Wave Energy Projects Research Articles

Assessment and prediction of significant wave height using hybrid CNN-BiLSTM deep learning model for sustainable wave energy in Australia

Wave energy is regarded as one of the powerful renewable energy sources and depends on the assessment of significant wave height (Hs) for feasibility. Hence, this study explores the potential of wave energy by assessing and predicting Hs for two study sites in Queensland (Emu Park and Townsville), Australia. Assessment and prediction of Hs is extremely important for reliable planning, cost management and implementation of wave energy projects. The study utilized oceanic datasets based on wave measurements obtained from buoys along coastal regions of Queensland that are transmitted to nearby receiver stations. The parameters of the datasets include maximum wave height, zero up crossing wave period, peak energy wave period and sea surface temperature to accurately predict Hs. A new hybrid Convolutional Neural Network (CNN) and Bidirectional Long Short Term (BiLSTM) deep learning model with Multivariate Variational Mode Decomposition (MVMD) is developed which is benchmarked by Multi-Layer Perceptron (MLP), Random Forest (RF) and Categorical Boosting (CatBoost) to compare the performance. All models attain relatively high-performance results. The MVMD-CNN-BiLSTM attains slightly better performance values for both study sites among all developed models with highest correlation values of 0.9957 and 0.9986 for Emu Park and Townsville, respectively. Other performance evaluation metrics were also higher for MVMD-CNN-BiLSTM with lowest error values in comparison to the benchmark models. The annual mean of Hs is also computed to compare and obtain an insight with a linear projection. There is a greater ocean wave energy potential for Emu Park for a 10-year period with a projected mean Hs of 0.865 m in comparison to Townsville where the projected mean was of 0.665 m.

A novel framework for wave power plant site selection and wave forecasting based on GIS, MCDM, and ANN methods: A case study in Hainan Island, Southern China

Wave power plants (WPPs) hold significant promise for sustainable energy generation but face complex challenges in site selection and wave forecasting. To address these challenges, this study presents an integrated methodology that combines geographic information system (GIS), multi-criteria decision making (MCDM) and artificial neural network (ANN) techniques. The primary objective of this research is to identify optimal sites for WPP deployment and enhance the accuracy of wave power density (WPD) forecasting. The study focuses on Hainan Island, the second-largest island in China, and employs both macro-scale and micro-scale site selection methods. It establishes a comprehensive criteria system that encompasses environmental, technical, economic, and social aspects. To improve the objectivity of criteria weighting, a group decision making-analytic hierarchy process (GDM-AHP) approach is applied. The findings reveal that approximately 1.36 % (1427.93 km2) of Hainan Island's area offers suitable conditions for WPP deployment, with concentrations in the southern, northern, and eastern marine regions. Among the 27 identified alternative sites covering 208.76 km2 along the eastern coast, six optimal sites are pinpointed in Wanning, Wenchang, and Qionghai. Furthermore, the optimized ANN outperforms the standard ANN, achieving a mean relative error of 9.0 %. This research contributes to the theoretical understanding of WPP site selection and wave forecasting while offering a practical and adaptable framework for stakeholders involved in renewable energy projects, particularly in coastal areas such as Hainan Island. These results and methodologies have real-world implications for the efficient and effective deployment of wave energy projects, ultimately promoting sustainable energy generation and socioeconomic development.

Wave energy communication and social opposition

Despite the benefits of marine renewable energies (MRE) to the decarbonisation, public opposition has often been posed to MRE projects. This opposition is one of the reasons slowing down Europe´s energy transition towards clean energies. Aside from one wave energy production farm operating in Europe, other developments are still at pilot or prototype phases. In the context of European SAFEWAVE project (https://www.safewave-project.eu/), we aim to understand the causes that trigger opposition to wave energy projects and identify how communication could improve the perception and attitudes towards MRE projects. To achieve this aim, a systematic analysis of ongoing wave energy projects, scientific bibliography and social media has been carried out. Outputs of this research indicate that opposition to wave energy is rather limited and primarily posed by national and local communities, as well as NGOs. Opposition emerges after envisaging negative affection on i) economy (e.g., conflict with existing uses), ii) social aspects (e.g., local communities for which the benefits are unclear), and iii) the environment (e.g., uncertainty on environmental impacts). Despite much of the wave energy information available on the media is produced and communicated by scientists and engineers (which should be considered a reliable sources of information), most of the communicated content focus on the drivers, the technological developments and benefits. Limited information on potential impacts of wave energy projects is shared. The target audiences vary between channels; YouTube, Facebook and Google have a wider audience than Twitter, which seeks a more professional audience. A holistic communication approach, in which both expected benefits and impacts are communicated may reduce opposition and help society to become more marine energy-literate, allowing for informed decisions and responsible behaviours/attitudes. Availability of official documents, participatory approaches, and transparency are crucial for improving the perception of future wave energy projects.

