Date of Completion
Smart Ocean Energy, MPET, MLCT, Wave Energy Converter, Direct Drive Linear Generator, Power Electronics Converter, energy encryption, underwater wireless power transfer
Field of Study
Doctor of Philosophy
Ocean energy offers the highest energy density when compared to other renewable energy resources, and its energy potentials is enormous. As ocean energy converter technology continues to advance, vigorous testing methodology, new design modeling, and assessments of the device performances under different wave conditions become critically important. This work presents the development of a new type of wave energy converter, Smart-WEC, from concept to prototype stage. It utilizes a direct drive linear generator to extract energy from the motion of ocean waves. An integrated dynamic model of Smart-WEC is developed to evaluate its dynamic behavior. Furthermore, Smart-WEC has the capability of making connections with underwater ocean technologies, such as autonomous underwater vehicles and ocean sensors, through a novel underwater wireless power transfer technology. In an effort to assure the energy resilience and maximum power absorption and power transferred, this dissertation addresses the limitations of conventional ocean energy converter technologies to allow a more robust, smart and reliable system. New control methods are explored and implemented: (1) a novel maximum power efficiency tracking (MPET) control that uses k-nearest neighbors to estimate the system's coupling coefficient and tracks the peak efficiency (>85%) through an adaptive converter control; (2) a maximum life cycle tracking control that minimizes the torques stress on tidal shaft and therefore maximizes the energy absorbed by tracking the power-speed curves; and (3) a model predictive control that calculates the power electronic converter voltage needed to force the measured current to its reference value, thereby maximizing power generated by Smart-WEC.
Orekan, Taofeek A., "Modeling, Design and Analysis of Smart Ocean Energy Systems" (2018). Doctoral Dissertations. 1719.
Available for download on Monday, March 28, 2022