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Wave power for La Isla Bonita
Energy 35 (2010) 5013e5021
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Wave power for La Isla Bonita G. Iglesias*, R. Carballo Univ. of Santiago de Compostela, Hydraulic Eng., EPS, Campus Univ. s/n, 27002 Lugo, Spain
a r t i c l e i n f o
a b s t r a c t
Article history: Received 31 March 2010 Received in revised form 12 August 2010 Accepted 14 August 2010
The island of La Palma (Spain), dubbed La Isla Bonita for its beauty, is a UNESCO Biosphere Reserve in the Atlantic Ocean. The island’s authorities are aiming for energy self-sufficiency based on wave energy and other renewables. In this research its wave resource is investigated using a 44-years hindcast dataset obtained through numerical modelling and validated with wave buoy records. First, its distribution around La Palma is studied. Significant variations are found, with the largest resource occurring off the north and northwest coasts; the northwest presents operational advantages (proximity to a port). Second, the seasonal variations in this area are studied. Wave energy is provided essentially by powerful NNW-NW swells in winter and autumn, by less energetic NNE-N waves in summer and spring. Finally, the resource is characterised in terms of sea states; it is found that the bulk of the energy is provided by waves between 9.5 s and 13.5 s of energy period and 1.5 m and 3.5 m of significant wave height, so the selection of the Wave Energy Converters to be installed should guarantee maximum efficiency in these ranges. Ó 2010 Elsevier Ltd. All rights reserved.
Keywords: Wave energy Wave power Wave model Atmospheric model Numerical model La Palma
1. Introduction The Canary Islands (Spain) are an archipelago of volcanic islands in the Atlantic Ocean, off the African coast (27.5 N e 29.5 N, 013 W e 018.5 W) (Fig. 1). La Palma, with an area of 706 km2, is the second smallest island of the group. Its physical geography is remarkable. A large part of the island is occupied by the Caldera de Taburientedwhich, incidentally, gave name to this volcanic feature in the geological vocabulary. This caldera has a diameter of approx. 9 km and a depth of 1500 m relative to the surrounding mountains; its inner part, which can only be reached by hiking through a deep canyon, is a national park. However, it is not only the physical geography of La Palma that earned it the name of La Isla Bonita (the beautiful island). Its fauna and flora are also remarkable, with a host of endemic species; this is attested by the island’s status as a UNESCO Biosphere Reserve. La Palma is aiming for energy self-sufficiency. A framework project to this effect has been passed by the island’s authoritiesdand wave energy is part of it. Developing wave energy in La Palma makes sense for several reasons. First, the resource is substantial (as shown below), the main reason being that La Palma, as the most northwestern island of the Canary Islands, is directly exposed to the energetic IV quadrant swellseswells generated over
* Corresponding author. Tel.: þ34 982 285900; fax: þ34 982 285926. E-mail address: [email protected] (G. Iglesias). 0360-5442/$ e see front matter Ó 2010 Elsevier Ltd. All rights reserved. doi:10.1016/j.energy.2010.08.020
the long Atlantic fetch by the westerlies prevailing in the midlatitudes. Second, its high altitudes (culminating at 2423 m) allow for energy storage by means of water reservoirs; the variability inherent to the wave resource can thus be absorbed. Third, the power grid of La Palma is isolated by the surrounding water depths. This is due to the volcanic origin of the Canary Islands and the corresponding lack of continental shelfdLa Palma is a 7 km high structure with its base on the ocean floor, in water depths exceeding 4000 m. Finally, the goal of energy self-sufficiency is made easier in La Palma by its relatively small population (85,000). In addition to its wave resource, the subject of this research, La Palma has also a significant wind and solar resource; the goal of the island’s authorities is to create a 100% renewable energy system by integrating the three resources. A 100% renewable energy system was investigated by [1], and the integration of wave, wind and PV power was analysed by [2e4]. Assessments of the wave resource range from the global perspective [5,6] to the European [7,8] or national leveldSpain [9e13], Portugal [14e18], and other countries. The present research deals with the wave resource in La Palma. Section 2 presents the material and methods: the atmospheric and wave models used to obtain the hindcast dataset (2.1), the procedure used to compute wave power at the study sites (2.2), and the validation of the dataset with wave buoy data (2.3). Results are presented and discussed in Section 3, which is divided into three subsections: the area with the highest potential for a wave farm is determined in 3.1; the seasonal variations of the resource in that area are analysed in 3.2; finally, the sea states composing the
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G. Iglesias, R. Carballo / Energy 35 (2010) 5013e5021 29.5 LA PALMA
Lanzarote
Latitude (º)
29
Fuerteventura
Tenerife
28.5
CGP
WB
28
El Hierro
La Gomera
Morocco Gran Canaria
27.5
Western Sahara
-19
-18
-17
-16
-14
-15
-13
Longitude (º)
Fig. 1. Map of the Canary Islands showing the location of the seven study sites around La Palma, the wave buoy (WB) and closest grid point (CGP) used for validating the hindcast dataset.
