Renewable Energy 34 (2009) 2323–2333
Contents lists available at ScienceDirect
Renewable Energy journal homepage: www.elsevier.com/locate/renene
Wave energy potential in Galicia (NW Spain) G. Iglesias a, *, M. Lo´pez a, R. Carballo a, A. Castro a, J.A. Fraguela b, P. Frigaard c a
University of Santiago de Compostela, Hydraulic Engineering, E.P.S., Campus Universitario s/n, 27002 Lugo, Spain ˜a, E.P.S., Campus de Esteiro s/n, Ferrol, Spain University of A Corun c University of Aalborg, Sohngaardsholmsvej 57, DK 9000, Denmark b
a r t i c l e i n f o
a b s t r a c t
Article history: Received 3 March 2008 Accepted 30 March 2009 Available online 7 May 2009
Wave power presents significant advantages with regard to other CO2-free energy sources, among which the predictability, high load factor and low visual and environmental impact stand out. Galicia, facing the Atlantic on the north-western corner of the Iberian Peninsula, is subjected to a very harsh wave climate; in this work its potential for energy production is assessed based on three-hourly data from a third generation ocean wave model (WAM) covering the period 1996–2005. Taking into account the results of this assessment along with other relevant considerations such as the location of ports, navigation routes, and fishing and aquaculture zones, an area is selected for wave energy exploitation. The transformation of the offshore wave field as it propagates into this area is computed by means of a nearshore wave model (SWAN) in order to select the optimum locations for a wave farm. Two zones emerge as those with the highest potential for wave energy exploitation. The large modifications in the available wave power resulting from relatively small changes of position are made apparent in the process. Ó 2009 Elsevier Ltd. All rights reserved.
Keywords: Wave energy Wave power Renewable energy Galicia Numerical model Wave propagation
1. Introduction The development of novel renewable energy sources together with the expansion of those currently exploited is crucial to reducing the emissions of greenhouse gases as prescribed by the Kyoto protocol. Among the new sources, wave energy is one of the most promising [1–3]. It may be seen as a concentrated form of wind energy in that ocean waves are generated by wind blowing over the ocean surface [4]. Wave energy presents a number of advantages with respect to other CO2-free energy sources – resource predictability, high power density, relatively high utilization factor and last, but not least, low environmental and visual impact [5]. With regard to tidal energy, the other marine renewable, there exist many more potential locations for a wave farm than for a tidal energy operation, as strong tidal currents occur only in a relatively small number of coastal areas. In spite of these advantages, wave energy exploitation is still in its infancy; the reason may be found in the technological challenges still ahead. There can nonetheless be little doubt that wave energy has a promising future in coastal regions with a medium or high-energy wave climate – the intensive research and development effort currently devoted to
* Corresponding author. Tel.: þ34 982 285900x23646; fax: þ34 982 285926. E-mail address:
[email protected] (G. Iglesias). 0960-1481/$ – see front matter Ó 2009 Elsevier Ltd. All rights reserved. doi:10.1016/j.renene.2009.03.030
various technologies will conduce over the next years to efficient wave energy converters operating commercially. Various wave energy technologies are currently being developed based on different principles. Although a detailed account is outside the scope of this paper, some general ideas may be of interest to frame the discussion. The different systems may be classified according to their proximity to the coastline as shoreline, nearshore, or offshore systems [6]; their respective water depth ranges are below 15 m, 15–30 m, and 30–50 m. Shoreline systems were the first to be developed; some of them resort to an oscillating water column coupled with a Wells turbine [7–9]. The high cost of building a structure in, or near, the surf zone and the high environmental and visual impact of a shoreline operation weigh against this kind of systems, especially if a high-energy output is intended. Some of these downsides disappear in the case that the converter can be integrated into a new coastal structure; although this solution may indeed be of interest in certain instances, it is naturally of limited application. As regards nearshore and offshore energy converters, the distinction between both types is not so clearcut as that between shoreline and non-shoreline devices – most non-shoreline devices can in fact operate in nearshore or offshore water depth ranges. Generally speaking, offshore installations appear best suited for providing energy to the general electricity network, while nearshore installations may be more appropriate where the aim is to supply a specific industry, such as a desalinisation plant. In the former case a number of converters
2324
G. Iglesias et al. / Renewable Energy 34 (2009) 2323–2333
Fig. 1. Location of WAM model grid points used for the study.
