Wave Energy Converter Research Articles

Self-powered wireless sensor node enabled by ultra-high-output swinging hybrid generator toward real-time and in-situ marine meteorological observations

With the intensification of global ocean exploration, there is an increasing need for extensive and dispersed wireless sensor networks (WSNs) to meet the requirements of real-time, in-situ, and high-spatial-temporal-density marine meteorological observations. Nevertheless, providing a reliable power source and ensuring the ongoing maintenance of these WSNs pose significant challenges. Here, an innovative self-powered wireless sensor node is developed to address these challenges, featuring an ultra-high-output triboelectric-electromagnetic hybrid generator (T-EHG) with a swinging mechanism. The T-EHG, which combines triboelectric (TENG) and electromagnetic (EMG) generation, assisted by a universal power management system (UPMS), efficiently converts wave energy into a consistent voltage output between 1.5 V to 3.3 V. Additionally, the self-powered WSNs integrated with T-EHG, UPMS circuits, meteorological sensors, and microcontroller units (MCUs) with LoRa wireless transmission functionality are capable of executing data collection and transmission operations every 10 s under simulated wave conditions. These systems can achieve a maximum wireless transmission range of 1.5 km. Notably, a marine meteorological monitoring system utilizes these autonomous sensor nodes, along with base stations, cloud servers, and terminal devices to effectively implement real-time, on-site measurements of temperature, humidity, and air pressure within the monitored zone. This research underscores the substantial practical utility and extensive application prospects of these advanced self-powered WSNs for marine meteorological surveillance.

Failure Consequence Cost Analysis of Wave Energy Converters—Component Failures, Site Impacts, and Maintenance Interval Scenarios

In the early stages of developing wave energy converter (WEC) projects, a quantitative assessment of component failure consequence costs is essential. The WEC types, deployment site features, and accessibility should all be carefully considered. This study introduces an operation and maintenance failure consequence cost (O&M-FC) model, distinct from conventional O&M models. The model is illustrated with case studies at three energetic Atlantic sites, each of which considers two types of generic floating WECs: a 300 kW point absorber (PA) with a hydraulic power-take-off (PTO) and a 1000 kW oscillating water column (OWC) with an air-wells-turbine PTO. This study compares 39 failure modes for PA and 27 for OWC in terms of direct repair costs and indirect lost production costs, examining the impact of location accessibility, capacity factors, and the mean annual energy production. The discussion revolves around the sensitive parameters. Recommendations for failure mitigations are presented, and the impact of planned maintenance (PM) during the operational phase is examined for 20 MW PA and OWC WEC projects. For a given WEC type, the method thoroughly evaluates how the location affects performance metrics. It offers a decision-making tool for determining optimal PM intervals to meet targets such as O&M costs, operating profit, or availability.

A top-mounted, chain-driven, bidirectional point absorber type wave energy convertor

The aims of this paper are to introduce the structure of a point absorber type wave energy convertor (WEC) mounted above sea level, to analyze the motion characteristics and power absorptions of such a WEC and to describe the numerous advantages of installing it in the nearshore. The motion equation is solved by representing the excitation force with the dynamic wave pressure and obtaining an approximate system transfer function. The possibility of the buoy becoming airborne or submerged is considered and the power absorption is increased optimally by reshaping the frequency response using a flywheel. The time, phase and spectral averages of power absorptions are presented for offshore waves, nearshore waves and for concentrated nearshore waves using standard wave spectrums and compared. Approximate gains possible with linear and rectangular arrays are also presented. Considering different phase distributions, it is shown that downgrading WECs based on short term power absorptions is not justifiable. With a buoy of radius 2 m, the power absorption of this kind of a WEC is estimated to be about 114 kW in the deep sea and 117 kW in the nearshore, when the energy flux is about 31 kW/m. By concentrating just 13.6 kW/m nearshore waves, it could be increased to 186 kW. If a 3-element longshore in-line array is placed inside the wave concentrator, the total power absorption could be about 556 kW. A 9-element rectangular array would be capable of absorbing about 1 MW by making use of the remaining energy of the down wave.

