Skip to main content
ARS Home » Midwest Area » Wooster, Ohio » Application Technology Research » Research » Research Project #440970

Research Project: Energy Balance Model Development for Indoor Farming Systems

Location: Application Technology Research

Project Number: 5082-21000-001-045-S
Project Type: Non-Assistance Cooperative Agreement

Start Date: Sep 20, 2021
End Date: Sep 19, 2025

In indoor farms, environmental variables including air temperature and humidity are commonly under control. Heating, ventilation, and air conditioning (HVAC) systems play a vital role in maintaining desired environments through heating, cooling, and humidity control processes. Precisely controlled environments favor plant growth, but electricity consumption is one of the major costs in indoor farms. Lighting and HVAC all require significant amounts of electrical energy to operate. Crop stage also significantly affects the internal heat and water vapor gained through evapotranspiration. Comprehensive tools to estimate energy consumption and guidelines for HVAC system design and equipment selection are still lacking. A few studies have investigated indoor farm energy consumption; however, there is no simple rule that can be applied to estimate energy consumption and calculate heat transfer for different indoor farming systems (Graamans et al., 2017; Harbick & Albright, 2016; Zhang & Kacira, 2020). HVAC sizing/design guidelines for most building types have been well established by various organizations, such as ASHRAE (American Society of Heating Refrigeration and Air Conditioning Engineers). Heating, cooling, and humidity design loads vary with internal energy loads (e.g., electric equipment, people, and plants), building characteristics (e.g., insulation materials, orientation, and shape; Graamans et al., 2020), and climate conditions (e.g., radiation, temperature, and wind speed). Lighting electricity depends on the efficacy of the luminaires (µmol J-1) and the light requirements of different crops. Crops also convert a large amount of sensible heat into latent heat by evaporating water into the air during transpiration, sometimes resulting in high air humidity and low vapor pressure deficit (Graamans et al., 2017). Therefore, transpiration models are key to estimating heat and water vapor loads and energy consumption for climate control. Although transpiration models have been well developed for greenhouse applications, transpiration rates for some crops are still unknown. An energy estimation tool for indoor farming is needed for growers and HVAC engineers to easily calculate heating, cooling, and dehumidifying loads and correctly size HVAC systems to meet operational requirements. Most energy models for CEA assume a single thermal zone, where temperature, humidity, and CO2 concentrations are homogenous. This serves as a reasonable baseline, but in real CEA environments, effects such as temperature stratification and air movement due to stack effect are present. Simulating these effects using techniques such as computational fluid dynamics (CFD) may facilitate modular HVAC designs that have finer control over conditions at the plant canopies. The objectives of this project are to 1) identify benchmark values of internal sensible and latent heat gains in indoor farms; 2) develop energy balance equations for energy consumption estimation; 3) develop an Excel-based tool for HVAC loads calculation; and 4) develop a CFD simulation that can model multiple thermal zones and the response of modular environmental control systems.

Objective 1: Identify benchmark values of internal sensible and latent heat gains in indoor farms. Measurement of internal heat gains from equipment and plants is necessary to make accurate assessments of their impact on HVAC loads. In this project, equipment commonly used in indoor farms, including LED lights, pumps, fans will be experimentally studied for their heat loss characteristics, including efficiency, total power consumption, radiant/convective split, and the relationship between manufacturer’s power ratings and actual power consumption. Typical values of these features will be summarized in tables and guides will be provided for using these data for energy consumption and heat transfer analysis. Objective 2: Develop energy balance equations for energy consumption estimation. The project will be conducted in a shipping container. The products grown in this project include lettuce, kale, and spinach. Holistic energy balance equations will be developed to estimate the energy consumption of HVAC systems for heating, cooling, and dehumidification. Energy modeling will consider outdoor climates, building materials and properties, internal heat gain from lighting systems, sensible and latent heat exchanges by humidification and evapotranspiration, and HVAC characteristics. Crop transpiration rates will be monitored and recorded. Transpiration equations will be developed for transpiration estimation. The energy balance at crop canopies will be determined with the energy balance at the plant canopy and the transpiration equations. The energy consumption data of the shipping container will be used for validating the accuracy of the estimation. Objective 3: Develop an Excel-based tool for HVAC loads calculation. An HVAC sizing tool will be developed in an Excel file with VBA. The parameters in the energy balance equations will be included in the calculator including the heat transfer through the building, the heat flow due to conduction and convection and the heat gain from solar heating of the opaque building envelope, the internal heat outputs from the sole source lighting, appliances, persons, and other electric devices, the latent heat flux due to plant transpiration, and the heat flux removed/added by the HVAC system. Various insulation properties and equipment selections will be available in the calculator for HVAC sizing. The tool will be suitable for leafy green production systems for HVAC sizing and selection. It can potentially be modified to fit other indoor production systems if plant transpiration data and system features are provided. Objective 4: Develop a CFD-based simulation tool for modeling multiple thermal zones A CFD model will be developed to study the effect of multiple thermal zones on the air temperature distribution. The results will aid the zoning of the HVAC system and HVAC loads calculation. In addition, the approaches to integrate CFD into an energy simulation program (EnergyPlus) will be studied. It can be applied to explore the potential use of coupling CFD and building energy modeling to optimize the operation of indoor farms.