Advanced wave energy conversion technologies for sustainable and smart sea: A comprehensive review

The quest for sustainable energy solutions has intensified interest in marine renewables, particularly wave energy. This study addresses the crucial need for an objective assessment of Wave Energy Converter (WEC) technologies, which are instrumental in harnessing ocean waves for electricity generation. To benchmark WEC technologies, we employed an integrated approach combining the MEthod based on the Removal Effects of Criteria (MEREC) and the Spherical Fuzzy Combine Compromise Solution (SF-CoCoSo). MEREC provided a systematic way to determine the importance of various benchmarking criteria, while SF-CoCoSo facilitated the synthesis of complex decision-making data into a coherent evaluation score for each technology. The results of the study offer a definitive ranking of WEC technologies, with findings emphasizing the importance of grid connectivity and adaptability to various wave conditions as pivotal to the technologies' success. While the study makes significant strides in the evaluation of WECs, it also recognizes limitations, including the potential for evolving market dynamics to influence criteria weightings and the assumption that the MCDM methods capture all decision-making complexities. Future work should expand the evaluative criteria and explore additional MCDM methods to validate and refine the benchmarking process further.

Wave energy conversion and hydrodynamics modelling technologies: A review

The Lancaster in-house code is a time-domain analysis code, developed especially for the TALOS wave energy converter, a novel wave energy conversion technology. The TALOS wave energy converter is a point absorber-like wave energy converter, but with a unique power take-off (PTO) system. The whole PTO system is fully enclosed within the structure, hence no moving parts are exposed to the harsh marine environments.
 The PTO of the TALOS WEC consists of a mass ball within the structure, with a number of springs and dampers (for instance, direct drives or hydraulic systems) connecting between the mass ball and the structure. Such an arrangement of the PTOs would make the PTO essentially non-linear, regardless whether the actual PTO dampers are linear or nonlinear as well as the linear springs. Therefore, a time domain analysis must be established for the TALOS WEC. Towards the goal, an in-house time-domain model has been developed at Lancaster University, and now it is to be validated via the delicated numerical models built using well-established commercial software (and in the future via experimental data). Within this framework, the present paper presents an effort for validation using the DNV SESAM commercial hydrodynamic and structural analysis software. 
 To build a numerical model for TALOS WEC, the Lancaster in-house time domain code is based on the hybrid frequency-time domain approach. That is, the basic hydrodynamic parameters are analysed using the panel methods (WAMIT, HAMS, NEMOH), and then the relevant parameters are transformed for the Cummins’ time-domain equation, such as the added mass at infinite frequency, and the memory effect (the convolution terms). This work is an extension of the comparison between the in-house code and the DNV SESAM software, and the comparisons would include the relevant hydrodynamic analyses, the time-domain analyses with and without the TALOS PTO system, with the aims towards developing the validated tools of both the in-house code and the commercial software.

CalWave Inc. (CalWave) is developing a wave energy converter (WEC) technology that can generate electricity from ocean waves. CalWave’s design offers a unique approach to wave energy conversion that operates fully submerged and can actively adjust the wave excitation. This capability gives the architecture enhanced survivability in ocean storms without adding significant costs. Prior to this project, CalWave had completed a demonstration of a fully functional WEC system in an open ocean demonstration at nominal 1:5 scale under FOA 1663. The goal of this project was the detailed design, following relevant standards and industry best-practices, of a variant of the xWave WEC technology that can safely and efficiently operate at the DOE’s PacWave South test site for a targeted deployment of up two years. The WEC design and associated review processes proceeded in two distinct project phases: a ‘Preliminary’ and a ‘Final’ design phase. The first phase of the project consisted of the systematic design of the WEC’s key features with regards to appropriate IEC standards. The work resulted in a preliminary design of the xWave hull including structural and Power Take-Off (PTO) load estimates, as well as performance estimates for all ocean conditions the WEC would operate in at PacWave South. Following the first open-water demonstration of CalWave’s small-scale “x1” device under FOA 1663, lessons learned were fed directly into a comprehensive review of the xWave design in the second design phase of this FOA project. CalWave’s work was supported by Sandia National Lab (SNL) and the National Renewable Energy Lab (NREL) on the holistic WEC design, and detailed feedback from specialized partners on hull design, mooring and anchoring specification, and electrical grid interconnection. Optimization of the WEC system was performed using a novel numerical optimization tool developed by Sandia and optimization trends were confirmed via an experimental model scale tank test campaign. Performance estimates for PacWave and a detailed xWave design including integration of all relevant system components were concluded. The mooring design was also concluded in the Final design phase using the most up to date sea floor characterization (CPT) data.

