Assessment of the potential for developing combined wind-wave projects in the European nearshore

Abstract

The objective of this work is to assess the synergy of the marine resources in the vicinity of several European offshore sites, in order to analyze the viability of the combined wind-wave renewable projects. The reference sites considered for evaluation are located in the vicinity of the European coasts, being already taken into account for various marine projects. As a first step, based on the dataset provided by the European Center for Medium-Range Weather Forecasts for the 10-year interval 2005–2014, it was possible to analyze the joint seasonal distribution of the offshore resources. In the second part of the paper, based on the technical characteristics of various offshore wind turbines and wave energy converters, it was possible to identify the performances of some systems for wind and wave energy conversion. Finally, it can be also highlighted that the results presented in the present work can be considered interesting and useful, since they provide some insights regarding the potential of some operational European sites to support colocated wind-wave projects.

Keywords

Ocean power European nearshore wind speed significant wave height synergy wind waves

Introduction

According to the present European Union policy, it can be expected that until 2050 almost 50% of the electricity generation will come from the marine renewable sources. This can be considered an optimistic plan, which takes into account the following milestones: an annual production of 563 TW h obtained from the offshore wind¹ and an output of 146 TW h generated from the sea waves until 2040.^2,3 At this moment, the offshore wind industry stands out with an impressive evolution, which for the European market started in 1993 from 6 MW, reaching at the end of 2015 a cumulative capacity of 11,027 MW. In the near future, it can be expected that this growth will follow a similar pattern since there are already taken into account new solutions, such as wind turbines with larger rotors, deep water sites, or floating platforms. At this moment, a total number of 80 fully operating projects are reported at a European level,⁴ from which it can be mentioned in the first place UK with 27 projects (5061 MW—45.9% of all installations), followed by Germany—18 projects (3295 MW) or Denmark—13 projects (1271 MW). Usually, the sites located close to the ocean are considered to be more suitable for such projects. Nevertheless, during the recent years, it has been highlighted that the enclosed or semienclosed seas may present also some attractive hot-spot areas, more promising results being reported for the Mediterranean Sea.^5–7

Among all the resources available in the marine environment, the wave energy is characterized by the highest energy density. It can be added to this the fact that the wave energy converters (WECs) seem to present a lower negative environmental impact, especially in the case of the offshore devices. Besides these, it is estimated that the wave generators can produce electricity for up to 90% of the time, compared to the solar and wind systems, where this value is around 25%.^8,9 Moreover, the potential of this natural source is the most significant, if we take into account that approximately 2% from the world’s coastlines (800,000 km) are characterized by a wave power which frequently exceeds the value of 30 kW/m.^10–13

The idea of extracting energy from the sea is not new, the first patent being registered in 1799 by Girard and his son. This represents the starting point of a dynamical industry, including thousands of concepts. The number of WECs tested at this moment is impressive, being reported performances at various levels. Even so, there is no clear solution for what will be the best technical approach for harnessing the wave power. This is due to the fact that these systems can be deployed either offshore or nearshore, while each geographical region is defined by a specific wave energy potential, which means that these systems need to be tuned in order to obtain optimal performances. Most of the current wave generators are developed in the UK. Nonetheless, there is a constant interest also from some other countries such as Israel, Norway, Denmark, Finland, Canada, Sweden, Portugal, China, Japan, Spain, Chile, or Australia.¹⁴

In order to reduce the intermittence of the wind and wave resources regardless of the time interval, a viable solution will be to take into account combined wind-wave projects,^15–17 increasing in this way the attractiveness of a site in terms of its overall marine energy potential.¹⁸ Thus, it is possible to extract two energy sources from a single site,¹⁹ which will lead to a better use of the marine areas that although are defined by vast spaces, they can be quite limited in the vicinity of the coastlines due to the existence of different restrictions, such as shipping routes or natural reservations.^20,21 Furthermore, since the wind energy is more developed, it is possible to adjust the infrastructure of an offshore project in order to include a wave farm. Such approach will be reflected also by a lower investment,^22,23 increasing in this way the chances for success of the wave generators, which are still considered an immature technology. Moreover, since WECs will extract the energy from waves, the tower of the wind turbine will be better protected, especially against of the wave fatigue loads.^24–27 At this moment, we can discuss about a network of European offshore wind farms, each site being defined by a particular wave energy potential, which can be efficiently converted into electricity or for desalination power stations.