Choosing wave energy devices for community-led marine energy development

As we pursue more justice and community driven renewable energy projects, more decision making is put in the hands of community leaders. Appropriate tools and resources are necessary for communities to determine what wave energy developer might fit their community needs and wave resource. While there are methods and tools for communities, researchers and wave energy developers to determine the wave resource or potential locations for wave energy development, we are lacking a tool to help communities take the next steps in pursuing wave energy.
 A community driven design process was undertaken in Sitka, AK, in conjunction with evaluating the local area for wave energy resource. The community had interest in wave energy development, a decent wave resource area accessible, and existing maritime expertise that could aid in operations and maintenance. Further, as a remote island, the community viewed alternative energy development positively as a way to achieve more energy independence. Still, in this community driven process, we identified a gap that while the community may be interested in a wave energy project, there was little data on which wave energy devices would be appropriate for the community and few tools to help them choose.
 This presentation will highlight questions that the participants from Sitka, AK still have after engaging in a community centered design process. We compare the requirements that the community prioritizes with the tools that researchers and developers have to evaluate those requirements, allowing assessment of whether these tools are useable and adequate for community use. We also show an analysis of a selection of current wave energy developers with some of the community focused factors and proposals for tools that may be useful in future community energy development. This research ultimately highlights what factors must be presented to a community for them to choose to pursue installation of a device.

Techno-economic feasibility of marine eco-parks driven by wave energy: A case study at the coastal arid region of Mexico

Coastal arid regions face significant challenges in ensuring energy, water, and food security. Given the urgency of meeting these demands, it is necessary to consider innovative solutions that enhance adaptive capacity and sustainable development of coastal zones. Harnessing wave energy has become a potential ocean renewable resource that can provide significant benefits to mitigating coastal vulnerability and climate change. However, most wave energy projects still face different challenges that limit their financing and commercial deployment. This paper aims to evaluate the techno-economic feasibility of 0.5 MW Marine Ecoparks as maritime clusters coupled with wave energy converter, seawater desalination, and marine aquaculture modules to produce the water-energy-food nexus and boost, symbiotically, the viability of the wave energy sector and the blue economy in the arid coastal communities of Baja California, a Mexican Pacific region with a mid-wave energy resource. Based on technical and economic data available in the literature, the cost estimates and the contribution of each coupled module to the Marine Ecopark profitability were carried out and compared against other forms of energy generation using different current and projected 2030 market scenarios. All the cases analyzed show that the Pelamis device generates higher techno-economic performance than the WaveDragon. While individual wave energy devised siting is not profitable, economic scaling in increases maritime clusters' profitability. Optimally selected Pelamis facilities attain capacity factors over 40 % and a Levelized Cost of Energy of 480 $/MWh. The coupled seaweed aquaculture module generates the highest water-energy-food nexus profitability, whereas seawater desalination is not economically viable. All wave energy farms show a decrease in estimated electricity cost by 2030, reaching 198 USD/MWh for the most competitive Pelamis farms.