will usually be installed together, forming a wave farm; this allows to reduce the cost of the connection to the electricity grid per device, and hence per kW of rated power, by laying a single submarine cable from the shoreline to a hub which is in turn connected to each converter. Some of these devices are currently being tested, either in the laboratory or in the sea (e.g. [6,10,11]). In addition to the technology itself, a fundamental aspect towards tapping wave energy is the resource characterisation, which has already been carried out in some regions [5,12,13]. Galicia, NW Spain, is well known for its harsh wave climate, among the most energetic in Europe. In this work, the wave energy resource offshore the Galician coasts was characterised based on
a long-term data set computed by the WAM ocean wave model [14] and checked for consistency with wind and pressure measurements. This allowed to discern the areas with the highest potential in the region. However, the wave climate is not – for all its importance – the only issue to consider when choosing the location of a wave operation: other aspects, such as the proximity to ports, navigation routes, or aquaculture and fishing areas ought to be taken into account. On these grounds, a coastal stretch extending some 110 km was selected. From the analysis of the offshore wave data a number of sea states were chosen, representing 61% of the total annual energy in the area. These wave cases were then propagated into the nearshore by means of the SWAN wave model,
G. Iglesias et al. / Renewable Energy 34 (2009) 2323–2333
which takes into account refraction, shoaling, bottom dissipation and shelter by the coastline or neighbouring islands [15,16]. This procedure allowed to identify the locations within the area where the wave energy potential is highest. This article is structured as follows. First, the WAM numerical model is briefly presented along with the main characteristics of the long-term data set itself. Second, the offshore wave energy potential is characterised. This is followed by an overview of the additional aspects to consider when selecting the location for a wave energy operation and their application to Galicia, which results in the choice of an area. Next the nearshore wave power within this area is studied, and two zones are recommended as those with the highest wave energy potential. Finally the main conclusions from the work are discussed.
2325
Table 2 % Of total time in an average year corresponding to sea states with different significant wave height (Hs) and peak wave period (Tp). Point 1043074. Hs (m) Tp (s) 2 2–4 4–6 6–8 8–10 10–12 12–14 14–16 16–18 18–20 >20 Total >10 9–10 8–9 7–8 6–7 5–6 4–5 3–4 2–3 1–2 10 Total 0.5 0.2 0.0 0.0 0.0 0.6 2.8 2.6 6.7
0.2 0.0 0.0 0.0 0.0 0.4 1.7 1.1 3.4
0.1 0.0 0.0 0.0 0.0 0.1 1.0 0.6 1.7
0.0 0.0 0.0 0.0 0.0 0.0 0.5 0.2 0.8
0.0 0.0 0.0 0.0 0.0 0.0 0.3 0.1 0.4
0.0 0.0 0.0 0.0 0.0 0.0 0.1 0.0 0.1
0.0 0.0 0.0 0.0 0.0 0.0 0.1 0.1 0.1
16.2 8.7 0.1 0.1 0.2 4.9 28.9 40.9 100.0
2326
G. Iglesias et al. / Renewable Energy 34 (2009) 2323–2333
Table 4 Annual wave energy corresponding to sea states in different ranges of significant wave height (Hs) and peak wave period (Tp), and % of the total annual energy. Point 1043074. Hs (m)
Tp (s) 2–4
4–6
6–8
8–10
10–12
18–20
>20
>10
E (MWh/m) % Total
0.0 0.0
0.0 0.0
0.0 0.0
0.0 0.0
0.0 0.0
0.0 0.0
0.2 0.0
1.0 0.2
7.9 1.8
0.0 0.0
0.0 0.0
9.0 2.1
9–10
E (MWh/m) % Total
0.0 0.0
0.0 0.0
0.0 0.0
0.0 0.0
0.0 0.0
0.0 0.0
0.5 0.1
0.6 0.1
6.6 1.5
0.0 0.0
0.0 0.0
7.6 1.7
8–9
E (MWh/m) % Total
0.0 0.0
0.0 0.0
0.0 0.0
0.0 0.0
0.0 0.0
0.0 0.0
0.4 0.1
3.0 0.7
15.4 3.5