Usually, the coastal areas defined by a certain energy potential are also associated with problems caused by the erosion processes.²⁸ From this perspective, throughout a combined wind-wave project, it is also possible to reduce these negative effects.²⁹ Such a concept, which involves WEC systems was already proposed for the Portuguese nearshore,^30,31 which is directly under the influences of the North Atlantic waves and also for some enclosed seas such as the Mediterranean Sea (ex: Sardinia Island), or the Black Sea, where a special attention was paid to the Romanian coastal environment.^32,33

In this context, the objective of the present work is to investigate the wave energy potential in several European marine sites, which are usually known for the performances of the local wind farms, in order to indicate which of them will be more suitable for a joint wind-wave project. Thus, the proposed work provides a better picture related to the possibility of combining the wind and wave energy resources. From this perspective, a first step would be to colocate wave farms, up wave some of the existing wind farms, where this is appropriate. In this way, besides producing energy they will provide a sheltering effect to the wind farms. Moreover, the results presented in this work might be also helpful in the further step in the effort to combine the wind-wave resources that consists in the development and the implementation of some hybrid wind-wave energy projects.

An outline of the following sections is given next. Thus, by using the reanalyzed wind and wave data coming from the European Centre for Medium-Range Weather Forecasts, it was assessed the renewable potential in several European sites, where some projects are already operating. These are mainly offshore wind farms. Furthermore, this will allow also to evaluate if these sites could be efficiently used to support combined wind-wave projects. Besides a description of the target areas, of the methods and datasets considered, the performances of several wind and wave generators are also discussed. This is done by considering some state-of-the-art technologies, which currently operate in various parts of the world. Finally, it can be also mentioned that the results presented in this work could provide a better insight to the European renewable market and also to highlight which coastal environment is more suitable for a combined marine project.

Methods and materials

The target areas

In Figure 1 the reference sites considered in the present work are presented. These were grouped into three target areas (denoted as A, B, and C). The first area is defined by the North Sea basin, for which there were considered six sites from UK, Germany, and Norway, respectively. A group of other six sites was defined in the vicinity of the coastlines facing the North Atlantic Ocean, being expected from their locations to present more significant wind and wave energy resources.^34,35 A particular site was selected close to the Canary Islands, which, although representing a Spanish territory, is located far in the south, exceeding the geographical borders of Europe. This reference point will be used to highlight the energetic potential of an island, which in fact, represents one of the first obstacles encountered by the waves in their way to the shallow water areas.^36,37 Going to a milder wave climate, in the Mediterranean Sea, it was selected a point close to the France border, in order to assess also the potential of the natural resources in this environment.^38–40

Figure 1.

Locations of the marine reference sites considered for various European renewable energy projects, where the points are identified throughout three target areas (A, B, and C). Figures processed from Google Earth (2016).

It is important to mention that all the sites taken into account are currently considered for various renewable projects. Some of them, such as Hywind (Norway), Floatgen and InFLOW (both in France) are used as research centers for various prototypes, such as the testing of floating wind turbine platforms.^41,42 Other projects are more mature, as in the case of Gode Wind 1 and 2, which with a project capacity of 582 MW represents the most important site considered for evaluation.⁴³ In terms of the water depths, the values are varying in the range 1.8–220 m, the greater depth values being reported by the Hywind, InFLOW and WindFloat (Portugal) projects. Regarding the distance to the shore, measured from the center of each project, it can be mentioned a maximum of 50 km for InFLOW, 45 km for Gode Wind, and a 30 km for Horns Rev 3 (Denmark).⁴¹

All the projects considered focus on the offshore wind turbine systems, none of them being currently involved in the development of a WEC. However, they might be considered also suitable for the implementation of a colocated project, taking into account that the infrastructure and the logistic support required for such a project are already there.

