Controlled environment agriculture (CEA) is considered one of the most efficient ways of crop production. CEAs have the ability to control environmental conditions to maximize crop production. Indoor farms are considered one of the CEA systems that precisely control the environment, leading to high energy consumption in lighting, heating, cooling, and humidity control requirements. Enhancing the energy use efficiency (EUE) of indoor farms requires a better understanding of the energy characteristics of the system and crop production is needed. In this study, a steady state energy model and a machine learning based crop growth model were developed to evaluate energy-saving strategies for indoor lettuce production. The strategies included shifting photoperiod, utilizing heat tolerant crops, and adjusting air temperature settings at four different locations (Phoenix, AZ, Los Angeles, CA, Jacksonville, FL, and Boston, MA). The results showed that cultivar selection plays an important role in EUE improvement. Using high temperature settings with heat tolerant cultivars can increase the EUE of the system. However, increasing temperature setting alone does not significantly reduce energy consumption because of the increasing amount of energy needed for dehumidification. The geographical location of the indoor farm also affects energy consumption because of the different outdoor climate conditions. Boston, MA, which has the coldest outdoor air temperature, had the lowest energy consumption overall compared to the other three locations. Lastly, changing the photoperiod schedule from daytime to nighttime can reduce the electricity costs dramatically by avoiding the peak rate of electricity despite not having a significant reduction in energy consumption.