1.4 0.3
0.0 0.0
20.2 4.6
7–8
E (MWh/m) % Total
0.0 0.0
0.0 0.0
0.0 0.0
0.0 0.0
0.0 0.0
0.1 0.0
2.1 0.5
6.5 1.5
17.1 3.9
0.9 0.2
0.0 0.0
26.7 6.1
6–7
E (MWh/m) % Total
0.0 0.0
0.0 0.0
0.0 0.0
0.0 0.0
0.0 0.0
1.2 0.3
7.9 1.8
9.8 2.2
24.4 5.6
0.8 0.2
0.0 0.0
44.1 10.0
5–6
E (MWh/m) % Total
0.0 0.0
0.0 0.0
0.0 0.0
0.0 0.0
0.2 0.0
4.4 1.0
14.9 3.4
16.8 3.8
20.6 4.7
1.1 0.3
0.1 0.0
58.1 13.2
4–5
E (MWh/m) % Total
0.0 0.0
0.0 0.0
0.0 0.0
0.1 0.0
1.9 0.4
10.0 2.3
23.5 5.4
19.2 4.4
18.2 4.2
0.4 0.1
0.2 0.0
73.5 16.7
3–4
E (MWh/m) % Total
0.0 0.0
0.0 0.0
0.0 0.0
1.8 0.4
6.8 1.6
14.0 3.2
35.7 8.1
18.8 4.3
8.7 2.0
0.5 0.1
0.1 0.0
86.4 19.7
2–4
E (MWh/m) % Total
0.0 0.0
0.0 0.0
0.3 0.1
7.2 1.6
9.7 2.2
22.3 5.1
34.5 7.9
5.7 1.3
3.5 0.8
0.2 0.0
0.1 0.0
83.4 19.0
1–2
E (MWh/m) % Total
0.0 0.0
0.0 0.0
1.3 0.3
4.4 1.0
9.3 2.1
9.9 2.3
3.4 0.8
0.7 0.2
0.3 0.1
0.0 0.0
0.0 0.0
29.4 6.7
1
E (MWh/m) % Total
0.0 0.0
0.0 0.0
0.0 0.0
0.2 0.0
0.2 0.0
0.1 0.0
0.0 0.0
0.0 0.0
0.0 0.0
0.0 0.0
0.0 0.0
0.5 0.1
Total
E (MWh/m) % Total
0.0 0.0
0.0 0.0
1.6 0.4
13.7 3.1
28.1 6.4
62.0 14.1
123.0 28.0
82.0 18.7
122.8 28.0
5.3 1.2
0.4 0.1
438.9 100.0
2
and the peak wave period is the inverse of the frequency at the spectral peak (fp),
1 Tp ¼ fp :
(4)
The wave power, also known as the wave energy flux, is given by
P ¼ rg
Z2p ZN 0
cg ðf ; hÞSðf ; qÞdf dq;
(5)
0
where r is the seawater density, g is the gravitational acceleration, and cg is the group celerity, i.e. the velocity at which wave energy propagates, which is a function of the wave frequency and water Table 5 Total wave energy in an average year and average wave power for the WAM grid points used in the study. Grid point 1044067 1044068 1044069 1044070 1043070 1043071 1042072 1043073 1043074 1044074 1045074 1046074 1047075 1048076 1049076 1050076 1051075 1052075
Annual wave energy (MWh/m)
Average wave power (kW/m)
328.81 320.58 302.01 254.25 338.79 290.01 434.60 395.98 438.89 404.07 379.70 356.60 375.03 403.48 387.68 376.03 128.59 184.15
35.45 34.55 32.74 28.01 38.68 33.11 49.61 45.20 50.10 43.20 41.02 38.74 40.49 46.06 44.25 42.93 14.68 20.93
12–14
14–16
16–18
Total
depth [19]. Seawater density depends on salinity and temperature, which vary in time and space; an average value was taken for this work, r ¼ 1025 kg/m3. Equation (5) yields the wave power per unit width of wave front; if a certain wave energy converter (WEC) captures the energy of a width b of wave front, the corresponding power is
PWEC ¼ Pb:
(6)
Naturally the actual power output will depend on the converter efficiency. The mean wave direction may be obtained from the directional wave energy spectrum through
Z2p ZN
qm ¼
arctan 0 0 Z2p ZN 0
Sðf ; qÞsin qdf dq :
(7)
Sðf ; qÞcos qdf dq
0
3. Characterisation of the offshore wave energy potential The WAM model grid nodes nearest to the Galician shoreline – 18 points (Fig. 1) whose coordinates are shown in Table 1 – were selected to characterise the wave energy potential. The threehourly values of significant wave height, peak period, and mean wave direction within the period 1996–2005 were analysed for each point. To this end, the joint (Hs, Tp) distribution was discretised considering eleven significant wave height intervals and similarly eleven peak period intervals (Table 2), leading to 121 combined intervals. Ascribing each three-hourly sea state to the appropriate interval, the percentage of the total time in an average year corresponding to the different intervals was obtained. For illustration Table 2 shows the results for grid point 1043074.
G. Iglesias et al. / Renewable Energy 34 (2009) 2323–2333
2327
Fig. 2. Wave energy potential offshore Galicia.