resource, their different contributions to the total annual energy, and how this should be taken into account in the selection of Wave Energy Converters (WECs) for La Palma is discussed in 3.3. The article is closed by Section 4, Conclusions.
a system moving with the current). The WAM model solves the spectral action balance equation:
v v v v v S ðNÞ þ ðcx NÞ þ cy N þ ðcq NÞ þ ðcs NÞ ¼ ; s vt vx vy vs vq
2. Material and methods
where cx and cy are the propagation velocity components in the xand y-space, respectively; cq is the propagation velocity in the q-space; cs is the propagation velocity in the s-space; and S¼S(s,q) represents sources or sinks of wave energy. The physical meaning of the terms on the left-hand side of Equation (2) is straightforward: the first term represents the local rate of change of action density in time, the second and third terms represent propagation of action in geographic space, the fourth term represents depthinduced and current-induced refraction, and the fifth term represents shifting of the relative frequency due to variations in depth and currents.
2.1. Atmospheric and wave models Given that there are no wave buoys in the vicinity of La Palma, the wave resource assessment was based on hindcast data obtained through numerical modelling, integrating a high-resolution atmospheric model and a wave model. Both models were run on a grid that covered the North Atlantic with a resolution of 0.5 0.5 , enhanced near the coastlines to 0.25 0.25 . The atmospheric model, REMO, solved not only the large-scale flow but also the smaller-scale effects associated with the topography of land masses using a spectral nudging technique [19]; it was forced with data from the global atmospheric reanalysis carried out by the U.S. National Center for Environmental Prediction, Washington, D.C., USA (NCEP) and the National Center for Atmospheric Research, Boulder, Colorado, USA (NCAR) integrating satellite and instrumental data [20]. The result was a high-resolution atmospheric dataset which was in turn used to force the spectral wave model WAM cycle 4 [21,22]. WAM is a third-generation wave model, i.e. no particular shape is assumed for the wave spectrum, which is free to evolve according to the energy sources and sinks. For convenience, a brief description of WAM is given here; further details may be found in [23e26]. The model is based on spectral action density because, unlike energy density, action density is conserved in the presence of currents [27]. Action density is defined as
Nðs; qÞ ¼
Eðs; qÞ
s
;
(2)
2.2. Computation of wave power As a result of the volcanic origin of La Palma, the seven study sites (Fig. 1) are located in deepwater, so wave fields are unaffected by refraction or shoaling [26,28]. It follows that wave power may be computed directly from the results of the WAM model (without running a coastal wave model). Wave power is given [29] by:
J ¼
rg2 2 Te Hm0 ; 64p
(3)
where Te is energy period, Hm0 is significant wave height, r is seawater density, and g is gravitational acceleration. The (spectral) significant wave height is defined as
(1)
1
Hm0 ¼ 4ðm0 Þ2 ;
E ¼ E(s,q) is the energy density, with q the propagation direction and s the relative radian frequency (i.e. the radian frequency in
(4)
where m0 is the zeroth moment (the variance) of the wave spectrum. In general, the nth spectral moment is given by
Table 1 Wave height, power and energy statistics at the study sites [Hm0, significant wave height; J, power per metre of wave front; (E)annual, total annual energy per metre of wave front]. Site No.
