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Abstract A plate‐wave energy converter (pWEC) moored in front of a floating stationary breakwater is considered. The pWEC is composed of a submerged flexible plate with piezoelectric layers bonded to both faces of it. Hence the elastic motion of the plate excited by water waves can be transformed into useful electricity due to the piezoelectric effect. To evaluate the performance of the breakwater‐attached pWEC in terms of wave power absorption and wave attenuation, a hydroelastic model based on linear potential flow theory and the eigenfunction matching method is developed with the electromechanical and the hydrodynamic problems of the pWEC coupled together. The pWEC can be either simply supported or clamped at the edge. A multi‐parameter analysis is carried out with the employment of the present model. Effects of the width, submergence and edge types of the plate, together with the scales of the breakwater, including its width and draft, on wave power absorption and wave attenuation, are examined. As the pWEC moves towards a deeper position, the main peaks of the frequency response of the wave power absorption efficiency become lower and narrower. In contrast, its effect on wave attenuation is limited.

Abstract In this study, the design requirements for a regional wave energy converter are identified from the analysis of 10 years of spectral data provided by nine buoys located across the Caribbean. It indicated that the average significant wave height and wave period in the Caribbean is 1.62 m and 5.91 s, respectively, while the average total theoretical power capable of being absorbed from a wave energy converter is 7.4 kilowatts per meter of surface waves. Devices should be designed to withstand a significant wave height of 19.0 ± 2.8 meters (95% confidence) for a 1 in 100 year return wave. This was determined by performing various extreme wave analyses. Additionally, a design life of 30 years for a device would have a probability of exceedance regarding this return wave as 26%. Using two‐dimensional wave spectra analysis for the resource study, the overall spectral width, directionality coefficient and direction of the maximum directionally resolved wave power for the region are determined to be 0.172, 0.74 and 42°, respectively. It is expected that the combination of these information would improve the viability of a wave energy industry in the Caribbean and advance technological development.

Abstract This review studies some of the existing ideas which create a fundamentally new direction for wave energy converter (WEC) development, obtaining energy from the elliptical motion of particles in water waves using a rotor. The review focuses on three main aspects of rotor‐based WECs: experimental study of the developed prototypes, derivation and development of the mathematical models, and control effectors and philosophies for the proposed devices. The range of developed small scale prototypes and their experimental studies are presented. The shortcomings of the current mathematical and hydrodynamic models are identified, while an overview of the proposed and new possible control effectors and strategies is conducted. This allows us to see the state of the development of the different concepts and problems to be solved in bringing wave energy rotors to operational reality.

Abstract Based on the concept of cost sharing, an oscillating buoy wave energy converter‐ floating breakwater integrated system is proposed, in which the surge or pitch motion of the front‐pontoon equipped with Power Take‐off (PTO) system is allowed. In this study, the methods of eigenfunction matching and variables separation are applied to establish a theoretical model on hydrodynamic performance of the proposed integrated system. Under the condition of optimal PTO damping, the effects of the front‐pontoon width, draft and pontoon spacing on the capture width ratio, reflection coefficient and transmission coefficient are investigated, respectively. It is found that the integrated system with surging front‐pontoon performs better on the wave energy conversion than that with pitching one, especially in the high frequency region. The peaks of capture width ratio Cw are associated with the gap resonance and the increase of front‐pontoon motion induced by the ‘hydrodynamic constructive effect’.

Abstract Recent studies have focused on optimising wave energy converter (WEC) designs, maximising their power performance and techno‐economic feasibility. Reliability has yet to be fully considered in these formulations, despite its impact on cost and performance. In this study, this gap is addressed by developing a reliability‐based design optimisation framework for WEC hull geometries to explore the trade‐off between power performance and power take‐off (PTO) system damage equivalent loading (DEL). Optimised hull geometries for two sites are considered (from the centre of the North Sea and off the west coast of Norway), and two directions of motions (heave and surge). Results indicate that site characteristics affect the potential power production and DEL for an optimal WEC design. These are also affected by the direction of motion for power extraction, which also significantly changes optimal hull shape characteristics. Optimal surging WEC designs have edges facing oncoming wave directions, while heaving WECs have pointed bottoms, both to streamline movement. Larger, more convex WECs result in greater power production and DEL, while smaller, more concave WECs result in lesser power production and DEL. These findings underline the importance of considering WEC hull geometry in early design processes to optimise cost, power production, and reliability.

Abstract Climate change “fuelled” by anthropogenic causes has been identified as the greatest threat faced by societies. In this respect, the roadmap to a “greener” generation mix certainly includes a greater heterogeneity in terms of renewable energy sources. In this regard, one of the leading candidates is ocean wave energy. One of the issues with renewables in general is their unpredictably and variability, as it is crucial to address the subject of wave power forecasting, to facilitate a future market integration. Hence, to tackle this prediction problem, a new approach to short‐term wave power forecasting is proposed, based on deep learning capabilities. These highly popular networks were traditionally developed to deal with images (2D data), so the authors discuss all the necessary implementation and design details to employ these networks with 1D input data, to solve a regression‐based problem. These case‐studies include wave data from three different locations. The proposed approach was tested across all seasons of the year, revealing the suitability to extract the relevant input data dependencies from the time‐series. As such, especially for horizons up to 6 h, the proposed approach outperforms other conventional methods.

Abstract In order to integrate wave farms into the grid, the power from wave energy converters (WEC) must be forecasted. This study presents a novel data‐driven modelling (DDM) method to predict very short‐term (15 min–4 h) and short‐term (0–72 h) power generation from a WEC. The model is tested using data from an oscillating body converter. Several other methods are tested as well. These include support vector machines (SVM), neural networks (NN), and recurrent neural networks (RNN). Of these, the best is the long‐short‐term memory (LSTM) network, which is trained and updated on observed values. The experiments demonstrate both the SVM and NN forecast well. However, the proposed deep learning models predict them more accurately. The models work well over short horizons. At horizons longer than three days, accuracy deteriorates, and the models cannot fit the data well.

Abstract The application of the theory of extreme values has been growing due to increasing interest in extreme natural events. Many articles on extreme values in data modelling consider unimodal data. This work introduces an appropriate regression for extreme values to detect the presence of bimodality by means of systematic components of two parameters of the odd log‐logistic log‐normal distribution. The global influence is addressed to verify the model robustness and to find possible influential points. Quantile residuals are proposed to detect distribution deficiencies and outliers in the new regression. A real dataset from the electricity generation area is analysed, namely the Santo Antônio Hydroelectric Plant in the state of Rondônia (Brazil), to illustrate the potential of the new regression. The main results indicate that the proposed regression can identify changes in the means and variability of the power generation between extreme events, that is, between the months of June and December.

Abstract A methodology to automate the sizing of a wave energy converter (WEC) is presented. The preliminary design of WEC geometry is addressed as a mathematical program by means of a meta‐heuristic optimisation, which includes as key aspects the use of a multi‐objective differential evolutionary (DE) algorithm and the implementation of a stochastic hydrodynamic model of the WEC. In this methodology, the WEC concept, the control strategy, the power take‐off characteristics and the location have been taken into consideration due to their strong influence on the WEC design. As a case example, a real project has been selected, and the methodology has been applied to two test locations. Stochastic models are used to handle irregular sea states and to obtain statistical information while reducing the calculation effort when compared to time‐domain models. The output derived from the proposed methodology is a set of feasible solutions so‐called Pareto frontier. These solutions can be used as inputs for a detailed design process. Data from real projects could be used to further develop the sizing methodology by improving the algorithm convergence, refining the requirements, or including new restrictions.