Hydroelastic modelling of a deformable wave energy converter including power take-off

Given the advantages of flexible wave energy converters (FlexWECs), such as deformation-led energy harnessing and structural loading compliance, there has been a significant interest in FlexWECs in both academia and industries. To simulate the FlexWEC interaction with ocean surface waves, a 3D computational fluid-structure interaction approach is developed in this study. The fluid and solid governing equations are discretized using finite difference and finite element methods, respectively. An immersed boundary method is used to couple the two independent grid systems. A novel numerical technique is introduced to model the dielectric elastomer generator (DEG) as the power take-off (PTO). The wave energy capture performance is analysed for different PTO configurations and at various wave conditions. Based on the obtained results, the PTO damping coefficient and the relative wavelength range that maximizes the capture width ratio (CWR) are determined. The wavefield results also reveal the presence of wave-height enhancement and attenuation points around a single FlexWEC, providing potential site selection references when deploying multiple FlexWECs in an array.

Computational Fluid Dynamics Simulation on Blade Geometry of Novel Axial FlowTurbine for Wave Energy Extraction

Wave energy converters (WECs) utilizing the Oscillating Water Column (OWC) principle have gained prominence for harnessing kinetic energy from ocean waves. This study explores an innovative approach by transforming the pivoting Denniss–Auld turbine blades into a fixed configuration, offering a simplified alternative. The fixed-blade design emulates the maximum pivot points during the OWC’s exhalation and inhalation phases. Traditional Denniss–Auld turbines rely on complex hub systems to enable controllable blade rotation for performance optimization. This research examines the turbine’s efficiency without mechanical actuation. The simulations were conducted using ANSYS™ CFX 2023 R2 to solve the three-dimensional, incompressible, steady-state Reynolds-Averaged Navier–Stokes (RANS) equations, employing the k-ω SST turbulence model to close the system of equations. A grid convergence study was performed, and the numerical results were validated against available experimental and numerical data. An in-depth analysis of the intricate flow field around the turbine blades was also conducted. The modified Denniss–Auld turbine demonstrated a broad operating range, avoiding stalling at high flow coefficients and exhibiting performance characteristics like an impulse turbine. However, the peak efficiency was 12%, significantly lower than that of conventional Denniss–Auld and impulse turbines. Future research should focus on expanding the design space through parametric studies to enhance turbine efficiency and power output.

Numerical Simulation Method of Hydraulic Power Take-Off of Point-Absorbing Wave Energy Device Based on Simulink

Wave energy has a high energy density and strong predictability, presenting encouraging prospects for development. So far, there are dozens of different wave energy devices (WECs), but the mechanism that ultimately converts wave energy into electrical energy in these devices has always been the focus of research by scholars from various countries. The energy conversion mechanism in wave energy devices is called PTO (power take-off). According to different working principles, PTOs can be classified into the linear motor type, hydraulic type, and mechanical type. Hydraulic PTOs are characterized by their high efficiency, low cost, and simple installation. They are widely used in the energy conversion links of various wave energy devices. However, apart from experimental methods, there is currently almost no concise numerical method to predict and evaluate the power generation performance of hydraulic PTO. Therefore, based on the working principle of hydraulic PTO, this paper proposes a numerical method to simulate the performance of a hydraulic PTO using MATLAB(2018b) Simulink®. Using a point-absorption wave energy device as a carrier, a float hydraulic system power-generation numerical model is built. The method is validated by comparison with previous experimental results. The predicted power generation and conversion efficiency of the point-absorption wave energy device under different regular and irregular wave conditions are compared. Key factors affecting the power generation performance of the device were investigated, providing insight for the subsequent optimal design of the device, which is of great significance to the development and utilization of wave energy resources.