The contribution of the SafeWAVE EU project to the future development of ocean energy

The European Atlantic Ocean offers a high potential for marine renewable energy (MRE), which is targeted to be at least 32% of the EU’s gross final consumption by 2030. The European Commission is supporting the development of the ocean energy sector through an array of activities and policies: the Green Deal, the Energy Union, the Strategic Energy Technology Plan (SET-Plan) and the Sustainable Blue Economy Strategy. The nascent status of the MRE sector and Wave Energy (WE) in particular, yields many unknowns about its potential environmental pressures and impacts. Wave Energy Converters’ (WECs) operation in the marine environment is still perceived by regulators and stakeholders as a risky activity. The complexity of MRE licensing processes is also indicated as one of the main barriers to the development of the sector. The lack of clarity of procedures, the varied number of authorities to be consulted and the early stage of Marine Spatial Planning (MSP) implementation are examples of the issues identified that may delay the permitting of the projects. Finally, there is also a need to provide more information on the sector to the general public. Only with an informed society would be possible to carry out fruitful public debates on MRE implementation at the local level. These non-technological barriers that could hinder the future development of WE in EU were addressed by the WESE project funded by EMFF in 2018. The present project builds on the results of the WESE project and aims to move forward through the following specific objectives:
 
 Development of an Environmental Research Demonstration Strategy based on the collection, processing, modelling, analysis and sharing of environmental data collected in WE sites from different European countries where WECs are currently operating (Mutriku power plant and BIMEP in Spain, Aguçadoura in Portugal and SEMREV in France).
 Development of a Consenting and Planning Strategy through providing guidance to ocean energy developers and to public authorities tasked with consenting and licensing of WE projects in France and Ireland; this strategy will build on country-specific licensing guidance and on the application of the MSP decision support tools (i.e. WEC-ERA[1] and VAPEM[2] tools) developed for Spain and Portugal in the framework of the WESE project; the results will complete guidance to ocean energy developers and public authorities for most of the EU countries in the Atlantic Arch.
 Development of a Public Education and Engagement Strategy to work collaboratively with coastal communities in France, Ireland, Portugal and Spain, to co-develop and demonstrate a framework for education and public engagement (EPE) of MRE enhancing ocean literacy and improving the quality of public debates.
 
 The project will finish in September 2023. In this contribution we present the main outcomes, results and lessons learnt during the project.
 [1] https://aztidata.es/wec-era/;
 [2] https://aztidata.es/vapem/

Principles of ADCP deployment methodologies

ADCPs are regularly used for resource characterization in wave and tidal energy sites; however, methodologies and best practices are entirely dependent on the site characteristics and the assets available. EMEC have used their widely varied experience at multiple sites and locations to develop a review of methodologies and the pros and cons of different deployment styles for data acquisition.When deploying ADCPs there are a number of site criteria that must be assessed, such as seabed type, bed flow speeds, surface flow speeds, recovery windows (slack and weather), and water depth and range. These criteria can significantly affect the success or failure of marine operations, not necessarily for deployment but certainly for recovery. When recovery operations fail then projects lose assets (ADCP units and bed frames), data, and money (in hire/unit costs, and vessel hire for example). When the data is not recovered then this can jeopardise project success, wasting time, effort and funding.Different deployment configurations and recovery techniques have been used for ADCP deployments. Equipment such as ground lines, acoustic releases, USBLs, and surface buoys are used to mark, locate, and/or recover devices. These are varied depending on a number of factors. Ground type, for example, can affect systems used since a ground line cannot be effectively used in delicate ecosystems since the dredging required to recover may disturb local flora and fauna. Also, for example, flow speed and vessel traffic will determine whether a surface buoy can be used.Based on multiple ADCP deployments to characterize resource for wave and tidal energy projects in Scotland, England, France and other sites, EMEC have reviewed different deployment methods and recovery techniques. There is a proposed set-up for deployments suitable for a number of active marine energy sites and suggestions for edits based on site characteristics and target data requirements.

The impact of climate change on the wave energy resource potential of the Atlantic Coast of Iberian Peninsula

This study investigates the impact of climate change on the wave energy potential along the Atlantic coast of the Iberian Peninsula, a region acknowledged for its high wave energy resource. The research focuses on the annual and intra-annual variations in wave power for the high-emission RCP8.5 global warming scenario over different time frames: historical, near-future, and far-future. The results show a decreasing trend in the wave energy resource throughout the study area, with the most notable reductions observed in the northwestern region. The reduction in maximum annual power ranges from 15.1 to 7.2 kW/m. Changes in atmospheric circulation patterns and ocean surface temperature gradients induced by climate change effects could explain these results. This study also discusses the impacts of wave power projections on the design of wave energy converters and their future operation. The outcomes are of high interest to adapt the renewable energy infrastructure to a changing climate, ultimately also aiding in the strategic planning and cost-effective design of future wave energy projects.

