Motion in the Ocean – Revolutionizing Marine Hydrokinetic Energy Harvesting Through the Optimal Periodic Motion Control of Underwater Kites
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Abstract: Tidal and ocean current resources in the United States have been collectively estimated to contain over 250 TWh/year of extractable hydrokinetic energy. This equates to powering tens of millions of homes, in addition to providing the opportunity to power so–called “blue economy” off–grid applications, such as supplying power to ocean observing platforms and autonomous underwater vehicles. The extraction of marine hydrokinetic energy in a 1 m/s flow speed through a fixed turbine requires approximately the same geometric sizing per unit of power as a wind turbine operating in a 10 m/s wind speed. However, complications associated with undersea installation result in dramatically higher costs than comparably scaled wind energy counterparts. This talk will examine the design and control of underwater kites as a game–changing solution for extracting ocean current and tidal resources. Compared with a fixed turbine design, an underwater kite eliminates massive rotating underwater machinery and in fact reduces the size and mass per unit power of the underwater system by more than an order of magnitude. The achievement of these levels of performance is dependent, however, on addressing two periodic optimal motion control challenges, which must be performed concurrently and robustly, within a flow environment that is varying in both space and time. First, the kite must follow efficient periodic flight paths (typically figure–8 or elliptical paths), under efficient periodic attitude profiles, to achieve the requisite high–speed operation for maximizing power output. Second, the kite must employ a periodic power take–off (PTO) system that harvests energy either through on–board rotors whose operating parameters vary over the course of each repeated flight path, or through cyclic spooling motion. This seminar will illustrate how techniques from iterative learning control and continuous–time optimal control theory have been adapted to tackle these challenges. Furthermore, the seminar will highlight ongoing experimental efforts to validate dynamic models and control strategies for a prototype underwater kite design. These efforts have so far included (i) early 1/100–scale water channel–based validation, (ii) tow testing in a controlled pool environment, and (iii) recent long–duration open–water demonstrations in Lake Norman, NC.
Bio: Chris Vermillion received his Ph.D. in Electrical Engineering from the University of Michigan in 2009 and received his undergraduate degrees in Aerospace and Mechanical Engineering from the University of Michigan in 2004. Immediately following his Ph.D. work, Dr. Vermillion worked on advanced automotive powertrain control, focusing on constrained optimal control approaches that simultaneously addressed the competing performance interests of fuel economy, emissions, drivability, and torque delivery. Subsequently he served as a Lead Engineer for Altaeros Energies and managed all of the dynamic modeling, control system design, software development, and embedded hardware development for Altaeros’ lighter–than–air wind energy system. Dr. Vermillion has participated in the full–scale fight testing of two of Altaeros’ designs. Dr. Vermillion is currently an Associate Professor at NC State, where his research focuses on the dynamic characterization, design optimization, and optimal control of airborne wind energy systems, marine hydrokinetic energy systems, and energy–efficient connected and autonomous vehicles. Dr. Vermillion was the recipient of the National Science Foundation’s CAREER Award in 2015, the UNC–Charlotte Maxheim Research Fellowship in 2016, the UNC–Charlotte College of Engineering Excellence in Teaching Award in 2017, and the NC State Mechanical and Aerospace Engineering Research Award in 2021.
***Event will take place in hybrid format. The location for in-person attendance will be room 1311 EECS. Attendance will also be possible via Zoom. Zoom link and password will be distributed to the Controls Group e-mail list-serv.
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