Latitude, Longitude
(Hm0)mean std. dev.(m)
S1 S2 S3 N1 N2 N3 N4
28.5 N, 18.0 W 28.25 N, 17.75 W 28.5 N, 17.5 W 28.75 N, 18.25 W 29.0 N, 18.0 W 29.0 N, 17.75 W 28.75 N, 17.5 W
1.50 1.71 1.80 2.07 2.14 2.11 1.99
0.76 0.65 0.71 0.85 0.87 0.87 0.79
(Hm0)max(m)
Jmean(kW/m)
Jmax(kW/m)
(E)annual(MWh/m)
10.1 9.4 7.8 10.3 10.0 9.3 8.5
15.92 15.99 18.76 27.36 28.46 27.84 24.04
671.1 589.1 437.9 698.0 677.2 672.8 573.3
139.6 140.2 164.5 239.9 249.5 244.0 210.7
G. Iglesias, R. Carballo / Energy 35 (2010) 5013e5021
N2
29.1
5015
N3
29 3000m
28.9
Pt. del Mundo
1000m
N1
N4
500m 2000m
Pt. Cumplida
28.8
Latitude (º)
Pt. del Aserradero
LA PALMA
28.7
Pt. Salinas
Puerto de Tazacorte
S3
28.6
S1
28.5
Pt. de Fuencaliente
28.4
2000m
28.3 S2 28.2 −18.3
−18.2
−18.1
−18
−17.9
−17.8
−17.7
−17.6
−17.5
−17.4
Longitude (º) Fig. 2. Map of La Palma with the annual wave roses for the study sites.
Z2p ZN mn ¼ 0
f n Eðf ; qÞdf dq;
(5)
0
where f is wave frequency and E ¼ E(f,q) is energy density (e.g. [26]). As regards the energy period, it represents the period of a sinusoidal wave with the same energy as the sea state and is defined as a function of the spectral moments:
Te ¼
m1 ; m0
(6)
Among the various characteristic values of the wave period of a sea state (peak period, significant period, mean period, etc.), the energy period is normally used for energy studies because it weights waves according to their spectral energy content.
Fig. 3. Hindcast data (..) vs. wave buoy measurements (dd) from 1 January to 30 December 2001. [Hm0, significant wave height; J, power per metre of wave front].
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G. Iglesias, R. Carballo / Energy 35 (2010) 5013e5021
Fig. 4. Distribution of mean wave power around La Palma.
Fig. 5. Distribution of annual wave energy around La Palma.
G. Iglesias, R. Carballo / Energy 35 (2010) 5013e5021
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Fig. 6. Annual wave power roses at sites N1 e N4 (high-energy area) [J, power per metre of wave front].
