Costal impact of a wave dragon based energy farm operating on the near shore of the Black Sea
Eugen Rusu & Sorin Diaconu*
Department of Applied Mechanics, University Dunarea de Jos of Galati, Romania [E.Mail: sorin.diaconuu@ugal.ro]
Received 23 July 2012; revised 25 October 2012
An analysis of the wave climate based on historical data is first carried out. High resolution simulations with the SWAN spectr al model were performed considering the most relevant environmental conditions that could be expected in the area targeted. In order to evaluate the impact of the wave energy farm, wave model simulations were carried out considering three different situations. These are without any wave energy converter, with one converter and with four converters operating in the nearshore. Impact in the geographical and in the spectral spaces was evaluated for various representative patterns. Moreover, in order to estimate the influence of the wave farm on the shoreline dynamics, the nearshore circulation was also assessed using the 1D Surf model. Results show that the presence of such a wave farm has a strong influence on the wave conditions immediately down wave but this influence is in general highly attenuated at the level of the coastline.
[Keywords: Black Sea, Wave Dragon, SWAN, Wave transformation, Coastal impact]
Introduction
A first evaluation of the wave energy resources at the level of the entire basin of the Black Sea was carried out by Rusu1 and the western side of the sea was found relatively more energetic. Moreover, further studies focused on the western side of the sea (Rusu2, Rusu and Ivan3 and Rusu and Macuta4) showed also the existence of some hot spots from the point of view of the wave energy. These are coastal areas where, due to the bathymetry or to other features of the environmental matrix, significant differences in the wave climate occur in comparison with the neighbouring areas. Coastal sector at the mouth of the Danube River is such a hot spot.
Based on various data sources, Onea and Rusu5 performed a preliminary evaluation of the wind conditions and variability in the Black Sea area and the western side was also found more energetic with very similar features with locations from the Northern and the Baltic seas where wind farms already operate.
Besides the Wave Dragon device, there are several other devices and a recent overview on the WEC (wave energy converters) evolution is given in Babarit6. The waves depend on the characteristics of the wind that generates them. They vary from day to day and from season to season, but also from a
location to another, as for example discussed in the works of Prasad7 and Rao8. In general the energetic conditions are significantly higher in winter time than in summer time.
Some preliminary studies are those performed by Millar9 for the Wave Hub project proposed for installation on the seabed off the north coast of Cornwall in the UK, or in Portugal by Palha10 that estimated the effect on the shoreline wave climate due to the installation of a Pelamis based wave farm in the Portuguese pilot zone. Even the existence of only a wind farm in the nearshore may affect substantially the dynamics of the coastline as reported by Ponce de Leon11. Hence, the estimation of how much the wave climate will be changed and which will be the coastal impact when an energy farm operates in the coastal environment represents a very important issue.
Previous studies concerning the influences of various factors on the coastal dynamics, as those performed by Kudale12, Kumar13, Neelamani14, Bhowmick15, Shenoi16 and Kalantzi17, showed that this influence is strongly dependent both on the bathymetric features and of the particularities of the environmental matrix. The present study provides some outputs in relationship with the influence of an
energy farm based on Wave Dragon devices that would operate in the coastal environment of the western Black Sea. On the other hand, it has to be highlighted that the work developed herewith could have relevance not only for the area targeted but also for some other coastal sites.
Materials and Methods
The target area considered in the present work is situated south of the Sulina channel, which is the main gate in the seventh Trans European transportation corridor (Fig. 1). This area was found in some previous studies (Rusu1,18) as being among the most energetic sites from the western side of the sea.
are coming waves in general higher than from the other directions. As expected the lowest wave heights correspond to the western direction because of the presence of the coast in that side.
Some other results coming from the above analysis are presented also in Fig. 2, where the Hs classes are presented in percents in terms of the number of occurrences. The figure illustrates in parallel the results for total time (a) and wintertime, respectively.
Fig. 1–Location of the target area and the wave conditions resulting from an analysis of 5 year of data (2006-2011).
Wave fields in the study area are characterized by significant variations during the year. Analysis presented in this section is based on data measured at a buoy situated close to the target area, in the western sector of the Black Sea at a location where the water depth is about 40 m. Measurements were made daily during a 5 - year period between 2006 and 2011.
