A transient energy-agriculture model to predict energy footprint of vertical farms

Abstract

Vertical farms produce higher crop yields with optimised water and land resources and reduce the distance between crops and consumers; as a result, they have emerged as a compelling solution capable of shifting the farming practice towards a more sustainable production paradigm. However, the widespread implementation of VFs has been significantly hindered by high energy costs, which account for between 20 and 40% of their total costs. This paper presents an innovative transient model for evaluating the overall consumption of a VF with a temporal resolution of five minutes. The model considers energetic and agricultural phenomena to estimate the VF’s thermal load and food production. It applies an algorithm to estimate the COP of the heat pumps based on external conditions and part-load factor, thus offering a more accurate estimate of the overall electric energy-food ratio than other models in the existing literature. The impact of the COP evaluation algorithm demonstrated an increase in energy estimation accuracy of 40% for cooling and 100% for heating. The model was tested to investigate key performance indicators in nine different indoor growing conditions. The results show the impact of light intensity, indoor temperature, and the external climate on energy consumption, including heating, cooling, and dehumidification, and on water and carbon dioxide requirements. The highest temperature and lowest PPFD scenario yield the most energy-effective result of 6.28 ${\mathrm{kWh}}_{\mathrm{el}}·{\mathrm{kg}}^{-1}$.