ASABE Technical Library - Abstract

Click on “Download PDF” for the PDF version or on the title for the HTML version.
If you are not an ASABE member or if your employer has not arranged for access to the full-text, view access and subscription options

Early-phase quantification of farm machinery energy demand: a case study on load profiling with IoT devices to size hybrid electric–hydrogen systems

Published by the American Society of Agricultural and Biological Engineers, St. Joseph, Michigan www.asabe.org

Citation:  2026 ASABE Annual International Meeting  2601563.(doi:10.13031/aim.202601563)
Authors:   Pierluigi Rossi, Dr., Giorgia Di Domenico, Dr., Massimo Cecchini, Prof., Elisa Cioccolo, Dr., Eyerusalem Tesfay Gereziher
Keywords:   farm energy demand, agricultural machinery, load profiling, CAN bus data, early-phase sizing, hybrid energy systems

Abstract. Decarbonizing agriculture requires energy-demand estimates that are sufficiently detailed and operationally grounded, capturing the strong variability of loads across working hours, seasons, and production cycles from farming machinery. This research presents an early-phase methodology developed to quantify agricultural energy demand for the sizing of hybrid electric–hydrogen systems. At the present stage, the contribution focuses on tractor energy demand profiling based on operational datasets and on the derivation of representative indicators including 705 field operational records. The dataset was processed to obtain daily, weekly, and monthly summaries, together with indicators of cumulative demand and specific intensity expressed per working hour and per hectare. Results show marked variability across activities, tractors, and seasons. The operations contributing most to total annual consumption do not necessarily coincide with those showing the highest specific demand, indicating that average values alone are insufficient for preliminary sizing. The present contribution therefore provides an initial machinery-side benchmark for the subsequent integration of stationary farm loads, direct monitoring of additional end-uses, and simulation-based assessment of modular hybrid supply architectures.

(Download PDF)    (Export to EndNotes)