Développement d’indicateurs de performance pour la caractérisation d’espace d’agriculture en environnement contrôlé à l’aide de modèles numériques

Abstract

Greenhouse production in Quebec, driven by policies aimed at greater food autonomy, faces significant challenges in terms of energy performance. However, the scientific literature in this field remains fragmented: key performance indicators (KPI) are often heterogeneous, focused on either agronomic or energy aspects, and rarely tailored to northern climate conditions. Moreover, few approaches offer a structured method to link numerical model outputs with indicators that are truly useful for analysis and decision-making in controlled environment agriculture (CEA) This thesis proposes a standardized evaluation framework to analyze the performance of agricultural greenhouses using key performance indicators. Two modeling approaches are used: a simplified quasi-static model built in Excel, and a detailed dynamic model simulated in TRNSYS. The objective is to identify, test, and compare relevant KPI while assessing the ability of both tools to generate reliable, reproducible, and actionable results in different Quebec contexts. The analysis led to the selection of 10 indicators from an initial set of 16 found in the literature, prioritizing those that are representative, non-redundant, and applicable to various CEA types. These thermal, radiative, and energy indicators were evaluated across three Quebec climates to assess their robustness and applicability. Based on their strengths and limitations, two new indicators were introduced: the Thermal Growing Season Limit TGSLLimit, which measures the actual growing season length based on a critical thermal threshold, and the Overall Growing Season Length (OGSL), which integrates both temperature and lighting constraints to estimate the period truly favorable to crop growth without external energy inputs. This latter indicator revealed growing seasons that are one to two months shorter than those estimated by the traditional KPI. This work thus proposes a complete, flexible, and reproducible method for evaluating CEA performance. By combining numerical modeling with a rigorous selection of standardized indicators, it provides a practical tool for improving design, energy planning, and crop strategies in controlled environments. This approach contributes directly to a more sustainable and resilient agriculture, adapted to Quebec’s climate realities.

Date	5 Aug 2025
Original language	French
Awarding Institution	École de technologie supérieure
Supervisor	Danielle Monfet (Supervisor) & Didier Haillot (Co-supervisor)