Quantification of dairy farm energy consumption to support the transition to sustainable farming

Todic, Tamara and Stankovic, Lina and Stankovic, Vladimir and Shi, Jiufeng (2022) Quantification of dairy farm energy consumption to support the transition to sustainable farming. In: International Conference on Smart Computing 2022, 2022-06-20 - 2022-06-24, Aalto University, Espoo, Finland.

[thumbnail of Todic-etal-ICSC-2022-Quantification-of-dairy-farm-energy-consumption-to-support-the-transition-to-sustainable-farming]
Preview
Text. Filename: Todic_etal_ICSC_2022_Quantification_of_dairy_farm_energy_consumption_to_support_the_transition_to_sustainable_farming.pdf
Accepted Author Manuscript
License: Strathprints license 1.0

Download (706kB)| Preview

Abstract

As the need for using energy-efficient machinery escalates, energy consumption estimation plays an important role in decision support and planning in the agri-sector. Within the present research study, energy consumption in dairy farms was examined. A deep learning-based load disaggregation approach was used to develop data-driven models to quantify individual energy consumption of milk production-related devices of dairy farms, from a single aggregate measurement. According to the experiments conducted on three dairy farms in Germany, load disaggregation from a single aggregate meter is a viable, cheaper alternative to submetering multiple pieces of equipment to accurately quantify electricity consumption at scale in dairy farms in order to provide the decision support needed to inform measures for tackling climate change.

ORCID iDs

Todic, Tamara, Stankovic, Lina ORCID logoORCID: https://orcid.org/0000-0002-8112-1976, Stankovic, Vladimir ORCID logoORCID: https://orcid.org/0000-0002-1075-2420 and Shi, Jiufeng;