PhD Oral Exam - Masoud Rezaei, Civil Engineering

When studying for a doctoral degree (PhD), candidates submit a thesis that provides a critical review of the current state of knowledge of the thesis subject as well as the student’s own contributions to the subject. The distinguishing criterion of doctoral graduate research is a significant and original contribution to knowledge.

Once accepted, the candidate presents the thesis orally. This oral exam is open to the public.

Abstract

Despite the ever-increasing use of renewables for societies’ energy supply and considering the long history of using some of them such as biomass for energy generation purposes, new challenges associated with their utilization emerge. 

For biomass-powered energy systems, issues such as seasonality of biomasses, supply chain problems, heat content of biomass resources, weather pollution, environmental contamination, and energy conversion limitations put the availability and affordability of such systems under question. The optimization of the energy systems considering their reliability, availability, and maintainability parameters and constraints could considerably affect the system design, and operation. 

The research proposes optimization modeling based on the methodologies derived for hybrid energy systems (generating heat, electricity and then hydrogen), considering reliability, maintainability, and availability parameters that deliver the optimal values for cost, reliable performance parameters for operation, and available energy systems. 

Such modeling is capable of being extended to be used for smart energy systems that are further hybridized by integrating other energy or product generation modules such as geothermal, solar, wind, or hydrogen-generating modules. 

This modeling by using cost and pollution correlation function of systems performance parameters (modules rated capacities, use times, etc.) could be adapted to a wide range of heat and electricity energy demands (building, complex of buildings, or district heating networks) for different applications ranging from populated areas to remote off-grid communities such as northern Québec, Canada. 

This modeling is flexible enough to adopt various other methods for optimization and reliability, maintainability, and availability analysis, such as Multiple Criteria Decision-Making (MCDM) techniques, to assist in achieving the most economically exploitable energy with the least pollution from various scenarios. 

In this methodology, nonlinear objective functions with several criteria for decision-making, subjected to reliability parameter constraints, are used to minimize the energy generation cost and pollution and are examined for single buildings or DHS applications. 

In this research, hybridization of the biomass-fuelled combined heat and power (CHP) systems is modeled by coupling such systems with geothermal and hydrogen modules. Configuration of such models was carried out by considering the particularities such as modeling the geothermal module surface and subsurface parts, hydrogen generators, and thermal energy storage components.

Sensitivity analysis of such methodologies and models is performed by scenarioizing and via scenarios considering biomass chemical compositions, wood pellets distance from consumption areas, and reliability, maintainability, and availability parameters for a single or complex of buildings. Techniques such as MCDM techniques like TOPSIS are employed to screen the optimal scenarios in multi objective optimization modeling.