A practical method for modeling temporally-averaged ocean wave frequency-directional spectra for characterizing wave energy climates

Wave energy resource characterization investigations have been hindered because frequency-directional wave spectra are not broadly available for many coastal regions due to the insufficient spatial coverage of buoy observation networks and spectral wave model hindcast outputs. We address this problem by developing and validating a practical method for approximating temporally-averaged frequency-directional wave spectra averaged over periods of months or years from bulk wave parameters, which are available at a much greater coverage and resolution than frequency-directional wave spectra. While the temporally averaged frequency-directional wave spectrum over these periods cannot be used for analyzing a single sea state, it aggregates multiple sea states, identifies dominant wave energy systems representing wave climate, and resolves their spectral characteristics. Therefore, modelling temporally averaged frequency-directional wave spectra is of great value for planning and designing wave energy projects, e.g., resource characterization, site assessment, and conceptual design of wave energy converters. Temporally-averaged frequency-directional wave spectra and related important wave energy parameters approximated using this method are found to be more accurate than commonly used parametric wave spectrum models. This method can be applied to a wide range of wave climates given its universality and high accuracy. Also, the availability of bulk wave parameters from multi-decade high-resolution wave model hindcasts is increasing.

A Review of the Levelized Cost of Wave Energy Based on a Techno-Economic Model

Wave energy provides a renewable and clear power for the future energy mix and fights against climate change. Currently, there are many different wave energy converters, but their costs of extracting wave energy are still much higher than other matured renewables. One of the best indicators of calculating the generating cost of wave energy is the ‘levelized cost of energy’ (LCOE), which is the combined capital expenditure (CAPEX), operational expenditure (OPEX), and decommissioning cost with the inclusion of the annual energy production, discount factor, and project’s lifespan. However, the results of the LCOE are in disagreement. Hence, it is important to explore the cost breakdown of wave energy by the wave energy converter (WEC), so for finding potential ways to decrease the cost, and finally compare it with other renewable energies. Different WECs have been installed in the same place; the Wave Dragon LCOE platform is the best one, with an energy conversion of EUR 316.90/MWh, followed by Pelamis with EUR 735.94/MWh and AquaBuOY with EUR 2967.85/MWh. Even when using different locations to test, the rank of the LCOE would remain unchanged with the different value. As the CAPEX and OPEX dramatically drop, the availability and capacity factors slowly increase, and the LCOE decreases from a maximum of USD 470/MWh to a minimum of USD 120/MWh. When the discount rate is down from 11% to 6%, the LCOE reduces from USD 160/MWh to USD 102/MWh. Under the ideal condition of the optimal combination of multiple factors, in theory, the LCOE can be less than USD 0.3/KWh. To better explore the LCOE for WECs, the detailed cost elements found in the CAPEX and OPEX have been examined for the scenarios of the undiscounted, half-discounted, and discounted cost models. When the AEP is discounted, the lowest LCOE is equal to USD 1.171/kWh in scene 2 when using a five-step investment, which is below the LCOE value of USD 1.211/kWh in scene 1 when using a two-step investment. Meanwhile, the highest LCOE amounts to USD 2.416/kWh using the five-step investment, whose value is below the LCOE of a two-step investment. When using a one-step investment in scene 3, the lowest LCOE is equal to USD 0.296/kWh, which accounts for 25% of the lowest value in the five-step investment. Meanwhile, the highest LCOE amounts to USD 0.616/kWh, which accounts for 24% of the highest value in the two-step investment. The results of the case study show that a one-step investment program in the half-discounted model is superior to the multi-step investment in the discounted model. This paper examines the viability of wave energy technologies, which is a critical factor for the LCOE of wave energy; furthermore, the form of investment in the wave energy project is also important when calculating the LCOE.