The ECMWF dataset

The European Center for Medium-Range Weather Forecasts (denoted also as ECMWF) is considered to be one of the most important research centers focused on the prediction of various meteorological parameters, including those that are more significant for the marine environment. As most of the meteorological centers, the products are obtained throughout a data assimilation scheme which involves a four-dimensional variational system (4D-Var), for each day being processed a number of about 30 million observations coming from satellites or from ground stations.⁴⁴

The European Centre for Medium-Range Weather Forecasts maintains various global reanalysis datasets, among them the ERA-Interim project is included. This was considered in the present work. As a general presentation, this dataset covers the time interval January 1979–present and provides marine parameters on different spatial resolutions which may vary between 0.125° × 0.125° and 3° × 3°, for this study being processed several NetCDF files (wind and waves) defined by a grid of 0.75° × 0.75°. The core of this project is represented by the assimilation system based on a 12 h 4D-Var of the upper-air atmospheric state, which replaces the previous 6 h 3D variational analysis scheme used for the ERA-40 project. In general lines, this is based on the following minimization scheme⁴⁵

J (x, β) = (x^{b} - x)^{T} B_{x}^{- 1} (x^{b} - x) + (β^{b} - β)^{T} B_{β}^{- 1} (β^{b} - β) + [y - h (x, β)]^{T} R^{- 1} [y - h (x, β)]

(1)

where

x, β

represent the control variables;

B_{x}, B_{β}

are the covariances of errors in the background estimates; R is the covariances of errors in the observations;

x^{b}

is the background state estimate;

β^{b}

is the background estimates for the bias parameters; and

h (x, β)

is the observation operator.

Almost 98% of the assimilated data are coming from satellites, which in the case of the wind parameter belong to the missions Geo/MODIS, SSM/I, ERS, or QuikScat, respectively. The wind conditions are defined at a 10 m height above the sea level, being computed at every 6 h from 72 to 240 h with a high resolution forecast model, which takes into account a land sea mask. For the wave conditions, the ECMWF predictions are based on the WAM (Wave Model) model, which run on a global scale throughout a computational grid of 0.36° × 0.36°. The wave model is based on a wave spectrum defined by 30 frequency bins and 24 directions, respectively. The WAM model is also implemented on a local scale, for regions from North Atlantic, North Sea or Black Sea, where the spatial resolution is higher (0.25° × 0.25°), the advantage of this version is that it takes into account the shallow water effects.⁴⁶

The WAM model is a third generation wave model capable to solve the energy balance equation in spherical coordinates, as follows⁴⁷

\frac{\partial}{\partial t} F + (\cos ϕ)^{- 1} \frac{\partial}{\partial ϕ} (\overset{\cdot}{ϕ} \cos ϕ F) + \frac{\partial}{\partial λ} (\overset{\cdot}{λ} F) + \frac{\partial}{\partial ω} (\overset{\cdot}{ω} F) + \frac{\partial}{\partial θ} (\overset{\cdot}{θ} F) = S

(2)

where t is the time; F is the energy density spectrum;

ϕ, λ

are the latitude and longitude; ω is the angular frequency; θ is the wave direction; and S is the source term which represents the sum of wind input, wave–wave interactions, wave dissipation due to bottom friction, and whitecapping.

In the assimilation process the wave data are generated in two steps. The first one involves the generation of a significant wave height field (H) obtained through optimal interpolation^48,49

H_{i}^{a} = H_{i}^{f} + \sum_{j = 1}^{n_{obs}} W_{ij} (H_{j}^{o} - H_{j}^{f})

(3)

where

H^{o}

is the significant wave height field indicated by the altimeter and

H^{f}

is the first-guess wave field generated by the WAM model. This information is used in the second step to obtain a 2D wave spectrum, which is considered to be a wind sea spectra if the wind sea energy is larger than 3/4 times the total energy, or as swell. The 2D wave spectrum

F^{a} (f, θ, x, t)

is based on the first-guess wave spectrum

F^{f} (f, θ, x, t)

plus the optimal interpolation of the wave height

H_{^{i}}^{a}

by adjusting the spectrum with two scale parameters (A and B)⁴⁹

F^{a} (f, θ) = {AF}^{f} (Bf, θ)

(4)

In the present work, the wind and wave conditions were processed for the 10-year time interval January 2005–December 2014, considering daily values reported four times per day (at 00, 06, 12, and 18 UTC). The wind dataset related to the 10 m height above the sea level will be denoted as U10, being defined by wind speed and direction, while for the wave conditions, there were considered for evaluation the parameters significant wave height (Hs in meters), wave period (Tm₋_1,0 in seconds, also known as Te), and mean wave direction (in degrees).

