Sequential design optimization with Bayesian approach for cost-competitive levelized cost of energy of a wave energy converter with adaptive resonance

Considering sequence of energy conversion processes for the wave energy conversion, we establish a sequential optimization for a wave energy converter with adaptive resonance to achieve a cost-competitive Levelized Cost Of Energy. As the ocean waves vary in peak frequency and significant height, the adaptive resonance is devised to locate natural frequency at which Capture Width Ratio is maximized for each sea state using the combination of mass relocation and nonlinear interaction with power-take-off dynamics. The sequential optimization comprises submerged volume optimization to maximize the first conversion from annual irregular waves to excitation relative to radiation damping, operational parameters optimization for adaptive resonance to maximize subsequent conversion to mechanical and electrical energy in terms of Capture Width Ratios at individual sea states occurring annually, system scale determination to get the highest Capture Width Ratio occurring at a target frequent sea state so that Annual Energy Production can be maximized for the given dimensions, and minimization of device costs through structural analysis and generator configuration. We perform the sequential optimization for a Surface Riding Wave Energy Converter in a kilowatt scale, which feasibly change pitch natural frequency by relocating mass units with nonlinear interaction with a linear power-take-off dynamics, featuring cost reduction of Levelized Cost Of Energy by an omni-directional submerged volume, linear power-take-off components sealed inside a tube, and minimum singe mooring line in slack condition. The optimized Surface Riding Wave Energy Converter results in annual average power 17.70 kW, Annual Energy Production 148.8 MWh, and the minimum Levelized Cost Of Energy $0.372/kWh. Contrary to $3.59 to $4.36/kWh of available reference models, the significant improvement of Levelized Cost Of Energy is attributed to the sequential optimization that includes those cost reduction features, extract the maximum energy at individual conversion processes, and results in the adaptive resonance at the optimized scale 3:1, producing the highest Capture Width Ratio 46.44 % among the annually occurring sea states, which is over two times performance of the reference model in equivalent floating condition. The performance of the optimized Surface Riding Wave Energy Converter is validated with fully nonlinear particle-based simulation in time series.