2.3. Validation of hindcast data with wave buoy measurements The hindcast dataset thus obtained covers a 44-year period, from 1 January 1958 to 30 December 2001. As there are no wave buoys in the vicinity of La Palma, the wave buoy near Gran Canaria was used for validation; its measurements were compared with the hindcast data corresponding to the closest grid point (Fig. 1). The validation period included 54 months of data, from 20 June 1997 at 21:00 UTC to 30 December 2001 at 12:00 UTC. Very good agreement was found (Fig. 3), with correlation coefficients of RH ¼ 0.8243 (significant wave height) and RJ ¼ 0.8121 (wave power) over the whole period. The last 12 months, from 1 January 2001 to 30 December 2001, are shown in Fig. 3 (the whole validation period is not depicted for the sake of clarity). 3. Results 3.1. Area with the largest wave resource Apart from the data used in the previous section for validating the hindcast dataset, the data used in the present research correspond to the seven grid points closest to La Palma (Fig. 1). Their
main wave height, power and energy statistics are shown in Table 1. The last column, total annual energy, is referred to an average year (the average of the 44 years in the dataset). It is apparent from the figures in the table that the study sites can be classified into two groups or areas: a high-energy area to the north (N1 to N4) and a low-energy area to the south (S1 to S3). The explanation for the difference between the two areas is straightforward: northerly waves (from NW to NE) prevail in the Canary Islands region, and the north of La Palma is fully exposed to them; in contrast, the south is sheltered by the island itself (Fig. 2). As for the differences within each area, they are clearly related to the position of each site relative to the island. Within the low-energy area the most sheltered are S1 and S2, hence they are also the least energetic. Within the high-energy area the most exposed are N2 and N3; in any case, their differences with N1 are minor (less than 2% in terms of annual energy), so the area with the largest wave resource is the north and northwest of the island. These geographical variations around the island are represented in Fig. 4 (mean wave power) and Fig. 5 (total annual energy). The wave roses in Figs. 6 and 7, for the high-energy and lowenergy areas, respectively, have a colour scale graded according to wave power. Focusing on the high-energy area (Fig. 6) it is clear that
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G. Iglesias, R. Carballo / Energy 35 (2010) 5013e5021
Fig. 7. Annual wave power roses at sites S1 e S3 (low-energy area) [J, power per metre of wave front].
the largest wave power values correspond to IV quadrant directions, in particular NNW, followed by NW and N (strictly speaking, N waves are 50% IV quadrant, 50% I quadrant); certain directions from the I quadrant (NNE) also have large probabilities of occurrence, but are associated with less energetic waves. This is explained by the Canary Islands’ location near the eastern boundary of the Atlantic Ocean, which results in longer fetch distances along IV quadrant directions, and by the northwesterly winds prevailing in the Atlantic north of the Canary Islands (where the IV quadrant swells in Fig. 6 are generated). The lower wave power values of I quadrant waves relative to IV quadrant waves account for the lower energy levels of the northeast of La Palma (site N4) relative to the northwest (site N1). For all its importance, the wave resource is not the only issue to consider when selecting the area for a wave power installation. Two other major issues, the construction and operational costs, are influenced by various factors: technological options, financing, public subsidies, taxation, etc. These factors are outside the scope of this work; there is, however, one factor that can be weighed here: proximity to a port. Its importance is obvious if the technological options are centred around offshore Wave Energy Converters. But even if an onshore wave power plant were envisageddwhich is
unlikely given La Palma’s status as a UNESCO Biosphere Reservedthe construction and operational costs would increase with road distance to the nearest port, not least in view of the winding roads of La Palma. While there are no ports along the north of the island, there is one on its west coast: Tazacorte (Fig. 2). On these grounds, the northwest (the area around site N1) has the highest potential for the installation of a wave farm. 3.2. Seasonality of the wave resource Having established the area with the highest potential for a wave farm, the seasonal variations of the resource in this area are considered next. Seasonal wave roses for study site N1 (Fig. 8) indicate that the prevailing wave direction veers from NW-NNW in winter to NNE in summer; the prevailing directions in the intermediate seasons are also intermediate: N in spring, NNW in autumn. Two more facts may be observed in Fig. 8. First, the largest waves occur in winter, followed by autumn; significant wave heights are clearly smaller in spring and summer. Second, there is a correlation between wave height and directiondthe larger wave heights are associated with NW and NNW waves. As indicated, this is a direct result of the long (oceanic) fetch along these directions.
G. Iglesias, R. Carballo / Energy 35 (2010) 5013e5021
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Fig. 8. Seasonal wave height roses at site N1 [Hm0, significant wave height].
In view of these seasonal variations it is clear that, alongside the installation of a wave farm, provisions should be made for storing wave energy. The mountainous nature of La Palma provides an excellent basis for inexpensive energy storage using water reservoirs at altitude. The integration of wave power with other renewable energies will also help to mitigate the effects of its variability.