Results

Analysis of the wind and wave conditions

Figure 2 presents the distribution of the wind and wave resources (mean values) in the vicinity of the selected sites. In Figure 2(a) it can be observed the variation of the parameter U10, from the highest (8.26 m/s) to the lowest value (3.2 m/s), from which it can be mentioned the site BALNEA which reports much lower values, compared to the rest of the reference sites. In terms of the wind conditions, more important values are noticed for the locations Gode Wind-Horns Rev 3 (8.26–7.8 m/s), being followed by the projects Greater Gabbard-Plocan (6.95–6.45 m/s) and finally by the sites WindFloat-Floatgen (6.12–5.89 m/s). In Figure 2(b), it is illustrated the distribution of the wind conditions focused only for the most energetic sites (the first five projects), the results being structured on summer and winter time periods, respectively, where the winter time is defined as being the interval October–March while the summer time is the rest.

Figure 2.

Mean values of the parameters considered for analysis: (a) and (c) U10 and Hs corresponding to the total time; (b) and (d) U10 and Hs corresponding to the summer and winter time, respectively.

Going to the wave conditions, from the distribution of the Hs parameter, there can be identified three reference groups: (a) Sceirde-Wave Hub (2.44–2.08 m); (b) Floatgen-Horns Rev 3 (1.8–1.23 m); (c) Greater Gabbard-InFLOW (0.96–0.46 m). Regarding the summer/winter distribution of the Hs values (Figure 2(c)) it can be observed that during the winter time the values reported are more consistent. From the category of the most energetic sites, it can be noticed that only the projects Gode Wind, Wave Hub, and Sceirde seem to present more important resources in terms of wind and wave energy potential.

A detailed description of the wind energy potential is presented in Table 1 for the most energetic sites, the results being structured for the total time (TT), summer time (ST), and winter time (WT), respectively. Based on the results for the total time interval, it can be mentioned that the Gode Wind project presents more wind resources, defined by an average value of 8.26 m/s, on the second place being placed the sites Sceirde and Wave Hub with a value close to 7.92 m/s while less energetic wind conditions are noticed close to the Hywind project (6.94 m/s). As expected, the maximum values of the wind conditions (U10–max) occur during the winter time, from which it can be mentioned the Sceirde site, where a 27.61 m/s was registered. The wind direction represents another important criteria for any renewable project, so that from the sites analyzed it can be noticed that most of the values are in the southwest sector, more precisely corresponding to the interval 199.2°–222.9°.

Table 1.

Characteristics of the wind conditions (at 10 m height) as resulted from the analysis of the ECMWF data, corresponding to some representative sites.

Site	Interval	U10 (m/s)	U10–max (m/s)	Dir (°)	Pwind (kW/m²)	Pwind–max (kW/m²)
Hywind	TT	6.94	22.04	211.3	0.39	6.56
	ST	5.93	17.25	222.9	0.23	3.14
	WT	8	22.04	199.2	0.55	6.55
Horns Rev 3	TT	7.67	22.88	208.8	0.45	7.34
	ST	6.7	18.74	218.0	0.29	4.03
	WT	8.69	22.88	199.2	0.62	7.34
Gode Wind	TT	8.26	24.3	210.1	0.56	8.79
	ST	7.15	19.6	218.3	0.35	4.63
	WT	9.42	24.3	201.7	0.77	8.79
Wave Hub	TT	7.91	23.09	205.1	0.51	7.54
	ST	6.81	22.36	209.2	0.32	6.85
	WT	9.05	23.09	200.9	0.71	7.54
Sceirde	TT	7.93	27.61	207.8	0.52	12.89
	ST	6.97	22.5	208.0	0.34	6.97
	WT	8.93	27.61	207.6	0.70	12.89

AWS: Archimedes wave swing; ECMWF: European Center for Medium-Range Weather Forecasts; OWC: oscillating water column; ST: summer time; TT: total time; WT: winter time.