Performance of a hybrid system with a semi-submersible wind platform and annular wave-energy converters

Performance of a hybrid system with a semi-submersible wind platform and annular wave-energy converters

Power prediction of oscillating water column power generation device based on physical information embedded neural network

Due to its simplicity and high reliability, Oscillating Water Column (OWC) wave energy conversion devices hold great promise for practical applications. The optimization of OWC parameters is currently a hot research topic. In this study, we address the challenges of rapid response prediction and parameter optimization for OWC systems by developing a physics-informed neural networks (PINN) model. The influence of different physical constraints on the performance of the PINN model is investigated. Our research demonstrates that incorporating the key parameter of wave elevation in the intermediate layer enhances the interpretability, prediction accuracy, and scalability of the model but may affect its convergence. By including the prior physical knowledge of the correlation between water volume change rate and power generation efficiency into the loss function, the convergence of the neural network model can be improved, albeit with minimal impact on prediction accuracy and scalability. Additionally, introducing the critical laws discovered in subsequent analyses regarding the relationship between wave elevation distribution and power generation efficiency into the loss function enhances the convergence of the PINN model while significantly improving its scalability. In summary, by integrating various physical constraints, including key parameters, prior knowledge, and critical laws, into the neural network model, significant improvements can be achieved in the interpretability, accuracy, convergence, and scalability of the model. The findings of this study highlight the avenues through which neural network model performance can be improved from these three perspectives, aiming to provide guidance for related modeling endeavors.

Fault diagnosis of a wave energy converter gearbox based on an Adam optimized CNN-LSTM algorithm

The complex structure and harsh operating environment of wave energy converters can result in various faults in transmission components. Environmental noise in practical operating situations may obscure the effective information in collected vibration signals, significantly increasing the difficulty of fault diagnosis. This paper presents a fault diagnosis model for the gearbox of the point absorber wave energy converter. The model integrates a convolutional neural network with long short-term memory to realize efficient extraction of local features from signals and enhance the performance in time-series analysis. Moreover, the model incorporates the Adaptive Moment Estimation algorithm to address the situations where gradients within tensors exhibit unstable changes in the model. A rigid-flexible coupled dynamics simulation model is developed to simulate vibration signals used to train and verify the fault diagnosis model. Experimental tests of the proposed model on a vibration dataset acquired from real vibration experiments demonstrate its efficacy in diagnosing various types of faults under interference of operating conditions. Comparative studies with other models demonstrate the superiority of the proposed model in terms of fault feature extraction, learning convergence efficiency, and diagnostic accuracy, indicating that the proposed model can achieve faster and more accurate fault diagnosis of wave energy converter gearboxes.

One Meter Triboelectric Nanogenerator for Efficient Harvesting of Meter‐Scale Wave Energy

AbstractTriboelectric nanogenerators (TENGs) are effective in harvesting high‐entropy low‐frequency wave energy, yet traditional TENGs struggle to align with the meter‐scale wavelengths prevalent in marine environments, significantly impairing their wave energy conversion efficiency. Addressing this, the One Meter TENG (OM‐TENG) is introduced, a pioneering advancement in TENG design that extends the shell size to 1 m. This innovation features a novel lantern‐shaped stacked silicon‐manganese steel sheet configuration, optimizing internal space usage, and achieving a single‐cycle transfer charge of 60.82 µC and a friction layer area density of 1.76 cm−1. Furthermore, by integrating a segmented limiter device for rational control of different sliders, effective contact separation among numerous TENG units is realized. Comprehensive evaluations through theoretical analysis, multiphysics field numerical simulations, sensor data analytics, and comparative experimental measurements have unequivocally demonstrated OM‐TENG's superior capability in capturing meter‐scale wave energy under actual environmental conditions, alongside its remarkable anti‐capsize performance. Achieving peak outputs of 584 V and 444 µA, OM‐TENG can power 96 2 W LEDs and drive wireless communication modules, marking a significant step forward in the efficient utilization of wave energy and the design of large‐scale TENGs.