Results specified were reported to the entire year and to the six-month period from October to March, respectively which will be denoted as the wintertime.
Fig. 1 presents some results of the above analysis in terms of the directional distributions of the Hs classes.
As it can be seen, the dominant wave direction is from the northeastern sector and also from this direction
Fig. 2–Analysis of the wave data measured at buoy close to the target area in the period 2006-2011: a) Classes of significant wave height (Hs) for total time interval; b) Hs
classes for wintertime.
Fig. 3–Analysis of the wave data measured at a buoy close to the target area in the period 2006-2011: a) monthly maximum
wave height; b) monthly maximum wave period.
Monthly maximum values of the significant wave heights and mean wave periods are shown in Fig. 3 a, b, respectively.
From the analysis of the results presented above, it results that the time interval between December and January has the highest probability of occurrence of waves with significant wave heights even greater than 7 m, the possibility of this occurrence begins in September and lasts through March. A quasi similar evolution can be seen for the significant wave heights in the classes 4-5 m, 5–6 m and 6–7 m.
Waves with significant wave heights between 1 and 2 m occur approximately equally throughout the year, with a minimum in March and a maximum in July. For the waves smaller than 1m, the frequency of occurrence in summertime is almost double than in wintertime.
In wintertime, for the classes 3-4 m it can be noticed an increase with about 4.28% in comparison with the total time while for the classes 0-1m a decrease of 9.69% could be noticed. Smallest difference between wintertime and total time occurs for the waves between 1-2 m, where there is a difference of only 0.44%. The largest difference of the Hs variation occurs between April and May. Analysis of the significant wave heights indicates that the highest value (7.08 m) are characteristic to the waves coming from the northeastern sector.
Regarding the maximum values of the mean wave periods, they do not differ very much in winter and total time. Nevertheless, values greater than 10s were encountered only in January while the lowest value was registered in July. Highest value of the mean wave period (10.04s) corresponds to waves coming from the northeast.
The wave model considered in the present study is SWAN (Simulating Waves Nearshore, Booij19). This is the state-of-the art phase averaging shallow water wave model and solves the wave action density balance equation.
Most of the energy accumulated by waves is finally dissipated in the surf zone by breaking. Many phenomena are generated from this dissipation but from a practical point of view, the generation of the longshore currents has most likely the highest significance. These currents sometimes achieve
considerable strength and are a significant factor in controlling the morphology of the beaches. They can also have severe impacts on human activities in the surf zone. A simple, but effective model for the nearshore currents is Surf, or Navy Standard Surf Model (NSSM), (Mettlach20). This is a parametric one-dimensional model that solves the momentum balace equation in the offshore direction only.
Because NSSM is one-dimensional several assumptions are utilized. In particular, the bottom contours are considered straight and parallel, the currents depth-uniform and directional wave spectra narrow-banded in frequency and direction.
Joint evaluations with SWAN and NSSM of the waves and nearshore currents were performed in the Italian nearshore by Conley and Rusu21,22 and extended comparisons against in situ measurements showed that this approach, although has several particular limitations related especially with the presence of the highly irregular bathymetry, can be considered reliable for a wide range of coastal applications including coastal areas as those considered herewith.
In an attempt to maximize the combined properties of simplicity and reliability, Rusu et al23 joined the two models in a user friendly computational tool denoted as the “Interface for SWAN and Surf Models”
(ISSM). Further validations against in situ measurements as well as comparisons with the more complex modeling systems performed in the Portuguese nearshore by Rusu and Guedes Soares24 showed the effectiveness of this computational environment. ISSM modeling system will be used in the present work.
Wave Dragon (Fig. 4) is composed of two main structural elements: two wave reflectors to guide the incoming waves towards a ramp and a main body where most of the waves run up. Curved ramp overtops in a water reservoir and consequently has an increased potential energy compared to the surrounding sea. The obtained energy is converted into electricity when the stored water drains back to the sea through hydro turbines. Waves which do not interact with the ramp are reflected or transmitted under the WEC, or diffracted around the structure.
Basically, the Wave Dragon is a very simple construction, having only one kind of moving parts:
the turbines. This is very important for every device which operates in the sea where extreme forces are commonly found, seriously affecting any moving parts.