The amount of energy concentrated in the air flow of a specific site, can be identified throughout the power density index (Pwind—in kW/m²), which is defined as⁶

P_{wind} = \frac{1}{2} ρ U_{10}^{3}

(5)

where ρ is the air density (1.22 kg/m³). In terms of this index, the reference sites present values in the ranges: 0.23–0.55 kW/m² → Hywind, 0.29–0.62 kW/m² → Horns Rev 3, 0.35–0.77 kW/m² → Gode Wind, 0.32–0.71 kW/m² → Wave Hub, 0.34–0.7 kW/m² → Sceirde.

Going to the wave statistics, a detailed representation of the local conditions is presented in Table 2 for five reference sites considered to be more energetic. The Sceirde site stands out with more impressive values, reporting an average of 1.84 m during the summer time and a maximum Hs of 11.68 m during the winter season. From this perspective, Gode Wind seems to present a moderate wave potential, which is defined by an average value of 1.68 m (total time) and a maximum Hs of 9.16 m, for the winter time. Regarding the wave period (Te), it can be mentioned that the average values are located in the interval 1.36–3.03 s, much higher values being encountered for the Sceirde site, where a maximum of 11.68 s is noticed during the winter. Similar to the wind conditions, the amount of energy carried out by the waves can be expressed as⁵⁰

P_{wave} = \frac{ρ g^{2}}{64 π} T_{e} H_{s}^{2}

(6)

where P_wave represents the energy flux in kW/m, ρ is the density of the sea water (1025 kg/m³), and g is the acceleration of gravity (9.8 m/s²). Following these values, it can be mentioned that during the total time the mean values may reach: 14.36 kW/m—Sceirde, 9.12 kW/m—Wave Hub, 8.97 kW/m—WindFloat, 6.38 kW/m—Floatgen, and 5.33 kW/m—Gode Wind.

Table 2.

Characteristics of the wave conditions as reflected by the ECMWF data for some energetic sites.

Site	Interval	Hs (m)	Hs—max (m)	Te (s)	Te—max (s)	Pwave (kW/m)	Pwave—max (kW/m)
Gode Wind	TT	1.68	9.16	1.68	9.16	5.33	368.1
	ST	1.29	5.46	1.29	5.46	2.22	77.95
	WT	2.1	9.16	2.08	9.16	8.56	368.1
Wave Hub	TT	2.08	9.94	2.08	9.94	9.12	470.3
	ST	1.58	6.18	1.58	6.18	3.35	113
	WT	2.59	9.94	2.59	9.94	15.13	470.3
Sceirde	TT	2.42	11.68	2.42	11.68	14.36	763.1
	ST	1.84	7.51	1.84	7.51	5.27	202.8
	WT	3.03	11.68	3.03	11.68	23.8	763.1
Floatgen	TT	1.8	8.81	1.8	8.81	6.38	327.5
	ST	1.36	5.97	1.36	5.97	2.28	101.9
	WT	2.25	8.81	2.25	8.81	10.66	327.5
WindFloat	TT	2.17	8.15	2.17	8.15	8.97	259.2
	ST	1.68	5.19	1.69	5.19	3.31	66.95
	WT	2.67	8.15	2.67	8.15	14.85	259.2

ECMWF: European Center for Medium-Range Weather Forecasts; ST: summer time; TT: total time; WT: winter time.

One way to assess the power smoothing of a particular site, which can be obtained from different natural resources, is throughout the total harmonic distortion (THD)²¹ which can be expressed as

THD = \frac{σ}{\bar{x}}

(7)

where σ stands for the standard deviation of the parameter and

\bar{x}

represents the average value of the parameter that is the power output of the wind (Pwind) or alternatively the wave power (Pwave), being also possible to define a mixed THD which combines the wind and the wave power (Pwind + Pwave). Usually, a lower value of this index is associated with better results.