Exponential slime mould algorithm based spatial arrays optimization of hybrid wind-wave-PV systems for power enhancement

Renewable clean energy sources, such as wind, solar, and wave energy, are currently gaining prominence and are being extensively researched. Given the escalating significance of clean energy, hybrid systems have gradually become an effective solution to address energy and environmental issues. In order to maximize the advantages of wind, wave energy, and photovoltaic (PV), this paper proposes a hybrid wind-wave-PV system (HWWPS) by combining wind turbines, PV panels, and wave energy converter (WEC) to achieve higher energy production and efficiency. To further enhance power output, this paper focuses on the influence of system spatial array optimization on power output and adopts an algorithm to establish a strategic layout. Through the integration of the chaos algorithm, exponential asynchronous factor, and the sine-cosine mechanism, the original slime mould algorithm (SMA) algorithm is enhanced to the exponential slime mould algorithm (ESMA), which has better optimization capability and is particularly suitable for determining the optimal power configuration. Simulations are conducted on hybrid systems consisting of three, seven, and thirteen buoys, respectively, which compare the ESMA are compared with the other six algorithms. The results verify the advantages of ESMA over the other algorithms, and demonstrates the superiority becomes more prominent as the system size increases.

Modeling, system identification, and friction compensation of an actuator system for heave and surge wave energy converter experiments

Modeling, system identification, and friction compensation of an actuator system for heave and surge wave energy converter experiments

Impact of translator mass and buoy choice on a power absorption of point absorbing wave energy converter linear generator with linear generator power take off

AbstractOcean waves have the potential to contribute to future renewable electricity production. A wave energy converter (WEC) is a technology developed to absorb the energy of the wave and convert it to another form of energy. The Uppsala University WEC (UU WEC) is a point absorber with a direct drive permanent magnet synchronous linear generator power take off. Among other parameters affecting the value of absorbed power for UU WEC are the buoy size, mass of the system consisting of the buoy and translator, and available wave energy at the site of interest. This study reviews the earlier static model that considered only static forces as the buoyancy and gravity forces and neglected all dynamic forces. The static model was proposed to simplify the early‐stage design decision. Although the static model was applied to two UU WECs of different dimensions, the present study shows that the static model is not held for certain buoy and translator dimensions. As an alternative, the dynamic model which accounts for the impact of hydrodynamic forces and various translator masses is proposed. The dynamic model is based on Cummins' equation and the linear potential flow theory, and the damping force is approximated as a viscous damper with the constant damping coefficient optimizing the absorbed mechanical power under a particular sea condition. The dynamic model is applied to four fixed buoy geometries of two shapes (cylinder and cylinder with a moonpool), each of two different dimensions, but the method can be extended to other buoy shapes and dimensions. In addition, the impact of translator mass was assessed for two sites located on the west coast of Sweden and near Gran Canaria, Spain. A translator of 10–11 t promotes 16.8% higher annual average power absorption for a cylindrical buoy compared to a translator of 6 t for the same buoy. However, heavier translators up to 15 t provide only 1.1% increase in average annual absorbed power.

Nonlinear modelling of arrays of submerged wave energy converters

Studies of arrays of wave energy converters (WECs) with respect to power absorption and array interactions are often performed using linear models. However, nonlinear effects can be important and may change power estimates and optimal array designs. In this study, we have compared linear predictions of the behaviour of a shallowly submerged, buoyant point absorber with predictions from the nonlinear model SWASH with a WEC incorporated (WEC-SWASH). The latter was first comprehensively validated against 1:20 Froude scaled measured data from physical experiments. WEC-SWASH predictions of body motions and mean power absorption were generally in good agreement with measurements (absolute bias within 25%), although some discrepancies were observed in the body motions, especially when the device exhibited motion instabilities. The validated WEC-SWASH model was then compared with a linear frequency-domain model, as the latter is well-known and widely used because of its computational efficiency. Model comparisons were carried out for both an isolated WEC and small arrays (up to 5 devices). The mean power estimates from the linear model and WEC-SWASH for two representative wave farms showed good agreement for mild waves, with a difference of less than 5%. However, for larger waves, the disagreement increased to about 75 to 85% between the models (for the two wave farms tested). We found that array interactions for these arrays depend on wave amplitude and not just wave frequency. Furthermore, we discovered that the power take-off coefficients optimized using the linear model were not the optimum coefficients for the nonlinear model (WEC-SWASH).