However, this device has a very complex design and a lot of efforts have been made to improve his performance with tests and simulations in order to reduce the forces acting on his structure, to optimize overtopping, to reduce construction and maintenance costs, to stay as stationary as possible and of course to produce more energy.
Physically there is quite a complex relationship between the wave height, the geometry of the ramp and wave reflectors, the floating height of the Wave Dragon and, most important, the amount of water overtopping and storing in the reservoir (Fig. 4b).
With its curved ramp and wave reflectors, Wave Dragon is deliberately designed to increase the quantity of water that overtops as the waves reach it.
Wave Dragon ramp is like a beach. When the wave interacts with a beach it changes its nature. Ramp of Wave Dragon is very short and relative steep to reduce the loss of energy that takes place each time a wave reaches the beach. The interacting wave changes its geometry and elevates. Test experiments showed that
overtopping increases significantly due the elliptical shape of the ramp which optimizes this effect.
The dimensions of the Wave Dragon model considered in this work are specified in (Fig. 4).
Computational domain is illustrated in Fig. 5. This is a rectangle with about 17.5 km in x-direction (cross shore) and 20 km in y-direction (long shore).
Fig. 4-a)–Main structural elements of a Wave Dragon WEC in plan view - dimensions in meters; b) cross sectional view of
the reservoir part of the Wave Dragon.
Fig. 5–The computational domain considered for the simulations with numerical models. In background the bathymetry is represented while in foreground the Wave Dragon, the reference points and the reference lines. BP indicates the boundary point, OP are the offshore points and RL represent the reference lines considered for the analysis of the nearshore currents. Each offshore extremity point of the above reference lines is denoted as NP (nearshore point). The
Wave Dragons which are floating slack-moored wave energy converters are deployed in the present case study at the depth
of 25m and a distance to coast line of 9.5 km.
It has to be highlighted that although the wind conditions were considered as input in the wave model, its influence was in general not significant because the geographical space of the target area is not large, this implying a small fetch. On the other hand since the target area is located more than 20 kilometers from the closer mouth of the Danube River (the Saint George arm) the currents induced by the river outflow can be neglected.
SWAN has the capacity to model the obstacle transmission. Following the Wave Dragon geometry, as illustrated in Fig. 4, the devices were defined as
obstacles in the model simulations. According to the technical notes of the device the transmission coefficient was set 0.6 and the reflection 0.2. These values are those indicated by PIANC25.
Results and Discussion
In order to perform an in depth analysis of the wave conditions corresponding to the three different cases considered in the present work, WD0 (without any Wave Dragon device operating in the target area), WD1 (with one Wave Dragon device operating in the target area) and WD4 (with four Wave Dragon devices operating in line in the target area), several reference points were considered and they are illustrated in Fig. 5.
Thus the first reference point is denoted as BP and indicates the boundary point. Three other reference points are defined 1800 meters down wave from the devices and they are denoted as offshore points (OP).
On the other hand, in order to assess the coastal impact of the wave energy farm by evaluating the wave induced nearshore currents with the ISSM modeling system, seven reference lines (denoted as RL1 to RL7) that cover the entire coast corresponding to the computational domain were also defined. All these reference points and lines are illustrated in Fig. 5.
Moreover, each extremity point from the offshore side of the above reference lines is defined as nearshore point (denoted as NP1 to NP7) and these points were also considered for analyzing in both geographical and spectral spaces the nearshore waves.
Impact in the geographical space on the wave field of a wave farm based on Wave Dragon devices is presented in Figs. 6 and 7 for two different case studies. These are CS1 (Hs=3 m, Tm=6 s, Dir=90°) and CS2 (Hs=5 m, Tm=8 s, Dir=30°). Where, Hs represents the significant wave height, Tm is the mean period and Dir stands for the mean wave direction.
Besides the case when no Wave Dragon device is deployed in the target area (denoted as WD0), two different farm configurations were considered in the model system simulations. These are WD1, when a single Wave Dragon device operates in the field and WD4 when four Wave Dragon devices operate in line.