In compliance with the green energy policy, mitigation from high fossil fuel dependency is becoming a new objective for most countries, including Malaysia. Wave energy is among extensively explored renewable energy relatively clean, sustainable, and inexhaustible resources. To this day, neither definite wave energy technology nor widely available commercial wave farm supplying the grid has existed. Therefore, wave energy harvesting is the most compelling solution, especially in regions where the possibility of grid connection is low in the nearest future. Like other renewable energy, the voltage amplitude and frequency generated from waves are unstable and may vary continuously. This uncertainty has created energy transfer challenges since the grid requires a stable and uninterrupted energy supply. Therefore, power electronics devices are employed to modulate the controller circuits’ pulse width. Further understanding of the relationship between wave energy conversion technology and its power conversion, particularly for nearshore applications, is summarized. This work also discussed selected wave energy conversion research and power conversion system implemented and studied in Malaysia. Finally, this review can provide extensive overview and broad understanding into power conversion system for Wave Energy Conversion, especially for nearshore applications.

This paper reviews the advancements in wave energy converter technologies in China, covering device design, performance evaluation, and system control techniques. It highlights power control technologies in wave energy conversion, including adaptive control, model predictive control, clutch control, clamp control, resistive load control, approximate optimal speed control, nonlinear control, and intelligent control methods. Through an analysis of these technologies, the study outlines the future directions and challenges in wave energy development in China, while also proposing potential pathways for optimizing the performance of wave energy conversion devices.

This paper aims to review the potential of wave energy in several countries, the wave energy converter technology that has been developed, and the impact of the installation of wave energy converter technology devices on the environment. In addition, it discusses the theoretical formulations and challenges in the development of energy converter technology in the future. Based on the detail analysis, the potential of ocean wave energy for alternative energy is very large but cannot be used optimally because the technology of wave energy converter that has been developed is still on a prototype scale. In addition, the impact of the use of ocean wave converters on the environment is insignificant compared with conventional energy. Finally, this study informs and recommends the government and the private sector to start investing in the ocean wave energy industry optimally in order to achieve a sustainable future.

The Lysekil wave energy converter (WEC), developed by the wave energy research group of Uppsala University, has evolved through a variety of mechanical designs since the first prototype was installed in 2006. The hundreds of engineering decisions made throughout the design processes have been based on a combination of theory, know-how from previous experiments, and educated guesses. One key parameter in the design of the WECs linear generator is the stroke length. A long stroke requires a taller WEC with associated economical and mechanical challenges, but a short stroke limits the power production. The 2-m stroke of the current WECs has been an educated guess for the Swedish wave climate, though the consequences of this choice on energy absorption have not been studied. When the WEC technology is considered for international waters, with larger waves and challenges of energy absorption and survivability, the subject of stroke length becomes even more relevant. This paper studies the impact of generator stroke length on energy absorption for three sites off the coasts of Sweden, Chile and Scotland. 2-m, 4-m, and unlimited stroke are considered. Power matrices for the studied WEC prototype are presented for each of the studied stroke lengths. Presented results quantify the losses incurred by a limited stroke. The results indicate that a 2-m stroke length is likely to be a good choice for Sweden, but 4-m is likely to be necessary in more energetic international waters.