Figure 3 presents the THD index taking into account all the reference sites. Following these results, it can be mentioned that the THD wind presents values in the range 1.01–2.27, THD wave is defined by values in the range 0.85–1.87, while THD mixed is in the range 0.85–1.7. It can be also mentioned that the evolution of the index THD mixed is similar to the distribution of the wind values, excepting for the site InFLOW. The good agreement between the wind and the wave energy resources seems to be reported close to Hywind, Teesside, Aberdeen, Floatgen, while from this point of view the project PLOCAN seems to represent the best solution for a colocated wind-wave project, since it shows much lower value of the THD indices (THD wind = 1.01; THD wave = 0.85; THD mixed = 0.86). Also the site WindFloat may be considered an option for such a project since it presents much lower value than the group sites Hywind-BALEA, reaching a minimum of 1.32 for THD wave and THD mixed, respectively.

Figure 3.

Distribution of the total harmonic distortion (THD) indicator used to describe the normalized power of wind (Pwind), wave (Pwave), and mixed (wind + wave power).

Since the objective of the present work is to assess the combined wind and wave potential for a particular site, Figure 4 illustrates an analysis of the THD mixed reported to an interannual level. By analyzing the points from the area A, it can be mentioned that the projects Gode Wind and Horns Rev 3 present much higher fluctuations, reaching a maximum value of 1.72 in 2013. In general, the interval 2006–2011 can be considered a suitable period for the renewable projects, being reported much lower THD values which may reach 1.22 near the Aberdeen project in 2009. From the Area B (Figure 4(b)), most of the sites follow a similar interannual pattern, indicating a maximum value of 1.9 for 2014. Going to the points from Area C, it can be mentioned that the site PLOCAN presents much lower value (0.68–0.99), compared to InFLOW where a maximum of 1.83 is related to the year 2012.

Figure 4.

Interannual variations of the mixed THD (wind and wave power) evaluated for: (a) area A, (b) area B, (c) area C. THD: total harmonic distortion.

Performance evaluation of the wind and wave generators

Since the natural resources and the performances of the wind and wave generators are usually going hand in hand, in this section will be briefly assessed their performances for the selected sites. Usually, the power output of the wind turbine is influenced by the cut-in limit from which the system will start to produce energy, most of the offshore turbines being defined by values of 3, 3.5, or 4 m/s.⁴¹ Based on these values, in Figure 5 it was represented the amount of time (in %) during which a wind turbine will not operate. Most of the sites present values which do not exceed 20% in the case of the 3 and 3.5 m/s cut-in indicators, and maximum 30% for the 4 m/s index. The site BALEA stands out with an impressive percentage of inactivity, which may register a maximum of 76.35%. As expected, the cut-in value of 3 m/s presents much lower percentages, indicating a minimum of 6.2% in Gode Wind and a maximum of 54.1% near the Balea site.

Figure 5.

Identification of the time interval (in %) during which a generic wind turbine will not operate. The results are based on the percentage reported below the common cut-in values (3, 3.5, and 4 m/s, respectively).

Figure 6 illustrates the monthly distribution of the time interval (in %) during which a wind turbine with a 3.5 m/s cut-in value will not operate, being expected that other types of turbines with different cut-in limits to present also results around these values. During the summer time the sites from Area A present much higher value, which may reach a maximum of 40.1% for the Teesside during June, while for the same month a minimum of 15.58% is accounted by the Gode Wind project. From this point of view, Gode Wind and the Horns Rev 3 seem to present lower fluctuations, which usually do not exceed 17%. From the projects considered in Area B (Figure 6(b)), it can be noticed a significant discrepancy between the site BALEA, which presents a higher percentage and the rest of the sites. In this case, the BALEA project presents values in the range 52.2–81.6%, compared to the more promising sites, such as Wave Hub and Sceirde, where a maximum of 19.5% is reported during the summer time. From the points located in Area C, it can be mentioned that the site PLOCAN presents during the summer time lower values, which can reach a minimum of 2.1% in July and August, compared to the winter season when a maximum of 22.13% is encountered in October. In Table 3 it is presented a similar analysis taking into account this time the three time intervals considered before (TT, ST, and WT).

Figure 6.

Monthly distribution of the time interval (in %) during which a wind turbine will not operate, considering 3.5 m/s as the cut-in value. Results evaluated for: (a) area A, (b) area B, and (c) area C.

Table 3.

Estimation of the time percentage during which a wind turbine will not operate. The results are based on the cut-in limit of 3.5 m/s, and they are reported for the total (TT), summer (ST) and winter time (WT), respectively.