Results presented in Figs. 6 and 7 show that for CS1 (corresponding to average wave conditions) the changes induced by the WECs on the wave propagation is only local and is attenuated after about 1 km. Nevertheless, as the incoming wave heights
Fig. 6–Evaluation in the geographical space of the impact on the wave field of a wave farm based on Wave Dragon WECs
that operates in the target area. CS1 – average to high energetic conditions and waves coming from east (90° in nautical convention). a) SWAN simulation for the case without
Wave Dragons (WD0). b) SWAN simulation for the case with one Wave Dragon (WD1). c) SWAN simulation for the case
when four Wave Dragons operate in line (WD4). The Hs scalar fields are presented in background while in foreground
the wave vectors are indicated.
Fig. 7–Evaluation in the geographical space of the impact on the wave field of a wave farm based on Wave Dragon WECs
that operates in the target area. CS2 – high energetic conditions and waves coming from northeast (30° in Nautical
convention). a) SWAN simulation for the case WD0. b) SWAN simulation for the case WD1. c) SWAN simulation for the case WD4. The Hs scalar fields are presented in background while
in foreground the wave vectors are indicated.
become greater this impact increases and propagates towards the coast.
The evaluation in the spectral space of the energy farm impact is illustrated in Figs. 8 and 9 for the same
two case studies (CS1 and CS2). 2D wave spectra were analyzed in parallel in the reference points OP2 and NP3 for the three different configurations considered (WD0, WD1 and WD4). As a reference, a JONSWAP type spectrum was considered.
Spectrum corresponding to the boundary point (BP) that is unaffected by the wave farm is also illustrated in each figure. The results from Figs. 8 and 9 show that due to the presence of the Wave Dragons the single peak JONSWAP spectrum is transformed in a double peak spectrum immediately after the WEC (in OP2) but this spectral shape does not propagate further in the geographical space and at the level of the nearshore (the reference point NP3) no significant difference occurs in terms of the spectral shapes between the three different configurations considered (WD0, WD1 and WD4).
Fig. 8–Evaluation in the spectral space of the impact on the wave field of a wave farm based on Wave Dragon WECs that operates in the target area for CS1. a) BP for WD0. b) OP2
for WD0. c) NP3 for WD0, d) OP2 for WD1, e) NP3 for WD1, f) OP2 for WD4, g) NP3 for WD4.
Fig. 9–Evaluation in the spectral space of the impact on the wave field of a wave farm based on Wave Dragon WECs that operates in the target area for CS2. a) BP for WD0. b) OP2 for WD0. c) NP3 for WD0, d) OP2 for WD1, e) NP3 for WD1,
f) OP2 for WD4, g) NP3 for WD4.
A detailed representation of the wave parameters variation is given in Table 1 for CS1 and in Table 2 for CS2. This includes the values of the wave parameters in all the reference points defined (BP, OP1, OP2, OP3, NP1, NP2, NP3, NP4, NP5, NP6 and NP7) for all the three configurations considered (WD0, WD1 and WD4).
Besides the two main case studies considered (CS1 and CS2), where the wave data are analyzed in both the offshore and the nearshore points, several relevant situations are presented in Table 3, this time the analysis being focused only on the offshore points where the influence of the wave energy farm is in fact really relevant.
Parameters considered in Tables 1-3 are (Hs), maximum variance (Emax), Dir, peak period (Tp), Tm, mean wave length (Wlen), the components of the energy transport (Px, Py) and the components of the wave forces (Fx, Fy). Results presented in the above tables show again that indeed relevant differences
Table 1–CS1 (Hs=3 m, Tm=6 s, Dir=90°), evaluation of the impact of the energy farms on the waves in the reference points OP1 (northern offshore point), OP2 (central offshore point), OP3 (southern offshore point), and in the point NP1-NP7. WD0 – no energy converter, WD1 – one Wave Dragon energy converter, WD4 – four Wave Dragon energy
converters operating in line.
