Investigation on the extreme peak mooring force distribution of a point absorber wave energy converter with and without a survivability control system
Keywords:Wave energy converter, Deep neural network, Control system, Design load, Long-term extreme response
To determine the optimal design of the wave energy converter (WEC) that can withstand extreme wave
conditions, the short- and long-term extreme responses of the system need to be determined. This paper focuses on the extreme peak force distribution of the mooring force for a 1:30 scaled point absorber WEC. The basis of this analysis is the mooring force response obtained from a WEC-Sim model calibrated by wave tank experimental data. The extreme sea states have been chosen from a
50-year environmental contour. Here, first, the long-term extreme response using the full sea state approach is obtained for three constant damping cases of the power take-off (PTO) system. Then, using a contour approach, the expected value of the extreme peak line (mooring) force distribution is computed for the sea states along an environmental contour. Further, for the most extreme
sea state, the extreme peak line force distribution is also computed where a survivability control system, based on a deep neural network (DNN), changes the PTO damping to minimize the peak mooring force in each zero up-crossing episode of surface elevation. The results show that in the absence of a control system, the zero PTO damping case is a conservative choice in the analysis of the long-term response and the design load. For the most extreme sea state along the environmental contour, the survivability control system slightly reduces the expected value of the extreme peak force distribution when compared with lower constant PTO damping configurations.
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