A similar analysis was carried out combining mean wave direction and significant wave height. Eight sectors were considered for the mean wave direction (N, NE, E, SE, S, SW, W and NW). With the same significant wave height intervals as before, 88 combined intervals of the (Hs, qm) distribution ensued. The sea states in the period 1996– 2005 were ascribed to these intervals and the corresponding time percentages computed (Table 3 for grid point 1043074). For the computation and characterisation of wave energy at each point, the wave spectra were assumed to hold during the lapse between consecutive data, i.e. 3 h. The wave energy in the sea states of each of the combined (Hs, Tp) and (Hs, qm) intervals in the 1996–2005 period was calculated and referred to a one-year period to obtain the value in an average year; the total annual wave energy was obtained as the sum of all the intervals. This procedure was repeated for each point; Table 4 shows the results of the (Hs, Tp)
analysis at point 1043074, with wave energy data expressed in MWh per unit width of wave front. The table also shows the percentage of the total energy corresponding to each interval. The annual wave energy was found to range between 128.59 MWh/m and 438.89 MWh/m; the average wave power varied from 14.68 kW/m to 50.10 kW/m (Table 5). To better visualise the variation of wave energy, it is plotted as a colour band offshore the Galician coasts in Fig. 2.1 It is apparent that Galician waters may be divided into two regions: the first covers most of the coastline, from its south-western corner to Cape Estaca de Bares, its northernmost point; the second is much shorter, from Cape Estaca
1 For interpretation of the references to colour in the text, the reader is referred to the web version of this article.
2328
G. Iglesias et al. / Renewable Energy 34 (2009) 2323–2333
N
30
% wave energy
40%
NW
25
NE
W
E
% total energy
20%
20
15
10
5
SE
SW
0
20
Tp (s)
S
Fig. 5. Percentage of total wave energy vs. peak wave period at point WANA 1043074. Fig. 3. Percentage of total wave energy vs. mean wave direction at point WANA 1043074.
de Bares to the north-eastern end. Throughout the first region the annual wave energy exceeds 250 MWh/m, with the stretches between Cape Finisterre and Cape San Adria´n and between Cape Ortegal and Cape Estaca de Bares displaying values in the order of 400 MWh/m. Incidentally, the section between Cape Finisterre and Cape San Adria´n is known as the Costa da Morte, or ‘Death Coast’, a reference to the many shipwrecks that occurred there. Its high wave energy potential is down to the situation of this coastal stretch at the corner of the region, itself a corner of the Iberian Peninsula, and to the general SW–NE orientation of the coastline, which results in this area being exposed to ocean swells from the widest range of directions. However, and although all the sectors from the SW to the NE provide a non-negligible share of the total wave energy, the lion’s share is supplied by westerly and northwesterly waves generated in the North Atlantic by eastward travelling low pressure centres. This is apparent in Fig. 3, obtained from the data at grid point 1043074, which may be used as a reference for this area. More than 50% of the annual wave energy is provided
by mid-height waves, with significant wave heights between 2 and 5 m (Fig. 4), because higher waves, albeit more energetic – wave energy density increases with the square of the wave height (e.g. [19]) – occur only very seldom. With regard to the wave period, swells with peak periods between 12 and 18 s accounted for 74% of the total wave energy (Fig. 5). The reason is twofold: (i) deepwater wave power is linearly related to wave period, and (ii) lower periods tend to be associated with smaller wave heights. Also in this first region, between Cape Ortegal and Cape Estaca de Bares, lies the other very energetic area, with annual wave energy figures of the same order. Although the intermediate stretch from Cape San Adria´n to Cape Ortegal has slightly lower values (approx. 350 MWh/m), it presents certain advantages for installing a wave energy operation that are discussed below. South of Cape Finisterre the coastline changes to a NNW–SSE orientation. This fact and the Cape itself afford protection from
N 20
NW
18
60% 40%
% wave energy NE
16
20%
% total energy
14 12 10
E
W
8 6 4 2 0
SE
SW 10
Hs (m) Fig. 4. Percentage of total wave energy vs. significant wave height at point WANA 1043074.
S Fig. 6. Percentage of total wave energy vs. mean wave direction at point WANA 1052075.
G. Iglesias et al. / Renewable Energy 34 (2009) 2323–2333
NW
35
% wave energy
60%
30
NE
40%
25
20% E
W
% total energy
N
2329
20 15 10 5
SE
SW
0
20
Tp (s)
S
Fig. 9. Percentage of total wave energy vs. peak wave period at point WANA 1046074.
Fig. 7. Percentage of total wave energy vs. mean wave direction at point WANA 1046074.
4. Additional considerations northerly and north-easterly storms, thereby reducing the annual wave energy to some 300 MWh/m. Finally the second region, east of Cape Estaca de Bares, is sheltered from westerly and south-westerly swells by the coastline configuration – in other words, it loses the prime position on the corner of the Iberian Peninsula. As a result, the annual wave energy decreases below 200 MWh/m, and the average wave power below 25 kW/m. Taking point WANA 1052075 as a reference, the main directions in terms of wave energy are NW, which accounts for more than 50%, followed at some distance by N, NE and W (Fig. 6). More than 50% of the energy is provided by waves with significant wave heights between 1 and 3 m, significantly lower than in the first region, with peak periods between 12 and 18 s.