WD Hs Emax Dir Tm/Tp Wlen Px Py Fx Fy
(m) (m2/Hz/deg) (deg) (s) (m) (m3/s) (m3/s) (N/m2) (Nm2)
BP 0 2.7 5.27 90 5.3/5.8 42.6 -1.7 0 -0.1 0
1 2.7 5.27 90 5.3/5.8 42.6 -1.7 0 -0.1 0
4 2.7 5.26 90 5.3/5.8 42.6 -1.7 0 -0.1 0
OP1 0 2.3 4.31 90.5 5.5/5.8 46.2 -1.3 0.02 0.03 -0.01
1 2.2 4.32 88.6 5.5/5.8 46.1 -1.2 -0.02 0.04 -0.02
4 2 3.8 89.3 5.5/5.8 45.8 -1 -0.01 0.04 0
OP2 0 2.3 4.31 91 5.5/5.8 46.3 -1.3 0.03 0.02 -0.01
1 2.2 4.05 91.4 5.5/5.8 46.2 -1.2 0.03 0.03 0
4 2 3.81 93.1 5.5/5.8 46 -1 0.06 0.03 0.01
OP3 0 2.3 4.32 91.5 5.5/5.8 46.5 -1.3 0.04 0.02 -0.03
1 2.2 4.33 93.4 5.5/5.8 46.4 -1.3 0.08 0.02 -0.02
4 2.1 4.07 96.4 5.5/5.8 46.2 -1.1 0.13 0.02 0
NP1 0 2.1 4.92 78.8 5.4/5.8 33.5 -1.3 -0.25 -0.76 -0.6
1 2.1 4.93 78.7 5.4/5.8 33.5 -1.3 -0.26 -0.75 -0.59
4 2.1 4.96 78.1 5.4/5.8 33.5 -1.3 -0.27 -0.7 -0.58
NP2 0 1.8 4.55 89.1 5.5/5.8 33 -0.9 -0.01 0.05 0.23
1 1.8 4.56 88.8 5.5/5.8 33 -0.9 -0.02 0.1 0.24
4 1.7 4.6 87.9 5.5/5.8 32.9 -0.9 -0.03 0.26 0.27
NP3 0 1.4 3.08 100.1 5.4/5.8 28.3 -0.5 0.1 -1.47 0.45
1 1.4 3.08 100.1 5.4/5.8 28.3 -0.5 0.1 -1.47 0.46
4 1.4 3.08 100.2 5.4/5.8 28.3 -0.5 0.1 -1.47 0.46
NP4 0 1.5 3.9 93.9 5.5/5.8 29.4 -0.6 0.04 -3.25 -0.05
1 1.5 3.89 93.9 5.5/5.8 29.4 -0.6 0.04 -3.25 -0.05
4 1.5 3.38 93.9 5.5/5.8 29.3 -0.6 0.04 -2.93 -0.07
NP5 0 1.6 3.46 94.9 5.5/5.8 31.5 -0.7 0.06 -0.23 -0.14
1 1.6 3.38 95.1 5.5/5.8 31.5 -0.7 0.07 -0.17 -0.11
4 1.6 3.44 95.8 5.5/5.8 31.4 -0.7 0.07 -0.06 -0.09
NP6 0 1.6 3.63 83.5 5.5/5.8 31.7 -0.7 -0.1 -0.98 -0.31
1 1.6 3.64 83.6 5.5/5.8 31.7 -0.7 -0.1 -0.97 -0.3
4 1.6 3.68 84 5.5/5.8 31.7 -0.7 -0.09 -0.94 -0.28
NP7 0 1.4 3.08 100.1 5.4/5.8 28.3 -0.5 0.1 -1.47 0.45
1 1.4 3.08 100.1 5.4/5.8 28.3 -0.5 0.1 -1.47 0.46
4 1.4 3.08 100.2 5.4/5.8 28.3 -0.5 0.1 -1.47 0.46
Table 2–CS2 (Hs=5m, Tm=8s, Dir=30°), evaluation of the impact of the energy farms on the waves in the reference points OP1, OP2, OP3, NP1-NP7.