3.3. Characterisation of the wave resource and WEC selection In the preceding sections the wave resource around La Palma was assessed, the area with the highest potential was determined, and the seasonal variations in this area were investigated. There is a further point of interest with respect to the wave resourcedone that influences the selection of the Wave Energy Converters to be installed. This point concerns the characteristics of the resource in terms of sea states, or in other words, the characteristics of the waves providing the power. There are many different technologies in different degrees of development for transforming this power into electricity [30]. Each technology has different operational ranges, and what is more, different efficiencies under different sea states (e.g. [31]). It follows that the WECs selected should have
Fig. 9. Contribution to the total annual energy of the different sea states at site N1 [Te, energy period; Hm0, significant wave height].
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Table 2 Probability of occurrence of the different sea states at site N1 expressed in number of hours in the average year. [Hm0, significant wave height; Te, energy period]. Hm0(m)
Te(s) <¼2
2e4
4e6
6e8
8e10
10e12
12e14
14e16
16e18
18e20
>20
Total
>10 9e10 8e9 7e8 6e7 5e6 4e5 3e4 2e3 1e2 <¼1
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.3 0.5
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 8.7 381.0 19.6
0.0 0.0 0.0 0.0 0.0 0.0 0.6 20.1 362.7 1323.8 161.0
0.0 0.0 0.0 0.0 0.1 1.6 14.0 96.2 385.9 1584.9 62.5
0.0 0.0 0.0 0.2 2.7 10.4 36.4 147.6 995.1 1259.5 35.3
0.1 0.1 0.6 1.4 4.9 16.8 59.1 284.4 610.4 325.4 12.0
0.0 0.2 0.5 2.4 5.1 17.9 60.2 128.0 131.7 72.0 1.6
0.0 0.0 1.0 1.4 5.8 10.1 22.6 30.6 25.8 11.5 0.1
0.0 0.0 0.0 0.0 0.1 0.6 1.8 4.1 3.5 1.0 0.0
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
0.1 0.3 2.0 5.5 18.7 57.6 194.8 711.0 2524.0 4959.6 292.5
Total
0.0
0.8
409.4
1868.2
2145.2
2487.3
1315.3
419.7
109.1
11.1
0.0
8766.0
maximum efficiency in the ranges of wave heights and periods that provide the bulk of the energy in the area of interest. The contribution of the different sea states to the total annual energy at study site N1, representative of the area with the highest potential, is presented in Fig. 9. Sea states are classified into ‘energy bins’ of 0.5 s 0.5 m (DTe DHm0), the colour of each bin representing its contribution. Wave energy is concentrated between 9.5 s and 13.5 s (energy period) and between 1.5 m and 3.5 m (significant wave height), so the selection of the WECs should aim for maximum efficiency in these ranges. Wave power isolines based on Equation (3) are also depicted in Fig. 9. From these isolines and the colours in the energy bins it is clear that the bulk of the energy is provided by sea states between w15 kW/m and w90 kW/m. At first sight it may seem odd that the most powerful sea states (some of them with wave power values beyond 250 kW/m) contribute so little to the total annual resource; there is, however, a simple explanation: high-power sea states are associated with waves of large heights and periods (Equation (3)), and these have low probabilities of occurrence. For illustration, the probability of occurrence of the different sea states at site N1 is shown in Table 2, expressed in number of hours in the average.
occur in winter, followed by autumn; wave power decays in spring and, especially, summer. Wave directions also present a seasonal pattern: the prevailing direction veers from NW-NNW in winter to NNE in summer. In fact, there is a correlation between wave direction and powerdthe most energetic waves are the NNW-NW swells. These seasonal variations should be taken into account by providing for energy storage alongside the wave power installation; thanks to the high elevations in La Palma, this storage can be achieved by means of water reservoirs at altitude combined with a hydropower scheme. Finally, the resource was characterised in terms of sea states, i.e. significant wave heights and energy periods. It was found that the bulk of the energy in the wave farm area was provided by sea states between 9.5 s and 13.5 s of energy period and 1.5 m and 3.5 m of significant wave height, so the selection of Wave Energy Converters should ensure maximum efficiency in these ranges. In sum, the wave resource in La Palma was assessed using a 44-year hindcast dataset validated with wave buoy measurements; a considerable resource was found in certain areas, which should be put to use to make La Palma’s goal of energy self-sufficiency a reality.