Knowledge of the effects of wave energy converters (WECs) on the near and far wave fields is critical to the efficient and low-risk design of waveforms. Several computational wave models enable the evaluation of WEC array effects, but model validation has been limited. In this chapter, we validate two popular models with very different formulations: the phase-resolving model WAMIT and the phase-averaged Simulating WAves Nearshore (SWAN) model. The models are validated against wave data from an extensive set of WEC array laboratory experiments conducted by Oregon State University and Columbia Power Technologies, Inc (CPT). The experimental WECs were 1:33 scale versions of a commercial device (CPT “Manta”), and several different WEC array configurations were subjected to a range of regular waves and random sea states. The wave field in the lee of the WEC arrays was mapped, and the wave shadow was quantified for all sea states. In addition, the WEC power capture performance was measured independently via a motion-tracking system and compared to the observed wave energy deficit (i.e., the wave shadow). Overall, WAMIT displays skill in predicting the wave field both in offshore and in the lee of the WEC arrays. WAMIT simulations demonstrate partial standing wave patterns that are consistent with the observations. These patterns are related to wave scattering processes, and their presence increases the magnitude of the wave shadow in the lee of WECs . The pattern is less pronounced at longer wave periods where WECs behave more like wave followers. In these situations, the wave shadow is primarily controlled by the WEC energy capture and less so by scattering. The SWAN model accounts for the frequency-dependent energy capture of the devices and performs well for cases when the wave shadow is primarily controlled by the WEC energy capture. For regular wave cases, inclusion of the wave diffraction process is necessary, but SWAN simulations for wave fields with frequency and directional spreading capture the general character of the wave shadow even without diffraction. Finally, we suggest that WECs designed to operate such that the expected significant wave energy lies at periods near, or larger than, the period of peak energy extraction will minimize the wave shadow effect for a given gross extraction of wave energy, which leads to more efficient arrays with respect to environmental impact.

Ocean waves are a vast, mostly untapped energy resource, and the potential for collecting energy from waves is enormous. Research in this field is motivated by the need to fulfil renewable energy goals, but is relatively immature compared to other renewable energy technologies. This study presents the overall state of wave energy and analyzes the device types that reflect current wave energy converter (WEC) technology, especially concentrating on work being done inside the United Kingdom. The potential power take-off systems are defined, followed by a study of some of the control methods to improve the efficiency of point absorber-type WECs. There is a lack of consensus on the optimum technique of collecting energy from the waves and, while past innovation has typically concentrated on the idea and design of the main interface, issues emerge about how best to optimize the power train. This essay ends with some recommendations of future advancements.

Power capture performance of an oscillating-body WEC with nonlinear snap through PTO systems in irregular waves

Experimental investigation and performance comparison of a 1 single OWC, array and M-OWC

Ocean energy technologies are in their developmental stages, like other renewable energy sources. To be useable in the energy market, most components of wave energy devices require further improvement. Additionally, wave resource characteristics must be evaluated and estimated correctly to assess the wave energy potential in various coastal areas. Multiple algorithms integrated with numerical models have recently been developed and utilized to estimate, predict, and forecast wave characteristics and wave energy resources. Each algorithm is vital in designing wave energy converters (WECs) to harvest more energy. Although several algorithms based on optimization approaches have been developed for efficiently designing WECs, they are unreliable and suffer from high computational costs. To this end, novel algorithms incorporating machine learning and deep learning have been presented to forecast wave energy resources and optimize WEC design. This review aims to classify and discuss the key characteristics of machine learning and deep learning algorithms that apply to wave energy forecast and optimal configuration of WECs. Consequently, in terms of convergence rate, combining optimization methods, machine learning, and deep learning algorithms can improve the WECs configuration and wave characteristic forecasting and optimization. In addition, the high capability of learning algorithms for forecasting wave resource and energy characteristics was emphasized. Moreover, a review of power take-off (PTO) coefficients and the control of WECs demonstrated the indispensable ability of learning algorithms to optimize PTO parameters and the design of WECs.

In this paper, a collection of deep water (>100 m) wave records was assessed to create a long-term, statistically reliable data set. These wave data were derived from the Coastal Information Data Program (CDIP) Buoy Data from UCSD Scripps Institute of Oceanography, National Data Buoy Center (NDBC) Buoy Data from NOAA, and other sources. From this data set, long-term annual averages and monthly wave probability distributions were analyzed for ten one degree latitude bins bounded by the 100 m and 1000 m depth contours seaward of the California coast. The probability distributions were used to quantify the potential for useful electricity extraction from the coastal wave of California. Optimal locations for developing wave energy installations are specified. The California coast north of Point Conception has an ideal wave resource for the generation of electricity from wave energy. South of Point Conception the wave energy arriving from North Pacific storms is efficiently blocked by the significant change in California coast orientation south of Point Conception and the Channel Islands. The near coastal Southern California (SOCAL) region has a significantly reduced wave resource compared to the California coast north of Pont Conception. Factors impacting the status of ocean wave energy technologies and their development are also discussed. Applicability of the wave statistical results is critical to determine the average “wave to wire” efficiency for the many different types of wave energy converter (WEC) technologies that exist in many different states of commercial development.

Optimal configuration of a discrete fluid power force system utilised in the PTO for WECs