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Investigating the electric power generated by wave energy converters (WECs) has attracted increasing attention along with the developments of wave energy converting technologies in recent years. Electric power estimation currently depends on wave-to-wire model-based numerical analysis and experimental studies of scale-down prototypes. However, traditional numerical simulations are time-consuming and expensive for power orediction of a full-scale WECs operated in real sea. More importantly, they cannot accurately predict WECs' power performance in real time, thereby cannot be used for prediction-based real-time control. To address those problems, four machine learning techniques are employed as an alternative to traditional, complex physical modelling processes to evaluate and predict the generated electric power, based on historical experimental data of a two-body hinge-barge WEC. Comparative results of a Backpropagation (BP) Neural Network algorithm, a Long Short-Term Memory (LSTM) algorithm, a Support Vector Machine (SVM) algorithm and a Radial Basis Neural Network (RBFF) algorithm indicate that machine-learning-based approaches can accurately predict the electric performance of this complex multi-degree-of-freedom WEC, where the coefficient of determination (R 2) of the BP Neural Network on the test dataset is up to 0.9987. • Four machine learning techniques are employed to evaluate and predict the electric power. • The machine learning techniques can be used to predict WECs' power performance under new sea state. • The coefficient of determination (R2) of the BP Neural Network is up to 0.9987. [ABSTRACT FROM AUTHOR]

Wave energy is a practical option for the sustainable powering of the drifting buoy beyond solar energy. However, efficient harvesting of wave energy from a complex and dynamic ocean environment for a drifting buoy is significantly challenging, since the buoy's global location and orientation are always in spatiotemporal variation. Herein, we propose a novel multi-DOF wave energy harvesting mechanism that integrates three sets of frequency-tunable harvesting systems into an enclosed drifting buoy, which can greatly enhance the energy harvesting ability of a long-term working drifting buoy that encounters direction-varying and frequency-varying waves. A time-averaged electric power up to 9.18 mW was achieved by a prototype that has a diameter of 45 cm, which is 32.76 % higher than the single-DOF case in sea trials. Additionally, laboratory dry test results show that the prototype provided a power up to 288.76 mW in one direction. This work provides an effective strategy for sustainably generating electricity in the offshore environment for drifting buoys. • A built-in multi-DOF wave energy harvester for a drifting buoy was presented. • Two different-sized prototypes were designed, assembled and tested in the open sea. • A time-averaged electric power of up to 9.18 mW was achieved in real sea tests. • The prototype generated a power of up to 288.76 mW in one direction in laboratory dry test. [ABSTRACT FROM AUTHOR]

Unmanned surface vehicles (USVs) have been widely used in various fields credited for their high flexibility and excellent manoeuvrability. However, the limited onboard electricity of USVs restricts their applications in long-term working tasks. A promising option to address that problem is employing a wave-powered USV, where a wave energy converter is integrated into the USV. For a wave-powered USV, it is challenging to achieve a precise estimation of its power generation under complex marine environments. Although there are physics-based models of WECs used for the estimation and prediction of power generation of USVs, they cannot achieve satisfactory accuracy in practice because of the linearization and simplification of those mathematical modelling. To fill up this gap, this paper proposes a data-driven modelling method utilizing feature engineering and ensemble learning to estimate the mean power generation of a wave-powered USV, relying on time-serial measurements obtained from real physical wave-flume experiments under regular waves. Results show that the estimation achieves promising performance, where the minimum RMSEs are 3.359 mW and 6.148 mW for a harvester-to-wire model and a wave-to-wire model, respectively. Additionally, the proposed method shows great potential for real-sea applications, such as online power prediction and control. • A data-driven method for power estimation of a wave-powered USV is proposed. • The robustness of the proposed method is verified with the presence of noise. • The proposed method possesses practical significance, such as data-driven control. [ABSTRACT FROM AUTHOR]

The multi-body hinge-barge wave energy converter has the advantages of high capture width ratio and wide bandwidth of wave-excited response, which is the current hotspot of studies on wave energy converters. However, to correctly and throughfully analyse its overall efficiency, hydrodynamics, mechanical dynamics and electrical dynamics, a fully coupled wave-to-wire approach by numerical analysis and physical validation is required, which is not concerned by current studies. The work conducted in this study improves the overall wave-to-wire efficiency by optimising the mooring system, the structure and geometry of the primary capture system, and the external electric load. Results show that an optimised prototype achieves a wave-to-wire efficiency up to 25 % in flume experiments, where a significant improvement of 53 % is contributed by employing a damping plate to the right barge. Numerical results indicate that a wave-to-wire efficiency of up to 53 % is obtained by further optimisation of the damping plate. • A wave-to-wire model is developed for a hinge-barge wave energy converter, verified by flume experiments. • Adding a damping plate to the right barge can significantly improve power generation. • High wave-to-wire efficiency of 25.02% is experimentally achieved by a prototype. • High wave-to-wire efficiency of 53% is numerically achieved by optimisation. [ABSTRACT FROM AUTHOR]