25
% total energy
20
15
Leaving aside shoreline wave energy converters for the reasons exposed above, we will focus in the following on devices that are installed at a certain distance from the coastline. While waves propagate in the high seas (in deepwater) they are unaffected by the sea bottom. However, as they travel towards the shoreline they eventually reach a point from which the seabed starts to affect their propagation through refraction, shoaling and bottom friction. This threshold defining the change between deepwater and intermediate or transitional water depths is not the same for all waves but depends on their length, or period (e.g. [19]). From this point onwards, waves dissipate part of their energy as a result of their interaction with the seabed. For this reason, wave energy is, generally speaking, greater in deepwater – although on certain bathymetries refraction may lead to local concentrations of energy for certain wave directions and periods. Nonetheless, wave energy converters must be located in relative proximity to the shoreline due to practical reasons, among which the water depth limits imposed by the anchoring or the foundations, as the case may be, and the cost of the submarine cable connecting the devices to the electrical grid onshore. Thus, the optimum location of a wave farm is a compromise in which the technology of the wave energy converters to be deployed, the coastline shape and the bottom slope and nature play a major role. For instance, a converter requiring a fixed foundation in the form of piles driven into the sea bottom will in principle be located in smaller depths than a floating device. Similarly where the bottom slope is very low, a smaller water depth may be accepted in order to reduce the cost of the submarine cable.
10
Table 6 Most energetic intervals of significant wave height, peak period and mean wave direction at WAM model grid point 1046074.
5
0
10
Hs (m) Fig. 8. Percentage of total wave energy vs. significant wave height at point WANA 1046074.
Denomination
Hs (m)
Tp (s)
qm ( )
% Energy
% Time
1 2 3 4 5
1–3 2–4 3–5 4–6 6–8
10–12 12–14 14–16 16–18 16–18
292.5–337.5 292.5–337.5 292.5–337.5 292.5–337.5 292.5–337.5
9.22 18.99 10.71 12.08 9.69
21.62 16.53 4.34 2.63 1.1
2330
G. Iglesias et al. / Renewable Energy 34 (2009) 2323–2333
Table 7 Wave cases propagated by means of the SWAN nearshore wave model, and weighing coefficient (a) for computation of the average wave power. Wave case
Hs (m)
Tp (s)
qm
1 2 3 4 5
2 3 4 5 7
11 13 15 17 17
315 315 315 315 315
a (NW) (NW) (NW) (NW) (NW)
0.4678 0.3576 0.0939 0.0569 0.0238
In addition to these technological and geophysical factors, environmental and human aspects must also be pondered. The first include the preservation of valuable biological areas, such as marine reserves or natural parks, and in general the minimisation of the impact to the marine environment. With regard to human factors, a commercial wave array park should be located clear of fishing or aquaculture areas, marine archaeological sites and areas of military interest. While shipping lanes should be avoided, the proximity of a port is not disadvantageous per se, as it reduces the navigation time necessary to access the wave farm and thereby helps to curb maintenance costs. In this respect it may be of interest to note that wave energy converters are to operate in the harsh marine environment, and maintenance costs may reasonably be expected to play an essential role in the economic viability of the project. The optimum situation would appear to be that in which a port with the facilities for servicing and/or repairing the converters – especially in the case of devices that are not well suited to in situ maintenance – is located not far away from the wave energy operation, while at the same time there exists a safety distance between the wave farm and the shipping lanes. What this safety distance should be is to be assessed in view of the port traffic and the wave energy conversion technology in question – the risk of a wave energy converter drifting away is not the same in the case of an anchored converter than in a bottom-fixed installation. With regard to the type of facility required for the maintenance, it also depends on the kind of converter. Generally speaking, a small fishing harbour is not likely to be sufficient; some converters may even need a fully-fledged dry dock in a shipyard.
