Validation of a building energy model of a hydroponic container farm and its application in urban design

Plant factories have developed within urban contexts following efforts to expand local food production, create local jobs, and provide alternatives to conventional agriculture with lower greenhouse gas emissions. One plant factory system, container farms, consists of artificially lit, vertically stacked hydroponic farms inside retrofitted shipping containers and support crop production in otherwise unused locations regardless of climate and daylight availability. Given their high energy intensity, municipalities considering container farms require reliable models to study their overall environmental performance and feasibility. While previous studies have used co-simulators to consider plant-air interactions within building performance simulation (BPS) tools, energy validation studies are lacking for such models. This research presents the validation of an EnergyPlus model of a hydroponic container farm in Boston, Massachusetts based on nine months of measured data. Despite shortcomings in predicting of hourly conditioning energy, the resulting calibrated energy model achieves a Normalized Mean Bias Error of 3% and a Coefficient of Variation of the Root-Mean-Square Error of 11%. Results show that through representing plant-air interactions within EnergyPlus and modeling cooling coefficient of performance as a function of outdoor air temperature, stakeholders can reliably predict annual container farm energy use. (c) 2021 Elsevier B.V. All rights reserved.

Automated summary

Plant factories have emerged in urban areas to increase local food production, create job opportunities, and provide environmentally friendly alternatives to traditional agriculture. Container farms, a type of plant factory system, use artificial lighting and hydroponic farming practices to support crop production in urban settings regardless of climate conditions. By validating an EnergyPlus model of a hydroponic container farm in Boston, stakeholders can reliably predict energy usage and optimize the environmental performance of container farms.