Recent Progress on Built-in Wave Energy Converters: A Review

A built-in wave energy converter (BI-WEC) is a type of WEC that is fully encapsulated within a floating body that is easy to integrate and promotes reliability. Significant advantages in integration and reliability make BI-WECs a promising pathway to achieve an in situ power supply for massive distributed marine equipment (such as ships, buoys, or USVs). A comprehensive review of the recent advances in built-in wave energy converters can help address the most relevant issues in BI-WEC development. This study enumerates recent progress on BI-WECs (energy capture, power take-off, and control) and summarizes the characteristics of various designs. Different design philosophies and technical pathways can be better understood through the classification and analysis offered by this study. This review helps to form a basic understanding of BI-WEC development to achieve in situ power sustainability for a large amount of distributed marine equipment in long-term sustained marine operations.

The onset of instability in a parametric resonance energy harvester under panchromatic excitations

This paper further explores the potential of parametric resonance to enhance wave energy conversion in a pendulum-based pitching floating energy harvester, considering power extraction and panchromatic excitation. Unlike traditional parametric systems that focus on inertial mechanical instability induced by floater motion, this concept, firstly proposed in a previous recent publication, leverages the parametric resonance induced by nonlinear hydrodynamic coupling between heave and pitch. By deliberately integrating parametric instability into the floater design with a 2:1 ratio of natural periods in two hydrodynamic degrees of freedom, the frequency bandwidth of the mechanical system is expanded, leading to two distinct regions of significant power production. The research advances current understanding in three key areas: (i) the use of Bezier curves to advance a computationally efficient nonlinear hydrodynamic model based on nonlinear Froude–Krylov force calculations tailored for prismatic floaters, (ii) investigation of the impact of power extraction on the severity of nonlinear parametric resonance, and (iii) consideration of more realistic panchromatic waves to quantify the onset of instability and the decrease in the severity of parametric resonance response, also addressing practical implications for numerical simulations and signal processing. Findings indicate that beneficial parametric resonance persists across various damping and wave conditions, although the relative importance of the contribution of the 2:1 parametric resonance region to power extraction decreases by 75%, on average.

Shared mooring system designs and cost estimates for wave energy arrays

For floating renewable energy devices to become more cost-efficient and commercially scalable, their mooring system designs must be low-cost and suited for large-scale installations. Large arrays of floating devices, such as wave energy converters (WECs), will likely be designed with an individual mooring system for each device in the array. However, new mooring technology advancements provide options to use shared mooring lines to connect adjacent devices to one another, reducing the total number of anchors in the array, thereby reducing material use and cost. This paper explores the design, modeling, and cost analysis of shared mooring systems for various sizes of arrays consisting of heaving oscillating water column (OWC) WECs. Shared mooring systems for WEC arrays sized in 2×N and N×N grid layouts are designed to meet the relevant design standards, checking their performance with a nonlinear time-domain dynamic simulation, and the costs of each are calculated and compared. Several assumptions are taken in the design process to produce efficient results, providing a preliminary optimization for guidance on design decisions rather than a full, detailed design analysis. Mooring system costs per WEC were found to decrease as the number of WECs in the array increase, up to certain array sizes. The 2 × 3 array had the lowest mooring system cost per WEC out of all arrays considered, with a 60% cost reduction relative to using individual mooring systems. The 3 × 3 and 4 × 4 arrays achieved a 50% cost per WEC reduction. In addition to these significant cost reductions, the shared mooring system designs can provide advantages through smaller mooring system footprints, lower installation times, and less seabed disturbance.

