Wave energy has great potential in energy harvesting, but due to its high system cost per electricity production, it is still in the pre-commercialization stage for grid connection.

A wave energy converter (WEC) system that harvests energy through wave motion consists of a wave energy converter and a power take-off (PTO). A wave energy converter, usually a floating buoy, absorbs the hydrodynamic motion from wave and generates a mechanical oscillation. A power take-off (PTO) with mechanical transmission, which harvests the electrical energy through the mechanical energy, usually includes a transmission that converts linear motions from the buoy to rotational motions, an electromagnetic generator that produces electricity from a rotational shaft, and a power electronics converter that converts the ac electric power from the generator and charges the output dc battery or the ac grid.

The models of the WEC system are usually oversimplified in a multi-physics study. A PTO model as an ideal actuator with 100 % efficiency will show a different frequency response than the real tested results and can make the controller design invalid. A conventional regular-wave circuit model shows discrepancies in power and force prediction in time-domain under irregular wave conditions. A model that can bring the multiple fields together, and provides an accurate prediction from irregular wave dynamics and non-ideal PTO mechanism is needed.

A methodology that converts mechanical transmission equations into a circuit model is created. The equivalent circuits of mechanical components such as one-way clutches, gears, a ball screw, mechanical couplings, and generator are derived respectively to describe the dry frictions, viscous damping, and mechanical compliances in these components. The non-ideal efficiency and force of the PTO are predicted in electrical simulations by integrating these sub-circuit models. The circuit model is simplified, and its parameters are categorized as dc and ac unknowns. Using PTO with a mechanical-motion-rectifier (MMR) gearbox as an example, the dc and ac tests on the PTO are performed sequentially to extract two sets of parameters through linear regression or nonlinear curve fitting. The simulated efficiencies of 30 – 80% match well with experimental results. The model is validated through its prediction capability over 25 test conditions on input forces, output voltages, and efficiencies, with correlation coefficients R2 value of 0.9, 0.98, and 0.981, respectively.

An equivalent circuit model of fluid-body dynamics for irregular waves, applicable to real ocean conditions with frequency-dependent radiation damping, is developed. Different from PTO modeling, the time-invariant circuit is created from a fourth-order RLC equivalent circuit through transfer function approximation in the frequency domain and Brune network. The circuit-based wave energy converter (WEC) model is verified by comparing the results with the predictions of a detailed model under irregular wave conditions in the time and frequency domains based on a point absorber type of WEC with a power take-off (PTO). The results show that the developed model gives an accurate dynamic prediction for a WEC under both regular and irregular conditions. Along with the PTO model, the circuit-based W2W model is completed for control and design optimization of the WEC system.

Wave energy converter systems have faced various challenges such as reciprocal wave motion, high peak-to-average power ratio, and potential wave height from hundred-year storm conditions. These could lead to an overdesigned power take-off (PTO) of the system and significantly reduce the lifetime of the power electronics converter.

The power ratio between the peak and the average power of the wave power converter is around 10 – 20 times. Power optimization is necessary to reduce the over design ratio of the power electronics converter. The design guideline that optimizes the power ratings for the power converter and the generator is introduced. The methodology is developed from the W2W circuit model taking the losses of the power converter and the generator into consideration. By optimizing the power limiting and field-weakening controls, the ratio from the average output power to the rated power of the power converter is reduced to 2.4 in the maximum wave condition, and 15 in the annual wave profile.

A maximum energy control algorithm on the power electronics in wave energy application is developed to increase the total energy produced from the power converter in a wave energy converter (WEC) system. A 4-D damping and power leveling maps for maximum energy are built for the algorithm. The maps are based on the irregular W2W circuit model and reliability analysis on the IGBT module. From the yearly wave mission profile, the strategy is proved to increase energy by 16 times or increase the lifetime from 3 to 18 years in exchange for 6 % of average output power than the conventional maximum power algorithm.

In conclusion, this work provides a new circuit-based perspective for co-designing the multi-disciplinary WEC system. The methodologies of circuit modeling can benefit the co-design process of other mechatronic power systems, such as electric vehicle or renewable energy system. The newly invented mechanical device – the mechanical motion rectifier, is understood thouroughly via the non-ideal electrical model.

The commercialization of wave energy converter is driven forward through the reduction of the levelized cost of electricity (LCoE) which is made possible by increasing the energy production and optimizing the cost per output power of the generation and power conditioning stages.