Date of Award

9-25-2024

Publication Type

Thesis

Degree Name

M.A.Sc.

Department

Mechanical, Automotive, and Materials Engineering

Keywords

Controlled Environment Agriculture;Energy Modeling;Life-Cycle Cost Analysis;TRNSYS

Supervisor

David Ting

Supervisor

Rajeev Ruparathna

Abstract

Conventional greenhouses (CGs) in colder regions consume substantial energy, primarily powered by fossil fuels, leading to detrimental environmental impacts. High energy demand poses a major obstacle to constructing these greenhouses. To enhance their sustainability, this research explores energy-efficient strategies to optimize solar insolation availability by modifying the greenhouse orientation, design, and roof inclination. Additionally, a methodology for greenhouse energy modeling (GEM) was proposed due to the unavailability of standardized guidelines or works of literature. GEM allows for predicting energy requirements and assessing the economic viability of greenhouses in advance. This methodological framework was tested using an experimental Chinese solar greenhouse (CSG) in Elie, Manitoba, revealing that GEM could accurately predict hourly internal air temperatures with an average prediction error of about 1.6%. The proposed framework was applied to simulate the heating and cooling demand of an Advanced Growing Building (AGB), indicating that it consumes 88% less heating and cooling energy than a CG producing the same crop output. AGB was simulated for different Canadian locations such as Toronto, Vancouver, Edmonton, and Winnipeg along with crops such as lettuce, tomato, and strawberry. The study shows that Vancouver is the most preferred location for growing all three crops, followed by Toronto, Winnipeg, and Edmonton. An optimization study was conducted using the design of experiments (DOE) and modified binary optimization approach, varying parameters individually that influence either heating, cooling demand, or the life-cycle cost (LCC). The results illustrated that cases 6D3A-1, 6K3A-1, and 6L3A-1 are optimal designs that can grow lettuce crops with a heating and cooling demand of 1.6 kW/kg and LCC of 61 cents/kg, which was 27% and 37% less, respectively, than the AGB base case. This research provides valuable insights for researchers and growers to analyze the energy-efficient parameters that significantly impact energy performance, as well as the effects of location and crop type within the greenhouse.

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