Site
	Hywind	Horns Rev 3	Gode Wind	Greater Gabbard	Teesside	Aberdeen	Wave Hub
TT	18.59	10.76	8.938	16.08	22.88	17.9	10.33
ST	23.04	13.85	11.71	21.51	28.65	24.03	14.08
WT	13.96	7.543	6.055	10.42	16.88	11.53	6.416

→	Sceirde	Floatgen	Oleron	InFLOW	BALEA	PLOCAN	WindFloat
TT	11.13	20.66	18.36	25.9	66.76	12.66	21.17
WT	14.44	24.61	22.53	31.82	73.81	9.208	22.47
ST	7.688	16.55	14.02	19.74	59.42	16.24	19.81

The performances of the WEC generators are also evaluated by taking into account the cut-in and cut-out values extracted from the power matrices of some common wave converters,⁵¹ such as a WEC of Oscillating water column type (OWC) → 0.5–5.5 m, Archimedes Wave Swing (AWS) → 1–6.5 m, and Pelamis → 1–8 m. At this point, it is important to mention that in this study the generator associated with the OWC system consists of a single unit defined by a single chamber of 4 m width and a rated power of 250 kW, which is related to a renewable project proposed to be built in front of the main breakwater of the port A Guarda (NW Spain).^51,52

In Figure 7, it is illustrated the time interval (in %) during which the selected WECs will not operate. Based on these results, it can be noticed that AWS and Pelamis present an identical pattern from which it can be assumed that these types of systems will perform better in the vicinity of the sites Wave Hub, Sceirde, PLOCAN, or WindFloat. Regarding the OWC generator, it can be noticed that such a system will perform well in all the reference sites, excepting the projects Greater Gabbard (20.7%), Teesside (26.25%), and InFLOW (64.9%). Table 4 presents a similar analysis for the WEC systems, considering this time only the OWC and AWS systems (presented with bold values), where the results are structured in total, summer and winter time intervals, respectively. From these values, it can be highlighted the site Inflow, which from the sites located in Area B presents significantly higher values that can reach a maximum of 95% during the winter time for an AWS system. This suggests that such a system will not perform well in an enclosed sea, such as the Mediterranean or the Black Sea.

Figure 7.

Estimation of the time interval during which some commercial WEC systems (OWC, AWS, and Pelamis) will not operate. The results are based on the Hs values below the cut-in and higher than the cut-out values, as indicated by the manufacturer in the power matrix of each device.

Table 4.

Estimation of the time percentage during which a WEC system will not operate. The results are based on the Hs values (cut-in and cut-out limits) as resulted from the power matrices of the OWC and AWS systems (bolded results).

Site
	Hywind	Horns Rev 3	Gode Wind	Greater Gabbard	Teesside	Aberdeen	Wave Hub
TT	4.48	11.37	4.23	20.69	26.25	3.87	1.7
TT	33.87	46.57	27.59	61.93	73.1	33.48	11.81
ST	7.94	18.88	6.67	29.47	40.1	6.82	0.5
ST	52.22	63.01	41.21	75.44	89.11	52.1	19.83
WT	0.88	3.57	1.70	11.55	11.85	0.81	2.95
WT	14.78	29.45	13.42	47.86	56.45	14.12	3.47

→	Sceirde	Floatgen	Oleron	InFLOW	BALEA	PLOCAN	WindFloat
TT	3.39	1.65	1.43	64.9	1.636	0	1.23
TT	7.95	20.52	24.96	90.82	28.58	5.09	5.71
WT	0.48	1.56	2.19	76.54	2.347	0	0.04
WT	11.9	31.9	37.44	95.46	43.83	7.20	9.08
ST	6.41	1.74	0.63	52.79	0.89	0	2.48
ST	3.84	8.67	11.97	86	12.7	2.90	2.21

AWS: Archimedes wave swing; OWC: oscillating water column; ST: summer time; TT: total time; WT: winter time.

