistics-explained/SEPDF/cache/92378.pdf
  15. 8. IEA. (2023, July 11). Data Centres and Data Transmission Networks. IEA.
  16. https://www.iea.org/energy-system/buildings/data-centres-and-data-transmission-networks
  17. 9. Innovation Norway. (2016). Conversion Guidelines - Greenhouse gas emissions. Innovation Norway. https://www.eeagrants.gov.pt/media/2776/conversion-guidelines.pdf
  18. 10. Liu, W., Jin, B., Wang, D., & Yu, Z. (2023). Performance modeling and advanced exergy analysis for a low-energy consumption data center with waste heat recovery, flexible cooling, and hydrogen energy. Energy Conversion and Management, 297, 117756–117756.
  19. https://doi.org/10.1016/j.enconman.2023.117756
  20. 11. Moote, K., & Vasantham, K. (2025, March 17). Global Institutional Investor Survey 2024 Report. The Harvard Law School Forum on Corporate Governance.
  21. https://corpgov.law.harvard.edu/2025/03/17/global-institutional-investor-survey-2024-report/
  22. 12. Oliver, M., & Pan, D. (2017). District Heating Network Pipe Sizing. Smart Energy Systems. https://smartenergysystems.eu/wp-content/uploads/2019/04/thrid_-_oliver_martin-du_pan.pdf
  23. 13. Pakere, I., Goncarovs, K., Grāvelsiņš, A., & Zirne, M. A. (2024). Dynamic Modelling of Data Center Waste Heat Potential Integration in District Heating in Latvia. Energies, 17(2), 445–445.
  24. https://doi.org/10.3390/en17020445
  25. 14. Reuter, S., Schmidt, R.-R., Marx, N., & Ortmann, P. (2022). Potential future and conventional waste heat sources. IEA HPT. https://heatpumpingtechnologies.org/annex57/wp-content/uploads/sites/69/2023/05/annex57-task-12-new-heat-pump-sources-v095.pdf
  26. 15. Robinson, A. (2023). Status of Liquid Cooling of Data Centres: Some Answers and Some Questions. Nexalus. https://www.nexalus.com/wp-content/uploads/2023/07/Status-of-Liquid-Cooling-of-Data-Centres.pdf
  27. 16. Segal, M. (2025, June 10). Investors Turning Outside U.S. to Look for Climate Investment Opportunities: Survey. ESG Today. https://www.esgtoday.com/investors-turning-outside-u-s-to-look-for-climate-investment-opportunities-survey/
  28. 17. Spencer, T., & Singh, S. (2024, October 18). What the data centre and AI boom could mean for the energy sector. IEA. https://www.iea.org/commentaries/what-the-data-centre-and-ai-boom-could-mean-for-the-energy-sector
  29. 18. Trading Economics. (2025). EU Natural Gas TTF. Trading Economics.
  30. https://tradingeconomics.com/commodity/eu-natural-gas
  31. 19. Yuan, X., Liang, Y., Hu, X., Xu, Y., & Chen, Y. (2023). Waste heat recoveries in data centers: A review. Renewable & Sustainable Energy Reviews, 188, 113777–113777.
  32. https://doi.org/10.1016/j.rser.2023.113777