Predictive Modeling of Energy Consumption for Cooling Ventilation in Livestock Buildings: A Machine Learning Approach

Carlos Alejandro Perez Garcia, Patrizia Tassinari, Daniele Torreggiani and Marco Bovo ()
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Carlos Alejandro Perez Garcia: Department of Agricultural and Food Sciences, University of Bologna, Viale G. Fanin 48, 40127 Bologna, Italy
Patrizia Tassinari: Department of Agricultural and Food Sciences, University of Bologna, Viale G. Fanin 48, 40127 Bologna, Italy
Daniele Torreggiani: Department of Agricultural and Food Sciences, University of Bologna, Viale G. Fanin 48, 40127 Bologna, Italy
Marco Bovo: Department of Agricultural and Food Sciences, University of Bologna, Viale G. Fanin 48, 40127 Bologna, Italy

Energies, 2025, vol. 18, issue 3, 1-16

Abstract: This research developed a predictive model using NeuralProphet to estimate energy consumption in the ventilation system of a dairy cattle farm. The necessity for energy management in livestock farming has increased due to the growing energy demands associated with climate control systems. Approximately two years of historical energy consumption data, collected through a smart monitoring system deployed on the farm, were utilized as the primary input for the NeuralProphet model to predict long-term trends and seasonal variations. The computational results demonstrated satisfactory performance, achieving a coefficient of determination (R 2 ) of 0.85 and a mean absolute error (MAE) of 27.47 kWh. The model effectively captured general trends and seasonal patterns, providing valuable insights into energy usage under existing operational conditions. However, short-term fluctuations were less accurately predicted due to the exclusion of exogenous climatic variables, such as temperature and humidity. The proposed model demonstrated superiority over traditional approaches in its capacity to forecast long-term energy demand, providing critical support for energy management and strategic decision-making in dairy farm operations.

Keywords: machine learning; energy efficiency; NeuralProphet; energy load forecast; cattle (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2025
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