WD Hs Emax Dir Tm/Tp Wlen Px Py Fx Fy
(m) (m2/Hz/deg) (deg) (s) (m) (m3/s) (m3/s) (N/m2) (N/m2)
BP 0 4.5 18.51 34.6 7.1/8.2 72.9 -3.7 -5.5 -0.08 -0.1
1 4.5 18.51 34.6 7.1/8.2 72.9 -3.7 -5.5 -0.08 -0.1
4 4.5 18.51 34.6 7.1/8.2 72.9 -3.7 -5.5 -0.08 -0.1
OP1 0 3.9 15.12 39.9 7.2/8.2 73.2 -3.7 -4.3 0.43 -0.2
1 3.9 15.12 39.9 7.2/8.2 73.2 -3.7 -4.3 0.43 -0.2
4 3.7 14.47 35.9 7.2/8.2 72.9 -3 -4.1 0.46 -0.2
OP2 0 3.8 15.07 41 7.2/8.2 73.1 -3.6 -4 0.36 -0.1
1 3.7 15.07 38.9 7.2/8.2 73 -3.3 -4 0.37 -0.2
4 3.5 12.97 36.5 7.2/8.2 72.5 -2.7 -3.6 0.38 -0.1
OP3 0 3.8 14.97 42.5 7.2/8.2 73.4 -3.6 -3.8 0.3 -0.2
1 3.6 14.21 41 7.2/8.2 73.2 -3.2 -3.6 0.33 -0.2
4 3.3 11.56 38.4 7.1/8.2 72.6 -2.6 -3.2 0.32 -0.2
NP1 0 2.4 6.89 49 7.2/8.2 47.1 -1.4 -1.2 -3.45 -3
1 2.4 6.89 49 7.2/8.2 47.1 -1.4 -1.2 -3.45 -3
4 2.4 6.89 49 7.2/8.2 47.1 -1.4 -1.2 -3.45 -3
NP2 0 2.1 14.95 72.2 7.5/8.2 46.6 -1.5 -0.4 -5.06 -1.3
1 2.1 14.95 72.2 7.5/8.2 46.6 -1.5 -0.4 -5.07 -1.3
4 2.1 14.97 72.1 7.5/8.2 46.6 -1.5 -0.4 -5.05 -1.3
NP3 0 1.5 7.54 77.2 7.4/8.2 40.9 -0.7 -0.1 -2.65 -0.1
1 1.5 7.57 77.3 7.4/8.2 40.9 -0.7 -0.1 -2.65 -0.1
4 1.5 7.64 77.5 7.4/8.2 40.8 -0.7 -0.1 -2.64 -0.1
NP4 0 1.7 8.36 76.8 7.4/8.2 40.6 -0.8 -0.2 -6.16 -1.4
1 1.7 8.33 76.8 7.4/8.2 40.6 -0.8 -0.2 -6.17 -1.4
4 1.7 8.5 75.7 7.4/8.2 40.7 -0.8 -0.2 -6.03 -1.4
NP5 0 1.7 9.81 76.3 7.4/8.2 44.5 -1 -0.2 -1.52 -0.6
1 1.7 9.53 76.1 7.4/8.2 44.4 -1 -0.2 -1.49 -0.6
4 1.7 9.01 75.7 7.4/8.2 44.2 -1 -0.2 -1.37 -0.6
NP6 0 1.8 9.91 66.3 7.4/8.2 44.1 -1 -0.4 -2.54 -1.2
1 1.8 9.82 66.4 7.3/8.2 44.1 -1 -0.4 -2.53 -1.2
4 1.8 9.64 66.6 7.3/8.2 44 -1 -0.4 -2.49 -1.1
NP7 0 1.5 7.54 77.2 7.4/8.2 40.9 -0.7 -0.1 -2.65 -0.1
1 1.5 7.57 77.3 7.4/8.2 40.9 -0.7 -0.1 -2.65 -0.1
4 1.5 7.64 77.5 7.4/8.2 40.8 -0.7 -0.1 -2.64 -0.1
Table 3–Evaluation of impact of the energy farms on the waves in the reference points OP1, OP2 and OP3 for the wave conditions Hs=3m, Tm=6s, Dir=30° and Hs=3m, Tm=6s, Dir=150°.