Model tests on a floating coaxial-duct OWC wave energy converter with focus on the spring-like air compressibility effect

The spring-like air compressibility effect in oscillating-water-column (OWC) wave energy converters may significantly affect the device’s power performance. Yet, this effect has rarely been accounted for in physical model testing, especially in floating OWCs. Quantifying this effect in the development and analysis of OWCs is crucial for i) making better estimates of their performances and decreasing uncertainties, ii) improving design and testing processes, iii) reducing development costs, and iv) accelerating decision-making on wave energy projects. This paper presents experimental results of a floating coaxial-duct OWC at 1:40-scale. The experimental campaign comprised tests in which the Froude scale was applied to the whole converter structure and, for comparison, tests where the air chamber volume was expanded to comply with the aero-thermodynamic similitude. Tests included regular and irregular waves and various damping conditions. Experimental results show that compressibility effects can increase, decrease, or have neutral contributions to the mean absorbed power, depending on wave frequency. Another effect is the presence of reactive power. The capture width ratio is higher for the compressible experimental configuration in several cases. A new compressibility factor is proposed to aid in designing experimental and numerical campaigns.

A Bayesian Network model to identify suitable areas for offshore wave energy farms, in the framework of ecosystem approach to marine spatial planning

The production of energy from waves is gaining attention. In its expansion strategy, technical, environmental and socioeconomic aspects should be taken into account to identify suitable areas for development of wave energy projects. In this research we provide a novel approach for suitable site identification for wave energy farms. To achieve this objective, we (i) developed a conceptual framework, considering technical, environmental and conflicts for space aspects that play a role on the development of those projects, and (ii) it was operationalized in a Bayesian Network, by building a spatially explicit model adopting the Spanish and Portuguese Economic Exclusive Zones as case study. The model results indicate that 1723 km2 and 17,409 km2 are highly suitable or suitable for the development of wave energy projects (i.e. low potential conflicts with other activities and low ecological risk). Suitable areas account for a total of 2.5 TWh∙m−1 energy resource. These areas are placed between 82 and 111 m water depth, 18–30 km to the nearest port, 21–29 km to the nearest electrical substation onshore, with 143–170 MWh m−1 mean annual energy resource and having 124–150 of good weather windows per year for construction and maintenance work. The approach proposed supports scientists, managers and industry, reducing uncertainties during the consenting process, by identifying the most relevant technical, environmental and socioeconomic factors when authorising wave energy projects. The model and the suitability maps produced can be used during site identification processes, informing Strategic Environmental Assessment and ecosystem approach to marine spatial planning.

Sectoral Analysis of the Fundamental Criteria for the Evaluation of the Viability of Wave Energy Generation Facilities in Ports—Application of the Delphi Methodology

Nearly 40% of the world’s population lives within 100 kilometres of the coast with the risk that this implies in terms of exposure to the effects of climate change. Ocean energy, according to the IPCC (Intergovernmental Panel on Climate Change) in 2019, has been identified as one of the measures for mitigating these effects. In addition, ocean energy can play an essential role in achieving some of the SDGs (Sustainable Development Goals) set at the Paris Climate Summit in 2015, namely SDG 7 (clean and affordable energy) and SDG 13 (climate action) and could have a substantial impact on others such as SDG 1 (poverty eradication), SDG 2 (end hunger), SDG 5 (gender equality), SDG 6 (universal energy access), SDG 8 (promote sustainable economic growth), SDG 9 (build resilient infrastructure), SDG 14 (sustainable conservation of oceans and seas) and SDG 17 (promote sustainable development cooperation). There are several projects under development around the world aimed at extracting energy from waves. However, to date, no technology has been found that, in general terms, is superior to others. There are several conditioning factors that prevent this type of energy from reaching the level of maturity of other marine renewable energies. These are mainly economic, technological, environmental, and regulatory, to mention the most important. This article aims to analyse the approaches that other researchers have adopted to evaluate wave energy projects and, through a prospective method of expert consultation such as the Delphi methodology, will present the most generally accepted criteria for successful wave energy projects. Subsequently, the validity of these results will be analysed for the case of the use of the energy produced for self-consumption in ports.

