Vatchavayi. Sagari Raju2019-08-202019-08-202019-06https://hdl.handle.net/11299/206185University of Minnesota M.S. thesis. June 2019. Major: Computer Science. Advisor: Andrew Michael Sutton. 1 computer file (PDF); vii, 68 pages.Ocean wave energy is a vastly unexploited source of renewable energy. The poten tial generated by the movement of waves can be captured by wave energy converters (such as buoys) and can be used to drive a turbine to generate electrical energy. However, the electrical output from a single buoy might not be enough to satisfy the requirements of large-scale applications. As a result, an array of many buoys is used for this purpose. Two major factors affecting the production of output energy in this array are location (x-y) and Power Take Off parameters, spring (kPTO in N/m/s) and damper (dPTO in N/m) coefficient. In the first part of our research, we visualize the impact of our proposed optimization by employing a variety of grid search mech anisms on an array of two fully-submerged three-tethered converters. The results of these grid searches show that the power output of our array increases significantly for a certain x-y-kPTO-dPTO configuration of each converter. In the second part of our research, we attempt to minimize negative interactions between the converters with the use of a derivative-free continuous optimization method (CMA-ES) to find the optimal placement. Furthermore, the best PTO parameter configuration is obtained by executing a Nelder-Mead search algorithm within the parameter bounds. Based on the order in which these algorithms are deployed, we test out three algorithmic approaches, namely Alternating, Bi-level and Random order optimization. On com paring the three approaches, it was observed that Bi-level performed the best with about 9 percent increase in total output power.enThesis or Dissertation