WD Hs Emax Dir Tm/Tp Wlen Px Py Fx Fy
(m) (m2/Hz/deg) (deg) (s) (m) (m3/s) (m3/s) (N/m2) (N/m2) Hs=3m, Tm=6s, Dir=30°
BP 0 2.6 5.12 35 5.4/5.8 43.8 -0.9 -1.3 -0.04 -0.05
1 2.6 5.12 35 5.4/5.8 43.8 -0.9 -1.3 -0.04 -0.05
4 2.6 5.12 35 5.4/5.8 43.8 -0.9 -1.3 -0.04 -0.05
OP1 0 2.3 4.24 34.8 5.5/5.8 45.9 -0.7 -1.1 0.04 -0.04
1 2.3 4.24 34.8 5.5/5.8 45.9 -0.7 -1.1 0.04 -0.04
4 2.2 4.3 31 5.5/5.8 45.6 -0.6 -1 0.05 -0.04
OP2 0 2.2 4.17 36 5.5/5.8 46 -0.7 -1 0.03 -0.03
1 2.2 4.17 33.9 5.5/5.8 46 -0.7 -1 0.03 -0.04
4 2.1 4.21 31.4 5.5/5.8 45.5 -0.6 -0.9 0.04 -0.03
OP3 0 2.2 4.11 37.2 5.5/5.8 46.2 -0.7 -1 0.03 -0.05
1 2.1 4.12 35.6 5.5/5.8 46.1 -0.7 -0.9 0.03 -0.04
4 2 4.01 32.7 5.5/5.8 45.6 -0.5 -0.8 0.03 -0.03
Hs=3m, Tm=6s, Dir=150°
BP 0 2.6 5.12 144.6 5.4/5.8 43.9 -0.9 1.3 -0.04 0.05
1 2.6 5.11 144.6 5.4/5.8 43.9 -0.9 1.3 -0.04 0.05
4 2.6 5.11 144.7 5.4/5.8 43.9 -0.9 1.3 -0.04 0.05
OP1 0 2.2 4.01 143.4 5.5/5.8 46.1 -0.7 1 0.04 0.01
1 2.1 4.01 145.2 5.5/5.8 46 -0.6 0.9 0.05 0.01
4 2 4.01 147.9 5.5/5.8 45.8 -0.5 0.9 0.05 0.02
OP2 0 2.2 4.1 144.4 5.5/5.8 46.1 -0.7 1 0.03 0.02
1 2.2 4.1 146.2 5.5/5.8 46.1 -0.7 1 0.04 0.03
4 2.1 4.11 148.2 5.5/5.8 46 -0.6 1 0.04 0.02
OP3 0 2.3 4.21 145.7 5.5/5.8 46 -0.7 1.1 0.03 0
1 2.3 4.21 145.7 5.5/5.8 46 -0.7 1.1 0.03 0
4 2.2 4.21 147.4 5.5/5.8 46.1 -0.7 1.1 0.03 0.01
occur in the values of the wave parameters in the offshore reference points that were defined while as regards the nearshore point NP1-NP7 these differences are highly attenuated.
As it is known, the energy transferred from the wind is transported with relatively small loss over the sea and is finally dissipated in the surf zone. This energy dissipation in the coastal environment
generates various phenomena and among them the nearshore currents are probably the most relevant because they contribute to the longshore sediment transport affecting in this way crucially the coastal dynamics.
In this connection, a very legitimate question would be to assess how an energy farm that would operate in the coastal environment will affect the nearshore circulation patterns and thus to estimate which will be the medium to long term impact on the coastal dynamics of the energy farm.
Thus considering the ISSM modeling system, the nearshore currents were evaluated along the reference
Table 4-Evaluation of impact of the energy farms on the nearshore currents in terms of maximum current velocities (in m/s) along the reference lines RL1-RL7 for Hs=3m and Hs=5m, with three different wave directions (30°, 90°,150°).
The three configurations (WD0, WD1 and WD4) were considered in parallel.
Case Line RL1 RL2 RL3 RL4 RL5 RL6 RL7
Study Config.