Evaluation of a few wave energy converters for the Indian shelf seas based on available wave power

The energy resource assessment at a location is crucial for designing wave energy projects. However, there is a divergence in wave energy converter (WEC) design due to diversity in wave climate, energy availability, and conversion methodology. Optimizing devices for different wave climates is essential since low risk, low variability, and moderate energy resources are attractive. This paper examines the location-wise wave characteristics with energy resource evaluation and the performance of a few WECs in the Indian shelf sea using the WAVEWATCH III model output data for 26 years (1990–2015). The annual mean wave power at 25–30 m water depth at the 20 stations varies from 1.49 kW/m to 11.79 kW/m. From offshore to nearshore waters, a large reduction in wave power is observed at a few stations. At stations off the west coast, southernmost peninsular, and northwest Bay of Bengal, the percentage wave power available during summer monsoon is 42–87% of the annual power. K-means clustering algorithm is applied to the study area and obtained two device classes. Based on Multi-Criteria Approach, different WEC for different sites are evaluated.

A new framework and tool for ecological risk assessment of wave energy converters projects

Marine renewable energy has considerable potential for enhancing the diversity of renewable sources, to reduce our reliance on fossil fuels and combat climate change. While the technological development of wave energy converters is progressing rapidly, their environmental impacts are still largely unknown, which is a barrier that could hinder their deployment. This research contributes to the state-of-the-art by introducing a framework for quantifying and analysing the ecological risks of three technologies (oscillating water columns, oscillating wave surge converters, and wave turbines). Based on a literature review, expert consultation process, and the development of a web tool, the potential pressures and the ecosystem elements that might be affected during the life cycle of a generic wave farm (an array of wave energy converters) are investigated. The main pressures are found to be physical disturbance, physical loss, hydrological change, and noise. The ecosystem elements sustaining the largest number of pressures and, therefore, at higher ecological risk are fish and cephalopods species, and benthic and pelagic habitats. The ecological risk assessment framework is operationalized into a free-access web tool (https://aztidata.es/wec-era/) for the interactive assessment and visualisation of the pressures and ecological risks. The tool is intended to be used by managers, decision makers, scientists or promoters during the Strategic Environmental Assessment and Environmental Impact Assessment of wave energy projects. The novel approach presented in this work is more sophisticated than previous risk assessment matrices, enabling to better capture the complexity of the interactions between a wave farm and the environment.

Dynamic self-adjusting classification for global wave energy resources under different requirements

This study designs a wave energy classification scheme that comprehensively considers energy, environmental risk and cost factors. Furthermore, by rationally adjusting, adding or deleting the weights of related parameters, a dynamic self-adjusting energy classification under different requirements is proposed to satisfy different wave energy projects or equipments. A global ocean wave energy classification is performed as a case study. According to the results, the global wave energy classes are generally optimistic, and most of the global ocean is energy-rich. The regional differences in the wave energy classes obtained by the new scheme are obvious compared to those obtained by the traditional scheme. Significant differences in the wave energy classification results are observed under different requirements. The extents of energy-poor areas in the global ocean are the smallest when focusing on cost factors and the largest when focusing on resource output. The extents of energy-rich regions above class 6 are the widest when focusing on self-sufficiency and the smallest when considering cost factors. Regardless of the demand, the energy classes in the Southern Hemisphere are always higher than those in the Northern Hemisphere, and those in the eastern ocean regions are always higher than those in the western parts.

Evaluation of Wave Energy Location by Using an Integrated MCDM Approach

In recent years, sudden global energy demand has led to the gradual exhaustion of fossil fuel, the world’s main energy resource. With the negative impact of fossil fuel on the environment, governments and organizations have increased R&D funding on renewable energy resources such as solar and wave energy. Vietnam has a great potential for developing wave energy projects owing to the presence of a long coastline and vast ocean. Choosing an optimal location for wave-based power plant projects is a multicriteria decision that requires understanding the quantitative and qualitative elements for assessing the balance of factors when trying to reach the most accurate result. This study proposes a multi-criteria decision-making (MCDM) model, fuzzy-analytic hierarchical process (FAHP), and weighted aggregated sum product assessment (WASPAS) in evaluating potential wave energy stations at the Vietnamese coastline. The authors identify all criteria and sub-criteria affecting the wave power plant location selection process through literature review and expert interview. Selection criteria include wave height, the distance between two waves, number of waves, wind speed, wind duration, ocean depth, turbulence, water quality, coastal erosion, shipping density, protection laws, labor resources, safety conditions, and other related factors. FAHP was used to determining the weights of the identified criteria in the first stage of this study. Finally, the WASPAS model was employed to rank all the alternatives involved in making an effective decision. This study aimed to develop a tool to enhance decision-making when solving fuzzy multi-criteria problems. We propose a real-world model for the effectiveness of the proposed model.