The socioeconomic aspects involved in the installation and operation of a wave farm should not be disregarded, as the public acceptance of the project may hold the key to its approval. Regions with a strong fishing and aquaculture tradition, such as Galicia, may be particularly sensitive as fishermen may tend to view a wave farm project as detrimental to their interests. The socioeconomic benefits of a wave farm, such as the local employment opportunities related to its installation and operation, should naturally be presented to the public along with the measures adopted to ensure that the project does not harm the marine environment nor the livelihood and lifestyle of the local residents. The previous analysis has identified two areas offshore the Galician coasts with a particularly energetic wave climate: from Cape Finisterre to Cape San Adria´n and from Cape Ortegal to Cape Estaca de Bares. These sections have nonetheless certain downsides as regards the installation and operation of a wave farm. To begin with, both are near important shipping lanes, connecting the Mediterranean and the South Atlantic with Northern Europe and the Bay of Biscay. A second drawback lies in their distance to any major port where wave energy converters can be serviced – within a range of 40 km there are only small fishing harbours. Finally, and with regard to the stretch from Cape Finisterre to Cape San Adria´n, a large aquaculture operation producing turbot is located in Lires, immediately north of Cape Finisterre. Not that a wave farm would necessarily interfere with this operation – but its presence would be likely to make the wave energy project a more sensitive topic from the political standpoint. On the other hand, between Cape San Adria´n and Cape Ortegal (Fig. 2) lies a section subject to a wave climate nearly as energetic as that in the two areas referred to above and with the benefit of a greater proximity to the Rı´a del Ferrol and its naval facilities – this ria harbours a major commercial port (Ferrol) and two large shipyards, among other facilities. A further advantage of this area is the absence of aquaculture operations of importance. Moreover, if the wave energy converters were to be built in any of the shipyards in the Rı´a de Ferrol, the benefits to the local economy would undoubtedly be welcome.
Fig. 10. Bathymetry of the coastal section between Cape San Adria´n and Cape Ortegal.
G. Iglesias et al. / Renewable Energy 34 (2009) 2323–2333
x 106
4.86
4.85
4.85
4.84
4.84
Northing (m)
Northing (m)
4.86
4.83 4.82
4.82 4.81
4.8
4.8
5
5.1
5.2
5.3
5.4
5.5
5.6
5.7
Easting (m)
5.8 x 105
Fig. 11. Computational grid for the SWAN model application.
5. Nearshore wave power between Cape San Adria´n and Cape Ortegal Based on the previous ideas, the stretch from Cape San Adria´n to Cape Ortegal (Fig. 2) was selected as a promising area for a wave energy operation. The data at point 1046074 of the WAM model grid (Fig. 1), located approximately midway between Cape San Adria´n and Cape Ortegal, may be used as the offshore reference for the area. With an annual wave energy of w350 MWh/m, the annual output of a wave energy converter capturing the power of 50 m of wave front with an efficiency of 20% would be w3500 MWh. The output of a wave farm with 10 converters would be sufficient to supply about 1500 homes with a typical consumption of 2000 kWh per month. 53% of this wave energy would be provided by northwesterly waves; westerly and northerly waves are of less relevance in the area, whereas all the other sectors are negligible due to the
x 106
4.83
4.81
4.79
2331
4.79
5
5.1
5.2
5.3
5.4
Easting (m)
5.5
5.6
5.7
5.8 x 105
Fig. 13. Mean wave direction between Cape San Adria´n and Cape Ortegal for case 3 (offshore wave spectrum with Hs ¼ 4 m, Tp ¼ 15 s, mean wave direction NW: qm ¼ 315 ).
coastline configuration (Fig. 7). The predominance of a single wave direction is advantageous from the standpoint of the wave farm operation. As for the wave heights and periods, more than 50% of the total wave energy would be supplied by waves with significant wave heights between 2 and 5 m (Fig. 8), and approx. 80% of the energy would correspond to waves with peak periods between 12 and 18 s (Fig. 9). In order to choose the optimum locations for a wave farm within this area it is important to bear in mind that, although the offshore wave energy potential is known from the previous analysis, the processes affecting waves as they propagate towards the shoreline – principally refraction, shoaling, bottom friction and, in some cases, diffraction – may modify the wave energy potential, giving rise to local enhancements or reductions of the wave energy in the water depth ranges where a wave farm can be installed. To quantify
Fig. 12. Significant wave height between Cape San Adria´n and Cape Ortegal for case 3 (offshore wave spectrum with Hs ¼ 4 m, Tp ¼ 15 s, mean wave direction NW: qm ¼ 315 ).
2332
G. Iglesias et al. / Renewable Energy 34 (2009) 2323–2333
Fig. 14. Wave power between Cape San Adria´n and Cape Ortegal for case 3 (offshore wave spectrum with Hs ¼ 4 m, Tp ¼ 15 s, mean wave direction NW: qm ¼ 315 ).
these processes and thus select the optimum locations, the SWAN nearshore wave model [15,16] was used to propagate a number of wave cases from deepwater into the area. Like its offshore counterpart, the WAM model, the SWAN model solves the spectral wave action balance equation by means of a finite-difference scheme. With the objective of selecting the wave cases to propagate, a number of intervals in the joint distribution of spectral wave parameters (Hs, Tp, qm) at grid point 1046074 were considered; the length of each interval was set at DHs ¼ 2 m, DTp ¼ 2 s, and Dqm ¼ 45 . The five most energetic intervals (Table 6) represented 46.22% of the time and 60.69% of the total wave energy; the mean wave direction was in all the five north-westerly. Based on this information, five wave cases were defined for propagation taking the mid-value of the corresponding parameter (Table 7). A JONSWAP [20] irregular wave spectrum was assumed, with a peak enhancement factor g ¼ 3.3.
