Energy Consumption Analysis and Modeling of Cannabis Cultivation Facilities**

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Since legalization in 2018, indoor Cannabis cultivation has seen an accelerated growth in energy demand due to the need for greater process control and yield, pest, and disease management. Although data about the required energy demand for cannabis growth in Canada is limited, studies in US found that cannabis production is responsible for 1% of national electricity use, or USD $ 6 billion each year. Hence, tracking the energy consumption for cannabis cultivation facilities via real-time monitoring devices is paramount for understanding the correlation between the operation practises of the facilities and the energy consumption behaviour. The industry partner, Braingrid, provides a wireless analytics system that delivers real-time insights, alarms and reports for precision agriculture. The system leverages sensors to measure variables within the grow facility. These can include energy use, air temperature, humidity and carbon dioxide levels, soil or nutrient concentration and pH, and more. Braingrid is working on this project with the SGRL team at York University to develop a process that can receive real-time energy data collected from the cultivator facilitates via sensors and perform load disaggregation to distinguish the contribution of individual equipment categories to the overall energy use. Also, a mathematical model that suggests changes to the operation practises, which will eventually lead to the minimization of the energy consumption, will be developed. The model will be formulated as an optimization problem, where several objective functions will be considered: maximize the net profit, maximize the cannabis yield, minimize the energy consumption, and minimize the greenhouse gas emissions. The proposed model would take into account various operating constraints to satisfy the operation requirements of the facility e.g., growing needs and product quality. The efficacy of the proposed model will be tested for different case studies using real-time data collected from existing cannabis facilities in Ontario.**