Wave energy in the UK: Current scope, challenges and prognostications

This paper reviews the current status, challenges and prognostications of wave energy systems (WES), which have momentous scope in the UK that could deliver the UK’s net zero energy target by 2050. In Britain, there are 43 primary seaside towns around the coast in which 37 are in England that encompass a collective population of 2.9 million and signify around 5.7 % of the population of England as a whole where the zero energy coastline house projects can be initiated with WES. The progress in the development of standalone WES for a vision of zero energy coastline houses is still in its initial stages. This paper exhibited a brief review of the onshore, nearshore and offshore WES technologies, particular focus was made to the scope in the UK. The feasibility and efficiency of WES study imply that the power take off (PTO) efficiency is crucially important as the overall output depends on the optimum energy harness from WES that will improve its competitive prowess with other renewable technologies and further reduce the cost of WES manufacturing. This study implicates one of prognostications that developing marine energy resources in the UK can save 60 metric tons of carbon dioxide by 2025. This study also concluded that WES can pose environmental challenges such as alterations of water column to biota and sea-bed habitats, dredging, noise and vibrations. The prognostication of zero energy coastline houses arises due to the location of the UK, which is one of the major determinants for the future success of wave energy projects, as the UK is located at the long fetch of the Atlantic Ocean and has the wind direction from the west. The available resource to harness wave energy in the UK is around 120 GW.

Wave energy converter physical model design and testing: The case of floating oscillating-water-columns

The quest for exploiting the ocean resources and understanding its behaviour has been a challenge with increasing needs for innovation and technology. Model testing is an essential step in offshore renewable energy technology development. It involves challenges that require experience and guidance. Costly mistakes might arise with the subsequent waste of time and resources. This paper presents the model design and testing processes as part of wave energy projects and the results of experimental testing of two types of oscillating-water-column (OWC) wave energy converters (WEC). The model design aims at the creation of a reduced-scale model to simulate the physical phenomena found in full-scale devices. It is a process that requires several skills and an adequate compromise among all variables. This design involves several approaches as different physical phenomena do not follow the same similarity conditions, requiring adjustments in scale, materials, and other relevant properties. Besides, the model testing process comprises the necessary planning and actions to execute the tests and post-processing of data. This process is addressed here through model design and testing of two WECs: the coaxial-duct and the spar-buoy OWCs. The configurations have been designed and studied for large-scale energy production and small-scale power in oceanographic applications. Although the devices are both OWCs, the designs exhibit significant differences. The development process of the models and results are presented for the two OWC devices. Free-decay tests, hydrodynamic performance and mooring tension results are presented and discussed. These may serve as guidelines and numerical modelling validation.

Dominant Wave Energy Systems and Conditional Wave Resource Characterization for Coastal Waters of the United States

Opportunities and constraints for wave energy conversion technologies and projects are evaluated by identifying and characterizing the dominant wave energy systems for United States (US) coastal waters using marginal and joint distributions of the wave energy in terms of the peak period, wave direction, and month. These distributions are computed using partitioned wave parameters generated from a 30 year WaveWatch III model hindcast, and regionally averaged to identify the dominant wave systems contributing to the total annual available energy ( A A E ) for eleven distinct US wave energy climate regions. These dominant wave systems are linked to the wind systems driving their generation and propagation. In addition, conditional resource parameters characterizing peak period spread, directional spread, and seasonal variability, which consider dependencies of the peak period, direction, and month, are introduced to augment characterization methods recommended by international standards. These conditional resource parameters reveal information that supports project planning, conceptual design, and operation and maintenance. The present study shows that wave energy resources for the United States are dominated by long-period North Pacific swells (Alaska, West Coast, Hawaii), short-period trade winds and nor’easter swells (East Coast, Puerto Rico), and wind seas (Gulf of Mexico). Seasonality, peak period spread, and directional spread of these dominant wave systems are characterized to assess regional opportunities and constraints for wave energy conversion technologies targeting the dominant wave systems.