The bathymetry of the area (Fig. 10) was digitised from the nautical charts 928, 929 and 930 of the Spanish Navy Hydrographic Office. The computations were carried out on a Cartesian grid (Fig. 11) with a 200 200 m resolution, its x-axis aligned in a N 40 E direction. The grid had up to 431 cells in the alongshore (x) direction and 247 in the cross-shore (y) direction, extending 86.2 km and 49.4 km respectively. For illustration, the main results of the propagation are shown for one of the wave cases (Case 3) in Figs. 12 (significant wave height), 13 (mean wave direction) and 14 (wave power). It is apparent that in certain areas the wave height is increased, or reduced, relative to its offshore value due to the local bathymetry – and so is the wave power. In the rias, semi-enclosed bodies of water well protected from the open sea, the wave power is much lower than on the exposed coastline, as expected. The sheltering effect of Cape San Adria´n is also apparent in Figs. 12 and 14.
Fig. 15. Average wave power between Cape San Adria´n and Cape Ortegal.
G. Iglesias et al. / Renewable Energy 34 (2009) 2323–2333
Finally, the average wave power of the five cases – the weighing coefficient (a) being the corresponding share of the time (Table 7) – is presented in Fig. 15. From an offshore value of w70 kW/m, the average wave power increases significantly in certain areas; in the two zones marked in the figure (Zones A and B) it reaches 135 kW/ m, almost 100% more. Conversely, in the areas sheltered by the coastline configuration, such as the lee of Cape San Adria´n or the rias, the wave power decreases below 40 kW/m. Although both zones have a similar average wave power, they are quite different with respect to two major aspects: water depth and distance to the shoreline. Zone A, with an area of approx. 600 m 2000 m, is some 1.7 km offshore, and the average water depth varies between 22 m and 28 m. By contrast, Zone B extends approx. 400 m 1000 m, is more distant from the shoreline, w8 km, and has an average water depth of 40–50 m. Both zones are far away from any aquaculture operation, and the shipping routes around the NW corner of the Iberian Peninsula pass well offshore. Zone A is very close to the shipyards and port facilities in the Rı´a del Ferrol, without for as much interfering with the entrance channel. In principle the choice would hinge on the particular wave energy conversion technology to be deployed, although the higher cost of the submarine connection and greater distance to the port of Ferrol may be expected to weigh against Zone B. 6. Conclusions Wave energy has a number of significant advantages with respect to other renewable energy sources – predictability, abundance, high load factor and low environmental impact, among others. Its late beginning relative to other CO2-free energy sources is down to the technological challenges that it poses. In addition to developing commercially viable converters, the resource characterisation is a crucial point towards the exploitation of wave energy. The wave climate in Galicia, NW Spain, is among the harshest in Europe. In this work its potential for energy production was assessed based on a three-hourly data set covering the period 1996–2005, computed by means of a third generation ocean wave model (WAM). Out of a model grid covering the whole North Atlantic, the 18 points closest to the Galician shoreline were selected. From the wave energy density spectra at these points, the annual wave energy and average wave power were computed. The total wave energy was found to range from 128.59 MWh/m to 438.89 MWh/m in an average year, whereas the average wave power varied between 14.68 kW/m and 50.10 kW/m. With the exception of a relatively short section on the north-eastern corner of the region, east of Cape Estaca de Bares, the annual wave energy is above 250 MWh/m throughout the region, and the average wave power above 30 kW/m. Two areas were identified as those with the highest annual energy: from Cape Finisterre to Cape San Adria´n, and from Cape Ortegal to Cape Estaca de Bares; both have approx. 400 MWh/m. The intermediate stretch from Cape San Adria´n and Cape Ortegal has approx. 350 MWh/m. It may be concluded that Galicia has indeed a significant potential for wave energy exploitation. Moreover, the wave climate was studied in order to characterise the sea states behind the wave energy available at each grid point. It was found that in the area between Cape Finisterre and Cape San Adria´n more than 50% of the energy was provided by swells with significant wave heights between 2 m and 5 m and peak periods between 12 s and 18 s; the two main wave directions from the standpoint of wave energy were W and NW. East of Cape San Adria´n the main direction was NW, with westerly swells losing importance due to the coastline configuration. When choosing the location of a wave farm, the wave energy potential is not the only aspect to be heeded. The proximity to a port with facilities for servicing and repairing the wave energy
