- Wave energy is a potentially important renewable clean source of energy that can help solve the energy demand throughout the world. A great deal of research has been conducted in the last few decades and it is now reaching the point of full implementation. In order to compete with other energy sources, we must first demonstrate that it is commercially viable. So far, researchers and developers have been able to demonstrate proof of concept utilizing a small number of wave energy converters (WECs) deployed in the open ocean or on shore. However, to make this source of energy commercially viable, the deployment of a large number of WECs is necessary. Regardless of the type of WEC used, the deployment of these devices has to be carefully thought out, since the direction of the wave fronts varies throughout the year and once the WECs are installed, they will remain fixed in those locations and they will experience only relatively small displacements on the ocean surface.
When a group of WECs is deployed on the ocean surface, their motion resulting from the excitation force due to the arrival of a wave front will affect other WECs in the vicinity. Furthermore, depending on the angle of arrival of the wave front, the interaction between WECs will vary and the energy conversion capability will be affected. This interaction has been coined as the q factor by researchers in the field.
In this thesis, we consider the deployment of an oscillating water column (OWC) WECs developed by researchers from the Polytechnic of Lisbon in Portugal and their Spanish collaborators, namely, the MarmokA5. Our deployment strategy has as its main objective the maximization of average power of the array of WECs. When we consider an array configuration, namely, its geometric configuration, distance between WECs, angle of arrival of the wave front, and sea state, we implement a mathematical model of the array produced by ANSYS AQWA in Simulink to compute the average power generated by the array. We evaluate array power generation performance by varying the form of its configuration and the number of WECs in it. The results of our strategy suggest that they can be incorporated into more formal mathematical objective function to optimize WEC array generated power.