Spectral wave modelling can reduce uncertainties in the estimation of wave energy resource assessment, converter design, extreme value analysis, etc. In spectral models, wave growth is represented with different approaches, resulting in wave resource assessments having large differences especially at high wave values. In this paper a modified version of the North Sea Wave Database is used to quantify the impact of wind temporal fidelity on the wind growth components. The Simulating WAves Nearshore (SWAN) model has been modified, with two different wind inputs used from the European Centre for Medium-Range Weather Forecasts (ECMWF). Results are compared with in-situ measurements an inter-comparison for 20 years (1980-1999). Differences are found on mean and maxima values of wave parameters, with little changes in directionality. However, higher temporal resolution of the wind does not mean always a better hindcast, in fact attention to the calibration of wind-wave growth interactions and whitecaps leads to similar results. Finally, the high fidelity hindcasts are compared, identifying limitations and opportunities for improvements in wave energy assessments.

Renewable energy offers significant opportunities for electricity diversification. South Africa belongs to the group of developing nations and encompasses a lot of potential for renewable energy developments. Currently, the majority of its electricity production originates from fossil fuels; however, incorporation of clean coal technologies will aid in reaching the assigned targets. This study offers a long-term wave power quantification analysis with a numerical wave model. The investigation includes long-term resource assessment in the region, variability, seasonal and monthly wave energy content. Locations with high-energy content but low variability pose an opportunity that can contribute in the alleviation of energy poverty. Application of wave converters depends on the combination of complex terms. The study presents resource levels and the joint distributions, which indicate suitability for converter selection. Depending on the region of interest, these characteristics change. Thus, this resource assessment adds knowledge on wave power and optimal consideration for wave energy applicability.

Significant advancements have been made in the past few decades (since the 1980s) on detailed evaluation and quantification of wave resources globally. Larger availability and advances of computational resources have contributed to the utilisation of numerical wave models as powerful tools in climatic and energy studies. This review presents current state-of-the-art numerical tools and their status in the process of wave power assessments. We focus on the evolution of studies undertaken at the European coastline regions and the Black Sea. Although, a number of studies have been successfully developed and implemented in the past contributing to our understanding of the resource, this paper discusses the benefits, limitations and potential for improvement of numerical tools. From the literature, it is evident that different applications and scale may require different models, however, it is also the experience and knowledge of the user, applied in the tuning of a number of parameters that govern the process of wave generation, propagation, and the quality of input parameters that are the cornerstones of a successful model. This review depicted that the use of numerical wave models, depending on specific region and application, offers significant benefits on quantification of coastal zone wave resources which benefit multiple offshore applications and the energy industry.

The study focuses around the energetic waters of Scotland that has expressed high interest in the development of wave energy farms. There are only a few long-term suitable studies characterising coastal locations. A detail coastal resource assessment is provided, focusing on wave energy and site characterisation. Mean nearshore energy content in the Western coasts is ≥50 kW/m and on the East ≈10 kW/m. Monthly and seasonal analyses outline available resource and annual variations. Availability of production is also examined, West coastlines present higher levels, however, depending on resource and wave converters operational range significant differences are shown. Availability levels on the East coastline are low ≈40% due to lower wave heights, while Western locations record consistently over 80% at both scenarios examined. Results discuss the potential applicability of favourable wave converters, and characteristics which achieve maximum utilisation based on the local environment.

The study uses a 35-year data set, which can be used to provide a long-term assessment for assessing wave power resources, availability for wave energy converters (WECs), and multithreshold accessibility suitable for numerous vessels and important for offshore maintenance operations. The data set demonstrates that winter months have harsher environmental conditions for the Western regions, such as the Spanish coastlines, and the Eastern regions, such as the Aegean Sea, record slightly higher waves during summer months. The data set also identifies the seasons with lower resources, which will have higher accessibility and will benefit offshore construction and maintenance operations for offshore energy activities. It has been shown that the availability for wave energy depends on the operational range of a particular type of WEC; hence, threshold selection affects the availability distribution more than accessibility. Availability varies per region, with Southern Aegean, Southern Italian, and North African coasts having higher monthly values. Accessibility in nearshore areas is constantly over 90%, with deeper waters presenting reduced levels. Statistical analysis performed for this work shows predictable availability due to lower maxima, potentially enhancing WECs operation; this, however, will depend on device properties. Furthermore, the resource analysis indicates that the dominantmetocean conditions yield low wave height range.

At autonomous electricity grids Renewable Energy (RE) contributes significantly to energy production. Offshore resources benefit from higher energy density, smaller visual impacts, and higher availability levels. Offshore locations at the West of Crete obtain wind availability ≈80%, combining this with the installation potential for large scale modern wind turbines (rated power) then expected annual benefits are immense. Temporal variability of production is a limiting factor for wider adaptation of large offshore farms. To this end multi-generation with wave energy can alleviate issues of non-generation for wind. Spatio-temporal correlation of wind and wave energy production exhibit that wind and wave hybrid stations can contribute significant amounts of clean energy, while at the same time reducing spatial constrains and public acceptance issues. Offshore technologies can be combined as co-located or not, altering contribution profiles of wave energy to non-operating wind turbine production. In this study a co-located option contributes up to 626 h per annum, while a non co-located solution is found to complement over 4000 h of a non-operative wind turbine. Findings indicate the opportunities associated not only in terms of capital expenditure reduction, but also in the ever important issue of renewable variability and grid stability.

