Profile
| Keywords: | Concentrated Solar Thermal, Molten Salts, Heat Decarbonization, Industrial Heat |
Dr. Manzoor leads the Renewable Thermal Lab at the University of Alberta, focusing on the decarbonization of industrial heat and power. With over 5 years of direct experience, he has been actively involved in investigating and developing Concentrated Solar Thermal (CST) systems. His contributions extend to designing the largest experimental solar simulator facility in Canada. He has trained over seven HQP in the field of renewable thermal energy. His trainees now study in world-renowned institutions like Oxford and ETH Zurich. Dr. Manzoor also possesses relevant industrial experience. As an Energy Storage Specialist at Hatch, he assessed the Technology Readiness Level (TRL) for a leading U.S.-based thermal energy storage start-up. He identified fatal design flaws and risks that needed to be retired to achieve the next TRL. He performed technology pre-screening for a leading mining company in Chile looking to decarbonize its processes by deploying thermal energy storage systems. Dr. Manzoor is knowledgeable about traditional energy storage technologies and the commercial aspects of energy storage systems. He aided Canadian government-owned utilities in the procurement of battery energy storage systems for remote sites. FES Funded ProjectsOutputs
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| Optimizing the performance of liquid-based medium-temperature volumetric solar thermal receivers using genetic algorithmsLiquid-based volumetric solar thermal receivers are a promising alternative to the traditional tubular receivers. By absorbing solar energy directly in a semi-transparent medium, volumetric receivers achieve higher capture efficiency and more uniform temperatures, overcoming the low capture efficiency issues faced by tubular receivers at high temperatures. However, accurately predicting the thermofluid behavior of volumetric receivers under various operating conditions is challenging due to the complex interactions between radiation, convection, conduction, and volumetric heating. A mechanistic model validated under a 6.5 kW solar simulator was developed, and demonstrated short-term (up to 7min) accuracy of predicting such behavior, yet the optimization of key parameters which can increase system efficiency and avoid the development of hot spots inside the receiver remains unexplored.
This study addresses this parameter exploration and optimization using an evolutionary algorithm, specifically a genetic algorithm (GA), focusing on five critical parameters— attenuation coefficient, solar flux, receiver depth, top surface emissivity, and heating time. By using MATLAB’s multiobjective genetic algorithm solver, we identified multiple solutions representing trade-offs between efficiency and temperature uniformity inside the receiver. This evolutionary computation method constructs the Pareto front, a set of solutions that represent the best trade-offs between competing objectives, by iteratively selecting, recombining, and mutating solutions while maintaining diversity among solutions. The ability to produce multiple optimal solutions is highly valuable, as it provides a range of possible outcomes that can be adjusted to different operational conditions, ultimately improving the performance of volumetric receiver systems.T12-Q04 University of Alberta | Publication | 2025-09-01 | | | Techno-Economic Analysis for the Deployment of Electric Thermal Energy Storage Systems Using Binary Chloride Salts in Edmonton, Alberta.T12-Q04 University of Alberta | Activity | 2025-05-28 | | | Preliminary Design of a Heat Extraction Mechanism for Volumetrically Absorbing Modular Concentrated Solar Thermal SystemsT12-Q04 University of Alberta | Activity | 2025-09-25 | Abdul Saboor, Mariem Sahbani, "Adam Jaikaran ", Julian Baudouin, Guylian Pelonde, Gaurav Yougal Kishore, Manzoor, T. |
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