The monthly performances of the WEC systems are presented in Figure 8, where however the Pelamis system was not taken into account since it will report similar performances as the AWS system. In this case the results are also indicated in terms of the nonactivity index. Regarding the OWC system, it can be noticed that in Area A lower performances can be expected during the summer time, compared to region B, where the site Sceirde presents higher values during the wintertime (close to 12%). Teesside presents a maximum of 52% during July, compared to Hywind, Gode Wind, and Aberdeen, which usually have lower values. Regarding the AWS system, it can be observed that the values reported in the case of Greater Gabbard and Teesside increase in magnitude reaching this time a maximum of 94.4% (in July) and a minimum of 46.3% in January. Going to Area B, the values are gradually increasing during the interval January–April, reaching a maximum in the interval June–July (BALEA—55.1%), and gradually decreasing to a 3.5% in December (Wave Hub site).

Figure 8.

Monthly distribution of the time interval (in %) during which the OWC and AWS devices will not operate, reported for the areas A and B.

Conclusions

In the present work, the wind and wave energy potential were assessed for several offshore European sites already involved in renewable projects, in order to establish which of them are more suitable for a combined wind-wave project. In most of the selected sites, offshore wind turbines already operate, a fact that makes them more suitable for the implementation of a wave farm project since the infrastructure is already there. From the analysis of the U10 index, it can be mentioned that the sites Gode Wind, Sceirde, Wave Hub, and Horns Rev 3 seem to present more consistent values, compared to the Hs index where the sites Sceirde, WindFloat, and Wave Hub are more relevant.

Regarding the performances of a generic wind turbine, it was noticed that lower performances will be expected in the vicinity of the BALEA site, which operates in the northern coast of Spain. From this perspective, the sites defined in Area C present a different pattern in the sense that the point PLOCAN located close to the Canary Islands has more important wind resources, compared to InFLOW (Mediterranean Sea), where a maximum of 40% can be noticed during the summer time. For the WEC systems, it was noticed that better results are obtained throughout the OWC systems, regardless of the area taken into account, with the mention that the site Plocan presents a 100% activity for this type of generator.

The results presented in this work can be considered interesting and of direct practical use, since they bring into discussion the viability of an offshore site for the combined wind-wave projects, indicating at the same time some potential sites, which is not worthwhile to be taken into account for such a renewable project.

Footnotes

Acknowledgements

The ERA-Interim data used in this study have been obtained from the ECMWF data server.

Declaration of conflicting interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work was carried out in the framework of the project proposal REMARC, submitted under the number PN-III-P4-IDPCE-2016-0017 to the Romanian Executive Agency for Higher Education, Research, Development and Innovation Funding, UEFISCDI. The ERA-Interim data used in this study have been obtained from the ECMWF data server.

Florin Onea earned his PhD in the field of Mechanical Engineering in 2013. The scientific researches carried out by him can be included in the current trends of implementing technologies which use natural resources from the marine areas, a particular attention being given to the European environment. He works as an assistant professor at the Faculty of Engineering, University ‘Dunarea de Jos’ of Galati, Romania.

Sorin Ciortan earned his PhD in the field of Mechanical Engineering in 2000. His research interests are mainly concerned with renewable energy problems and also applications of the neural networks in engineering problems. He is currently Head of Department of Mechanical Engineering in Galati University, ‘Dunarea de Jos’.

Eugen Rusu earned his PhD in the field of Mechanical Engineering in 1997. He worked as a postdoctorate fellow at Hydrographical Institute of the Portuguese Navy from 1999 to 2004, where he was responsible with the wave modelling and participated in providing the environmental support for some major situations as: the accident of M/V Prestige (2002) and the NATO exercises ‘Unified Odyssey’ (2002) and ‘Swordfish’ (2003). He worked as a consulting scientist at the NATO Centre for Maritime Research and Experimentation, La Spezia, Italy (2005), having main tasks as: modelling coastal waves and surf zone processes. Starting in 2006, in parallel with his activity as a professor at University ‘Dunarea de Jos’ of Galati, he also worked as a professor collaborator at CENTEC – Centre for Marine Technology and Ocean Engineering, University of Lisbon, Portugal. He has published more than 150 works in the fields of renewable energy and marine engineering and he has received the awards of Doctor Honoris Causa (2015), at the Maritime University of Constanta, Romania and Outstanding Contribution in Reviewing, Renewable Energy (2015) and Ocean Engineering (2016) journals. He is also the president of the Council of the Doctoral Schools in Galati University, ‘Dunarea de Jos’.

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