Wave energy converters are devices that capture the energy carried by ocean waves and convert it into electricity, and their performance is significantly influenced by the geometric shapes of harvesters and the control strategies of power take-off systems. This paper presents a hybrid methodology to improve conversion efficiency in realistic sea states measured from an intended deployment site, taking into account the full coupling of ocean waves, geometric shapes of wave energy harvesters, and control strategies of power take-off systems. The proposed hybrid approach employs a control-strategy-informed optimization routine to select optimal/suboptimal geometries at the design stage, then employs different control strategies for the power take-off system at the operation stage. In numerical case studies, the proposed hybrid methodology is applied to a direct-driven point-absorber type wave energy converter, where its geometric shape is optimized, informing an optimal linear passive control strategy at the design phase. Simulation results indicate that the concave shape has the best energy harvesting performance. A high capture width ratio of 428% is achieved for the found optimum concave shape that employs an optimal linear active control strategy, in a sea state with a significant wave height of 1.6 m and an average period of 5.5 s. • Asymmetric and axisymmetric arbitrary geometries are optimized. • Optimum geometry has a concave shape. • Motion constraints are considered in control strategies. • A high capture width ratio of 428% is achieved. [ABSTRACT FROM AUTHOR]

This paper performs an investigation of power performance and techno-economic performance of wave power farms in realistic wave climates, where hydrodynamic interaction and influence of control strategies employed by power take-off systems are fully considered in mathematical modeling and numerical analysis. This is of great significance for a commercial wave power farm operated in a specific sea site over a long time of years, as wave energy converters will encounter a wide range of sea states, which requires that associated power take-off systems of individual units must be controlled accordingly to maximize the converted energy and to reduce the levelized cost of energy (LCOE). To that end, a fully-coupled numerical model, where the power take-off systems of wave energy converters are coordinately controlled/tuned for each sea state by employing an optimal linear passive control strategy and an optimal active control strategy, respectively. Numerical results show that power performance and LCOE of wave power farms vary over wave climates, and machinery constraints of power take-off force must be considered. Globally coordinated control of wave power farms by employing a constrained optimal linear active control strategy yields a LCOE of 0. 17 − 0. 54 $/kWh and increases the annual energy generation at least three times in specific wave climates of China, United States, Australia and Ireland. • Full hydrodynamic interaction of individual wave energy converters is considered. • Energy generation of wave power farms in realistic wave climates is maximized. • Individual wave energy converters are coordinately controlled. • Machinery constraints of power take-off systems are considered. [ABSTRACT FROM AUTHOR]

Lacking a long-term power supply restricts the endurance of unmanned surface vehicles (USVs) and their application in remote sea areas. To address that ptoblem, a reliable solution based on the utilisation of wave energy is proposed in this study, where a wave-excited energy harvester is integrated into the USV. A fully coupled mathematical model is established to describe the dynamics and the electricity generation performance of the integrated system, considering the coupling of the mooring system. Numerical results given by this mathematical model are validated by physical experiments. The influence of the external load, the wave height, the wave period, the pendulum length, the pendulum mass and the mooring system on the system's performance are investigated, respectively. Experimental results of two small-scale prototypes, performed in a wave flume, show that the time-averaged generated electrical power is up to 324.89 mW when the wave height is 9.00 cm and the wave period is 1.72 s , where the corresponding wave-to-wire efficiency is 9.72%. Results indicate that the pendulum length, the pendulum mass, and the configuration of the mooring system significantly influence the resonant period and bandwidth. • A new wave-powered USV based on an inertial pendulum is proposed. • The proposed wave energy harvester has the capability to tune natural frequency. • A time-averaged electric power of 324.89 mW is achieved under a flume wave height of 9 cm. • The mooring system has a significant effect on the bandwidth of the USV. [ABSTRACT FROM AUTHOR]

Evaluating the hydrodynamic response, the electric power generation and the wave-to-wire efficiency of scale-down prototypes are critically crucial for developing wave energy converters (WECs). Experimental evaluation through dry and wet tests are commonly employed approaches, besides the numerical analysis. However, the current study heavily relies on expensive test platforms and lacks physical verification of control strategies. This study aims to comprehensively evaluate a scale-down oscillating-body-type WEC through newly developed cost-effectively experimental techniques and test rigs, where the influence of the electric load and the implementation of a control strategy are investigated. The newly-designed dry test rig provides a low-cost and generic approach to evaluate the mechano-electric conversion performance of the power take-off system, and an advanced real-time measurement and control system is assembled and employed to test the wave-excited performance of a WEC through flume experiments. More importantly, this real-time control system is used to physically implement a well-established control strategy under regular and irregular waves, to approach the required stable output power. • Propose a low-cost test rig to assess the mechano-electric conversion performance. • The system-wide performance is efficiently obtained by a high-integrated DAQ system. • The real-time control strategy implementation example of look-up table is shown. [ABSTRACT FROM AUTHOR]