This paper describes the design and analysis of several buoy geometries that may be applied to a near-shore floating point-absorber wave energy converter. After the characterisation of the device, a numerical model and a simulator in the time domain were developed and the structural performance of the wave energy converter evaluated for three different buoy geometries. The influence of the buoy dimensions, different submerged conditions and position of hydraulic cylinder piston rod, on the structural performance of the wave energy converter is also analysed. The numerical study was conducted using a commercial finite element code. This software needs, among other parameters, the magnitude of the forces acting upon each buoy. A dynamic model was, therefore, developed assuming that the buoy heave motion is excited by the sea waves. The finite element analysis revealed that a load with a higher magnitude than those computed from the simulator was required. It was shown that, even considering the partially submerged condition, the spherical buoy geometry leads to best structural behaviour.

The Archimedes wave swing (AWS) is a a fully- submerged wave energy converter (WEC), that is to say, a device that converts the kinetic energy of sea waves into electricity. A first prototype of the AWS has already been built and tested. This paper presents simulation results of the performance of several control strategies applied to this device, including PID control, reactive control, phase and amplitude control, latching control, feedback linearisation control, internal model control, switching control, and combinations thereof. Linear, white-box nonlinear, and neural network models were employed. Significant (above threefold) increases in yearly energy production were found to be possible with properly designed control strategies.

This paper uses Levy's identification method to build linear, second-order models for the Archimedes Wave Swing (AWS), an off-shore, fully-submerged, point absorber wave energy converter, expected to behave much like a mass-spring-damper system, though with relevant non-linearities. Since very few experimental data is available, data from an accurate non-linear simulator of the AWS was used. One of the identified models yields a satisfactory performance, and can now be used for the development of control strategies for the AWS.