Oscillating surge wave energy converter using a novel above-water power takeoff with belt-arc speed amplification

We investigate the performance of a novel power takeoff (PTO) featuring belt-arc speed amplification for oscillating surge wave energy converters (OSWECs), aiming to address the PTO design challenges of extremely low rotary speed and large torque under the low-frequency and large energy density ocean wave excitations. The belt-arc design significantly increases the rotary speed of the generator, enabling generator downsizing and decreasing the powertrain friction losses. The design also allows for placing the generator above water, eliminating the need for high Ingress Protection ratings for the generator and powertrain, and potentially leading to substantial reductions in capital and maintenance costs. Using the potential flow theory, the dynamics of the integrated system are analyzed, and key parameters are identified. To validate the numerical analysis, a 1:10 scale model is designed, fabricated, and tested in a wave tank. Performance evaluations are conducted under regular and irregular wave conditions, with quantified effects of parameter tuning. The results reveal an optimal wave-to-electric efficiency of 48% under regular wave excitation and 20% under irregular excitation. These findings underscore the effectiveness of the proposed novel PTO design in addressing the challenges of low rotation speed and large torque inherent in OSWECs, demonstrating its ability to efficiently convert wave power into electricity.

Optimization of Design Parameters for Improved Buoy Reliability in Wave Energy Converter Systems

Wave energy converters are frequently subjected to cyclic fatigue loads, making them prone to structural failure. This study presents a comprehensive design for reliability analysis of buoy structures used in ocean energy converters. A finite element model (FEM) was developed using ABAQUS to evaluate the effects of different materials—linear low-density polyethylene (LLDPE) versus high-density polyethylene (HDPE)—as well as variations in rib spacing and structural thickness under uniform pressure conditions. The analysis considered configurations with 3, 5, and 7 ribs, and wall thicknesses of 0.5, 0.7, and 1 inch. Results indicated that increasing the number of ribs and wall thickness significantly reduces deflection and von Mises stress, enhancing structural stability. HDPE demonstrated superior strength and lower deflection compared to LLDPE, although with reduced ductility. This study provides critical insights into optimizing buoy design parameters to improve the structural performance and durability of wave energy converter buoys, ensuring their reliability and longevity in harsh marine environments.

A wave forecasting method based on probabilistic diffusion LSTM network for model predictive control of wave energy converters

Accurate long-term prediction of wave excitation forces is critical for optimizing wave energy converters, enabling enhanced control, and improving energy absorption efficiency. Traditional prediction models often employ deterministic conservative approaches, overlooking uncertainties. This paper introduces a novel prediction method based on the probabilistic diffusion model, offering a more precise prediction while accounting for uncertainty. Notably, our approach goes beyond previous works by simultaneously achieving control objectives for maximizing energy absorption, contrasting with methodologies solely focused on prediction and control tasks. The proposed method utilizes long short-time memory to extract temporal information from historical wave excitation observation. The hidden features are then processed through a diffused probabilistic-based unit. Subsequently, a time-scale neural network is developed for wave excitation moment prediction, followed by the application of nonlinear model predictive control to maximize the energy absorption. The methodology is validated on the 1:20 Wavestar prototype devices through numerical simulations. Results indicate that the predicted excitation moment closely align with measured values. In cases 4, 5, 6, the proposed method yields a substantial improvement in maximum control energy absorption–22%, 16%, and 31%, respectively–compared to traditional prediction methods. The proposed approach not only achieves a more accurate wave excitation moment prediction with uncertainty consideration but also introduces advanced control strategies in a full-scale plant application. This work contributes significantly to the field by bridging the gap between precise prediction and effective control in wave energy conversion systems.