Improving Smart Farm Heating Performance and Energy Efficiency by Means of AI Data Center Waste-Heat Recovery

This study evaluated the seasonal heating performance of a single-span strawberry greenhouse maintained at a constant heating setpoint temperature using a conventional air-source heat pump (ASHP) or water-to-water heat pump (DCHP) connected to a data center.Python-based dynamic simulations were conducted to calculate the greenhouse's energy balance, incorporating the factors of conduction, convection, and ventilation driven by weather inputs.The heat pump performance was estimated by means of the temperature-based coefficient of the performance correlations.The results indicate that integrating a greenhouse with a data center improves seasonal efficiency and reduces electricity consumption.The DCHP increased the seasonal performance factor from 3.40 (ASHP) to 3.94, resulting in an absolute gain of 0.54 (approximately 15.8%).Additionally, annual compressor electricity consumption was reduced from 38,800 kWh to 26,942 kWh, resulting in savings of 11,858 kWh (approximately 30.5%).These savings are particularly significant during the winter months, when a warmer and more stable heat source can enhance the performance of the heat pump.Considering the energy mix factor, the annual greenhouse gas emissions decreased from 18,550 kg CO 2 -equivalent to 12,881 kg CO 2 -equivalent, highlighting a clear carbon reduction benefit in addition to energy savings.

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Publication Details

Journal
Horticultural Science and Technology
Published
2025-12-17
DOI
https://doi.org/10.7235/hort.20250079
Primary Topic
Scientific Research Methodologies and Applications
Type
article
Field-Weighted Citation Impact
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article

Improving Smart Farm Heating Performance and Energy Efficiency by Means of AI Data Center Waste-Heat Recovery

Siwon Yoon, Joo Hyun Moon, S. An, Seo Yeong Kang et al.
Horticultural Science and Technology
Scientific Research Methodologies and Applications
article

Improving Smart Farm Heating Performance and Energy Efficiency by Means of AI Data Center Waste-Heat Recovery

Siwon Yoon, Joo Hyun Moon, S. An, Seo Yeong Kang, Seungwon Seok
article en

Abstract

This study evaluated the seasonal heating performance of a single-span strawberry greenhouse maintained at a constant heating setpoint temperature using a conventional air-source heat pump (ASHP) or water-to-water heat pump (DCHP) connected to a data center.Python-based dynamic simulations were conducted to calculate the greenhouse's energy balance, incorporating the factors of conduction, convection, and ventilation driven by weather inputs.The heat pump performance was estimated by means of the temperature-based coefficient of the performance correlations.The results indicate that integrating a greenhouse with a data center improves seasonal efficiency and reduces electricity consumption.The DCHP increased the seasonal performance factor from 3.40 (ASHP) to 3.94, resulting in an absolute gain of 0.54 (approximately 15.8%).Additionally, annual compressor electricity consumption was reduced from 38,800 kWh to 26,942 kWh, resulting in savings of 11,858 kWh (approximately 30.5%).These savings are particularly significant during the winter months, when a warmer and more stable heat source can enhance the performance of the heat pump.Considering the energy mix factor, the annual greenhouse gas emissions decreased from 18,550 kg CO 2 -equivalent to 12,881 kg CO 2 -equivalent, highlighting a clear carbon reduction benefit in addition to energy savings.

Horticultural Science and TechnologyVol. 43
Jeonbuk National University (KR)
Openalex Percentile: Top 63%
Scientific Research Methodologies and Applications
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