H3D30 WD0 1.13 0.81 0.99 0.59 0.62 1.51 0.49
Hs=3m WD1 1.13 0.81 0.99 0.59 0.63 1.51 0.49
WD4 1.13 0.81 1.01 0.6 0.63 1.51 0.49
H3D90 WD0 0.4 0.31 0.36 0.12 0.22 0.42 0.29
Hs=3m WD1 0.4 0.31 0.22 0.12 0.22 0.41 0.29
WD4 0.41 0.32 0.16 0.12 0.24 0.4 0.3
H3D150 WD0 0.73 0.28 1.92 0.74 0.91 0.71 0.94
Hs=3m WD1 0.73 0.28 1.92 0.75 0.91 0.71 0.94
WD4 0.72 0.27 1.92 0.75 0.92 0.71 0.94
H5D30 WD0 1.55 0.7 0.73 0.82 0.5 0.68 0.41
Hs=5m WD1 1.55 0.7 0.74 0.83 0.51 0.68 0.41
WD4 1.55 0.7 0.82 0.84 0.51 0.67 0.4
H5D90 WD0 0.34 0.09 1.33 0.5 0.38 0.26 0.43
Hs=5m WD1 0.35 0.1 1.32 0.5 0.39 0.26 0.43
WD4 0.37 0.12 1.32 0.5 0.4 0.26 0.43
H5D150 WD0 0.85 0.26 1.98 1.02 0.77 0.32 1.04
Hs=5m WD1 0.84 0.26 1.99 1.03 0.77 0.32 1.04
WD4 0.83 0.25 2.01 1.04 0.77 0.32 1.04
lines RL1-RL7, for the three different configurations (WD0, WD1 and WD4). In terms of maximum longshore current velocity the results are presented in Table 4 and illustrates the results corresponding to Hs=3 m and Hs=5m, for the wave directions (30°, 90°, 150°).
For the two case studies considered (CS1 and CS2, and which present qualitatively similar results) the maximum values of the velocities of the nearshore currents along the reference lines are illustrated in Fig. 10. Although, as the results show, in general the influence of the wave farm over the nearshore currents is not high, it can be seen that the most sensitive direction is that normal to the shoreline (90°), when
Fig. 10–Evaluation of the impact of the energy farms on the maximum velocities of the nearshore currents along the
reference lines considered. a) CS1, b) CS2.
for CS1 the current velocity decreases with about 60%
in NP3.
An additional case is presented in Fig. 11. This corresponds also to the normal direction to the shoreline but to a significant wave height of only 1 m. For such situation, the current velocities are very low but on the other hand the relative variations of the current velocities become significant. Moreover the results of the modelling system indicate that in such conditions the presence of the energy farms lead to an increase of the nearshore currents in some places.
Relatively high difference in terms of current velocities might be explained due to fact that this parameter is highly dependent on the local bathymetric features and in certain conditions (as those corresponding to the reference line RL3) even a small variation of the wave parameter can induce a more relevant variation of the current velocity.
Final considerations
The present work has as objective to study the influence of an energy farm operating in the western coastal environment of the Black Sea. Wave energy converter considered is the Wave Dragon and the influences of two different configurations were studied. These are a single device and alternatively four devices. According to their standard requirements the WECs are considered deployed between 25 and 30 meters. SWAN model simulations were performed considering the three different situations, without WECs, with one WEC and with four WECs. Besides the standard wave parameters as significant wave height, mean and peak periods, mean wave direction and wavelength, the components of the wave energy transport vectors and of the wave forces were also evaluated. Analysis of the results performed in both geographical and spectral spaces show that, although immediately down wave the presence of the wave farm changes drastically the wave fields, this influence is highly attenuated at the level of the breaking line. This is also due to the particularities of the specific site considered where, in order to operate at the indicated depth the Wave Dragons should be deployed at about 10km from the coast line.
The effect on the nearshore circulation was also evaluated. Results of these simulations show that despite the fact that the nearshore waves are
Fig. 11–Evaluation of the impact of the energy farms on the maximum velocities of the nearshore currents along the reference lines considered for an additional case defined by
the parameters Hs=1m, Tm=4s, Dir=90°.
apparently not very much affected by the presence of the wave energy farms, the maximum current velocities may however have more relevant variations.
For this particular coastal environment, these variations are even more significant when the wave direction is normal to the shoreline.
The results concerning the overall influence of the wave energy converters on the wave field are in line with the before mentioned studies of Millar9,Palha10 and Ponce de Leon11, which are based on similar wave modelling techniques. On the other hand, unlike in the previous studies, the present work went a step forward and evaluated also the nearshore currents variations due the conversion of the wave energy. This represents an extremely important issue since the variation of the nearshore currents may be significantly higher in relative terms than the wave height variations.
The work is still ongoing and the medium to long term impact of the energy farm on the shoreline dynamics is presently investigated.
Acknowledgment
Work of the corresponding author has been made in the scope of the project SOP HRD - EFICIENT 61445/2009 (Management System for the Fellowships Granted to the PhD Students).
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