In this work, an extended overview of the marine renewable energy in the Mediterranean Sea is provided as regards current status, potential problems, challenges, and perspectives of development. An integrated and holistic approach is necessary for the economic viability and sustainability of marine renewable energy projects; this approach comprises three different frameworks, not always aligned, i.e., geotechnical/engineering, socio-economic, and environmental/ecological frameworks. In this context, the geomorphological, climatological, socio-economic, and environmental/ecological particularities of the Mediterranean basin are discussed, as they constitute key issues of the spatial context in which marine renewable energy projects are to be implemented. General guidelines for the sustainable development of marine renewable energy in the Mediterranean are also provided.

The investigation of wave climate is of primary concern for the successful implementation of offshore aquaculture systems as waves can cause significant loads on them. Up until now, site selection and design (or selection) of offshore cage system structures on extended sea areas do not seem to follow any specific guidelines. This paper presents a novel methodology for the identification of favorable sites for offshore aquaculture development in an extended sea area based on two important technical factors: (i) the detailed characterization of the wave climate, and (ii) the water depth. Long-term statistics of the significant wave height, peak wave period, and wave steepness are estimated on an annual and monthly temporal scale, along with variability measures. Extreme value analysis is applied to estimate the design values and associated return periods of the significant wave height; structures should be designed based on this data, to avoid partial or total failure. The Eastern Mediterranean Sea is selected as a case study, and long-term time series of wave spectral parameters from the ERA5 dataset are utilized. Based on the obtained results, the most favorable areas for offshore aquaculture installations have been identified.

One preliminary key step for developing an offshore wind farm is identifying favorable sites. The process of sitting involves multiple requirements and constraints, and therefore, its feasible implementation requires either approximating assumptions or an optimization method that is capable of handling non-linear relationships and heterogeneous factors. A new optimization method is proposed to address this problem that efficiently and accurately combines essential technical criteria, such as wind speed, water depth, and distance from shore, to identify favorable areas for offshore wind farm development through a user-friendly data-driven tool. Appropriate ranks and weighting factors are carefully selected to obtain realistic results. The proposed methodology is applied in the central Aegean Sea, which has a high offshore wind energy potential. The application of the proposed optimization method reveals large areas suitable for developing floating wind energy structures. The algorithm matches the accuracy of the exhaustive search method. It, therefore, produces the optimum outcome, however, at a lower computational expense demonstrating the proposed method’s potential for larger spatial-scale analysis and use as a decision support tool.

In the context of wave resource assessment, the description of wave climate is usually confined to significant wave height and energy period. However, the accurate joint description of both linear and directional wave energy characteristics is essential for the proper and detailed optimization of wave energy converters. In this work, the joint probabilistic description of wave energy flux and wave direction is performed and evaluated. Parametric univariate models are implemented for the description of wave energy flux and wave direction. For wave energy flux, conventional, and mixture distributions are examined while for wave direction proven and efficient finite mixtures of von Mises distributions are used. The bivariate modelling is based on the implementation of the Johnson–Wehrly model. The examined models are applied on long-term measured wave data at three offshore locations in Greece and hindcast numerical wave model data at three locations in the western Mediterranean, the North Sea, and the North Atlantic Ocean. A global criterion that combines five individual goodness-of-fit criteria into a single expression is used to evaluate the performance of bivariate models. From the optimum bivariate model, the expected wave energy flux as function of wave direction and the distribution of wave energy flux for the mean and most probable wave directions are also obtained.

A wide range of wave energy applications relies on the accurate estimation of extreme wave conditions, while some of them are frequently affected by directionality. For example, attenuators and terminators are the most common types of wave energy converters whose performance is highly influenced by their orientation with respect to the prevailing wave direction. In this work, four locations in the eastern Mediterranean Sea are selected with relatively high wave energy flux values and extreme wave heights are examined with wave direction as a covariate. The Generalized Pareto distribution is used to model the extreme values of wave height over a pre-defined threshold, with its parameters being expressed as a function of wave direction through Fourier series expansion. In order to be consistent with the analysis obtained from the independent fits for directional sectors, the estimation of parameters is based on a penalized maximum likelihood criterion that ensures a good agreement between the two approaches. The obtained results validate the integration of directionality in extreme value models for the examined locations and design values of significant wave height are provided with respect to direction for the 50- and 100-year return period with bootstrap confidence intervals.

For coastal engineering studies and the efficient design of ports and harbors, reliable information concerning wave conditions in nearshore and coastal sites is needed. In the absence of long-term wave data at the site of interest, this becomes possible by using offshore data, which are usually available in the nearby geographical area, in addition to bathymetric and coastline information concerning the nearshore area and the local site. The latter are used in conjunction with a suitable wave model, which calculates the offshore-to-nearshore transformation of wave conditions and incorporates the relevant shallow-water phenomena. In the present work, the above methodology is applied to calculate the nearshore wave conditions in the Bay of Sitia, Crete, by applying the Simulating WAves Nearshore (SWAN) model. The interesting feature of the Bay of Sitia is its vulnerability due to strong erosion, which downgrades the touristic value of the beach. Furthermore, nearshore wave data offer valuable information concerning further coastal and port engineering studies. In this context, results from directional extreme value analysis of the nearshore wave conditions in the Sitia Bay are derived and used to investigate resonances in the enclosed marina of the Sitia port, by taking into account the depth variations inside the basin. To this end, a novel method was developed based on the modified mild-slope equation, in conjunction with the Finite Element Model, for the solution of the nonlinear eigenvalue problem.