2333
converters, the non-interference with major shipping routes or navigation channels into ports, and the minimisation of the impact to the marine environment and, in particular, fishing and aquaculture areas are also major considerations. On these grounds the coastal stretch between Cape San Adria´n and Cape Ortegal was selected. The nearshore wave power in this area was studied in order to identify the optimum locations for a wave farm. From the analysis of the offshore wave climate, five wave cases representing 46.22% of the time and 60.69% of the wave energy were chosen. The propagation of these cases into the area was computed by means of the SWAN nearshore wave model. It was found that, although the average wave power is w70 kW/m in most of the area, this figure increases to 135 kW/m in two zones (A and B) and falls below 40 kW/m in others. It may be concluded that the modifications of the wave power in the nearshore due to refraction, shoaling, bottom friction and, in some cases, shelter by the shoreline should be carefully analysed before deciding on the wave farm location, as a displacement of some hundreds of metres may either increase or decrease its output significantly. Acknowledgements The authors are indebted to Spain’s State Ports (Puertos del Estado) for supplying the WAM model data set. During this work R. Carballo has been supported by the FPU grant AP2006-03891 of the Spanish Ministry of Education and Science. References [1] Falnes J, Lovseth L. Ocean wave energy. Energy Policy 1991;19(8):768–75. [2] Duckers L. Wave energy. In: Boyle G, editor. Renewable energy. Oxford University Press [chapter 8]. [3] Cle´ment A, McCullen P, Falcao A, Fiorentino A, Gardner F, Hammarlund K, et al. Wave energy in Europe: current status and perspectives. Renewable and Sustainable Energy Reviews 2002;6(5):405–31. [4] Holthuijsen LH. Waves in oceanic and coastal waters. Cambridge University Press; 2007. [5] Henfridsson U, Neimane V, Strand K, Kapper R, Bernhoff H, Danielsson O, et al. Wave energy potential in the Baltic Sea and the Danish part of the North Sea, with reflections on the Skagerrak. Renewable Energy 1997;32:2069–84. [6] Tedd J. Testing, analysis and control of the wave dragon wave energy converter. Ph.D. thesis, DCE thesis no. 9. Denmark: Aalborg University; 2007, ISSN: 1901-7294. [7] Rulla J. A-priori estimates for the optimal control of an oscillating water column. International Journal of Engineering Science 1993;1:77–84. [8] Morris-Thomas MT, Irvin RJ, Thiagarajan KP. An investigation into the hydrodynamic efficiency of an oscillating water column. Journal of Offshore Mechanics and Arctic Engineering 2007;129:273–8. [9] Josset C, Clement AH. A time-domain numerical simulator for oscillating water column wave power plants. Renewable Energy 2007;32(8):1379–402. [10] Carcas MC. The OPD Pelamis WEC: current status and onward programme. International Journal of Ambient Energy 2003;24(1):21–8. [11] Nielsen K, Plum C. Point absorber – numerical and experimental results. In: Proceedings of the 4th European wave power conference, Aalborg, Denmark, paper H2; 2002. [12] Pontes MT, Aguilar R, Oliveira Pires H. Nearshore wave energy atlas for Portugal. Journal of Offshore Mechanics and Arctic Engineering 2005;127: 249–55. [13] Bernhoff H, Sjo¨stedt E, Leijon M. Wave energy resources in sheltered sea areas: a case study of the Baltic Sea. Renewable Energy 2006;31(13):2164–70. [14] Hasselmann K. The WAM model – a 3rd generation ocean wave prediction model. Journal of Physical Oceanography 1988;18(12):1775–810. [15] Booij N, Ris RC, Holthuijsen LH. A third-generation wave model for coastal regions – 1. Model description and validation. Journal of Geophysical Research – Oceans 1999;104(C4):7649–66. [16] Ris RC, Booij N, Holthuijsen LH. A third-generation wave model for coastal regions – 2. Verification. Journal of Geophysical Research – Oceans 1999; 104(C4):7667–81. [17] Cats G, Wolters L. The HIRLAM project. IEEE Computational Science & Engineering 1996;3(4):4–7. [18] Whitham GB. Linear and nonlinear waves. Wiley-Interscience; 1999. [19] Dean RG, Dalrymple RA. Water wave mechanics for engineers and scientists. Wiley-Interscience; 1990. [20] Hasselmann DE. Directional wave spectra observed during JONSWAP 1973. Journal of Physical Oceanography 1980;10(8):1264–80.
