Electrifying Montreal International Airport: A Living Lab Demonstrating Stakeholder-Driven Pathways to Decarbonization of Major Infrastructure

Supervisory details

Supervisor: Andreas K. Athienitis
Department: Building, Civil, and Environmental Engineering, Gina Cody School of Engineering and Computer Science 
University: Concordia University, Montreal, Canada 
Start date: Flexible (Fall 2025, Winter 2026, Fall 2026) 
PhD Fellowship: 35K CAD per year for 4 years 

Project overview

The Living Lab at Montreal International Airport aims to reduce emissions and boost electrification while enhancing stakeholder experience. In partnership with key public and private organizations, the project targets five goals: measurement protocols, building optimization, alternative energy design, energy resilience, and financing models. Aligned with the airport’s net-zero 2040 target and the ACCESS 2030 expansion, it will deliver scalable economic, social, and environmental benefits for airports and large buildings across Canada.

Role description

• Develop reduced-order, physics-informed grey box thermal models of airport buildings based on historical sensor data and machine learning for accurate yet computationally efficient simulation of thermal dynamics.
• Design and implement a model-predictive control (MPC) framework that integrates day-ahead weather forecasts and occupancy predictions to optimize building energy use while maintaining occupant comfort and operational constraints.
• Incorporate adaptive feedback loops within the MPC to dynamically update control strategies in response to real-time data deviations, ensuring robust and resilient building operation.
• Conduct rigorous simulation studies using digital twins to validate and refine MPC strategies across diverse operational scenarios before pilot field implementations.
• Analyze, design, and prototype the integration of solar energy solutions including PV, BIPV, BIPV/T, and STPV technologies tailored for different airport expansion components (roofs, façades, canopies).
• Collaborate closely with design consultants and airport authorities to evaluate the feasibility, cost- effectiveness, and operational benefits of integrating PV technologies with building systems and de-icing solutions for winter efficiency.

Requirements

• Master’s degree in Engineering, Energy Systems, Mechanical Engineering, Electrical Engineering, Building Science, or related areas.
• Strong background in building energy modeling, thermal dynamics, and reduced-order model development using grey box or RC network approaches.
• Experience with model-predictive control (MPC) and advanced control optimization techniques for building systems.
• Proficiency in machine learning/statistical methods for model calibration and prediction refinement using sensor and environmental data.
• Skills in digital twin simulation and validation of control strategies under varying operational scenarios.
• Knowledge of solar photovoltaic technologies, including BIPV, BIPV/T, and semi-transparent PV systems, and their integration into building envelopes and infrastructure.
• Ability to collaborate with multidisciplinary teams including design consultants, facility managers, and stakeholders to ensure practical and scalable renewable energy and control solutions.

Questions/contact

For all questions, please contact Alisa Makusheva at alisa.makusheva@concordia.ca.