The study focuses on a high resolution coastal assessment for the Libyan Sea at the South-West Mediterranean. To date majority of information for the area, are based on large scale oceanic models with coarse resolutions not adequate for nearshore assessments. This dataset and analysis provides an in-depth wave energy resource assessment and detail dissemination of sites according to their metocean characteristics. Identification for wave energy is based on the database constructed, allowing the quantification of energy levels and resource implications at sites. Mean values of wave heights around the coastlines are ≈1m, though high storm events exceed 5 m at several areas. Highest wave energy resources are located at open coastal areas, with energetic months reaching up to 10 kW/m. Low energy seasons are found throughout summer months, where energy content is reduced threefold. The resource can be classified as low, however the coefficient of variation suggests a predictable resource with extreme events not expected to surpass 10 m. Although, resource is not as energetic as open oceanic regions the low variations may assist wave energy as a supporting renewable energy option. Assessing the wave climate around the coasts for a long period of time can also provide confident and robust suggestions on the selection for wave energy converters. In addition, lower extreme events are expected to reduce potential installations costs by lowering structural expenditure and strengthening works to facilitate operation at milder environments.

Wave energy is expected to play an important role in the forthcoming years for the de-carbonisation of Scottish and British electricity production. This study underlines the importance of resource assessment and attempts to improve the quantifiable wave power resource, with use of a validated numerical model. While levels of wave flux are high for an area that may not always constitute the best option for wave energy applications. In this study, a long-term hindcast for the Scottish coastlines run from 2004 to 2014 (11 years) improving the existing wave maps and resource estimations. Spatial and physical considerations of a third generation spectral model allow examination at locations of immediate interest for the ocean energy community. Utilising numerical wave models of finer resolution allows for the detailed coupling of potential wave energy converters (WECs) and site characterization. Such detail energy results allow for improved financial analysis that take into account the severity of local resource and its energy potential.

The study enhances the coastal resource knowledge and discusses opportunities for wave energy in the Aegean Sea. A fine-resolution numerical wave model is utilised to provide results for the Greek coastal regions. The model ran for 35 years (1980–2014) estimating wave characteristics, and quantifying the wave energy potential in coastal areas. The results deliver the energy potential, variability, and site characterisation for the Aegean Sea. The dataset is coupled with wave energy converters power matrices to provide for the first time a long-term analysis of expected power production. Performance of devices is highly dependent on matching the power matrix to the local resource, suitable devices can obtain capacity factor up to 20% and favour operation for low wave heights and high frequencies. Based on energy analysis data, an economic performance and payback period of a hypothetical wave farm is examined. With little information on wave energy in the region, this preliminary cost-to-benefit analysis shows the viability of wave converters. Even with high capital expenditure associated with novel technologies, certain scenarios achieve amortization periods at 7.5 years for a properly selected converter. Results are comparable with previous renewable schemes aimed at increasing the cumulative installation of other early stage technologies.

Wind is the dominant process for wave generation. Detailed evaluation of metocean conditions strengthens our understanding of issues concerning potential offshore applications. However, the scarcity of buoys and high cost of monitoring systems pose a barrier to properly defining offshore conditions. Through use of numerical wave models, metocean conditions can be hindcasted and forecasted providing reliable characterisations. This study reports the sensitivity of wind inputs on a numerical wave model for the Scottish region. Two re-analysis wind datasets with different spatio-temporal characteristics are used, the ERA-Interim Re-Analysis and the CFSR-NCEP Re-Analysis dataset. Different wind products alter results, affecting the accuracy obtained. The scope of this study is to assess different available wind databases and provide information concerning the most appropriate wind dataset for the specific region, based on temporal, spatial and geographic terms for wave modelling and offshore applications. Both wind input datasets delivered results from the numerical wave model with good correlation. Wave results by the 1-h dataset have higher peaks and lower biases, in expense of a high scatter index. On the other hand, the 6-h dataset has lower scatter but higher biases. The study shows how wind dataset affects the numerical wave modelling performance, and that depending on location and study needs, different wind inputs should be considered.

Waves are characterised by high energy density content, able to provide significant renewable energy contribution. Identification of wave energy potential locations around Europe can provide significant benefits for application of wave energy converters (WECs). While the highest resources are placed in the open Atlantic coastlines of Europe that does not exclude the fact thatwave energy can provide significant contributions to the rest of Europe. To support such claims, a detail resource assessment has to be in place to characterize the resource. State of-the-art resource assessments provide a tool that can identify trends in the resource and proper evaluation of production, based on such long-term data allows robust financial and engineering decisions. In addition, the results can also be used for climate investigations, extreme value analysis, site characterization, and information concerning a variety of offshore activities. This study investigates the metocean conditions of the Mediterranean Sea and assesses the levels of energy around the Basin. Hidden opportunities lay in both energetic and milder wave environments with each having each own benefits and drawbacks, in terms of capital costs required and energy production. The results from the hindcast underwent a detailed annual, seasonal, and decadal analysis. Furthermore, potential benefits of wave energy converters (WECs), are assessed in terms of energy production, adaptability, and final considerations for site selection are discussed.

Wave energy sites around Scotland, are considered one of the most energetic waters, as they are exposed to the Atlantic Ocean. The amount of energy reaching the shoreline provides an opportunity for wave energy deployments.

Currently, considerations on wave devices expect them to be installed at nearshore locations. That means that the potential wave resource has to be investigated, since deep to shallow water interactions alter the shape of propagated waves. Resource assessment for these regions is essential in order to estimate the available and extractable energy resource. Although several numerical models exist for wave modelling, not all are suitable for nearshore applications.

For the present work, the nearshore wave model SWAN has been used to simulate waves for the Hebridean region. The set-up, calibration and validation of the model are discussed. The resulting wave conditions are compared with buoy measurements. Results indicate that the modelling technique performed well.