Energy Efficiency and Sustainability: From Materials Design to System Integration and Control

Energy efficiency and improvements in sustainable practices are major factors towards mitigating the depletion of fossil fuel reserves and the environmental impact of their consumption. Innovative approaches to unconventional resource recovery improvement and the integration of renewable resources into distributed production of power are key enablers towards achieving these goals. 

The first part of the talk will focus on the utilization of nanoparticles for enhanced oil recovery (EOR). The recent emergence of inexpensive surface-treated nanoparticles has provided a promising and still largely unexplored toolbox for oil and gas recovery. Despite great efforts, the fundamental understanding of flow behavior and design of efficient nanoparticles for this application remains a scientific challenge. The classical rheological description of complex fluids does not capture behavior that mimics the oil extraction process, which depends on the processing history, nature of the fluid/fluid movement, and the geological formation, and therefore vary in space and time. Recent results aiming at fundamental understanding how particles behave under different processing conditions and different confinements will be presented. This research builds on our recently developed experimental tools which allows imaging of sample morphology in 4-D under well-defined macroscopic flow fields, and has a significant promise to reveal a mechanistic understanding of these systems at an unprecedented level of detail.

The second part of the talk will focus on the emerging theme of distributed power production from renewable resources. The motivation lies in the promise of developing an efficient and robust energy management strategy that can address weather intermittency, handle economic objectives and operational limits in a systematic manner. A parametric programming based approach for energy management in microgrids will be described. The formulation leads to significant improvements in uncertainty handling, solution quality and computational ease; by removing dependency of the solution on meteorological forecasts and avoiding the multiple computational cycles of the traditional online optimization techniques. Recent results along with opportunities for real-time implementation will be highlighted.

Speaker: Milana Trifkovic, Univ. of Calgary