4. Conclusions
Acknowledgements
La Palma is the most northwestern of the Canary Islands, a volcanic archipelago in the Atlantic; dubbed La Isla Bonita for its natural beauty and environmental values, it is a UNESCO Biosphere Reserve. The island’s authorities are aiming for energy self-sufficiency using wave, wind and PV power. This research focused on the wave resource, which was investigated based on a hindcast dataset covering 44 years. This dataset is the result of two numerical modelsda regional atmospheric model and a wave model. For validation the hindcast data were compared with wave buoy data; excellent agreement was found. The wave resource presents significant differences around the islanddit is substantial off its north and northwest coast, but less abundant elsewhere. This is explained by the location of the Canary Islands in the Atlantic Ocean and that of La Palma within the archipelago, which leaves its north and northwest directly exposed to powerful IV quadrant swells; as a result, mean power and annual energy in the area are above 25 kW/m and 220 MWh/m, respectively. Comparing the north and northwest, their energy resource is very similar, but the northwest is nearer to a portdan advantage with respect to the construction and operational costs. Having selected the northwest as the area with the highest potential for a wave farm, the seasonal variations of the wave resource in this area were analysed. The most energetic waves
The authors are grateful to three anonymous reviewers, whose kind suggestions contributed to improve the manuscript. This research is part of the project “Assessment of Renewable Energy Resources” (DPI2009-14546-C02-02) supported by Spain’s Ministry of Science and Innovation (Ministerio de Ciencia e Innovación). Its authors are indebted to Spain’s State Ports (Puertos del Estado), in particular to Dr. I. Rodríguez-Arévalo, Dr. E. Fanjul, Ms. P. Gil and Ms. S. Pérez.
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Wave power for La Isla Bonita G. Iglesias*, R. Carballo Univ. of Santiago de Compostela, Hydraulic Eng., EPS, Campus Univ. s/n, 27002 Lugo, Spain
a r t i c l e i n f o
a b s t r a c t
Article history: Received 31 March 2010 Received in revised form 12 August 2010 Accepted 14 August 2010
The island of La Palma (Spain), dubbed La Isla Bonita for its beauty, is a UNESCO Biosphere Reserve in the Atlantic Ocean. The island’s authorities are aiming for energy self-sufficiency based on wave energy and other renewables. In this research its wave resource is investigated using a 44-years hindcast dataset obtained through numerical modelling and validated with wave buoy records. First, its distribution around La Palma is studied. Significant variations are found, with the largest resource occurring off the north and northwest coasts; the northwest presents operational advantages (proximity to a port). Second, the seasonal variations in this area are studied. Wave energy is provided essentially by powerful NNW-NW swells in winter and autumn, by less energetic NNE-N waves in summer and spring. Finally, the resource is characterised in terms of sea states; it is found that the bulk of the energy is provided by waves between 9.5 s and 13.5 s of energy period and 1.5 m and 3.5 m of significant wave height, so the selection of the Wave Energy Converters to be installed should guarantee maximum efficiency in these ranges. Ó 2010 Elsevier Ltd. All rights reserved.
Keywords: Wave energy Wave power Wave model Atmospheric model Numerical model La Palma
1. Introduction The Canary Islands (Spain) are an archipelago of volcanic islands in the Atlantic Ocean, off the African coast (27.5 N e 29.5 N, 013 W e 018.5 W) (Fig. 1). La Palma, with an area of 706 km2, is the second smallest island of the group. Its physical geography is remarkable. A large part of the island is occupied by the Caldera de Taburientedwhich, incidentally, gave name to this volcanic feature in the geological vocabulary. This caldera has a diameter of approx. 9 km and a depth of 1500 m relative to the surrounding mountains; its inner part, which can only be reached by hiking through a deep canyon, is a national park. However, it is not only the physical geography of La Palma that earned it the name of La Isla Bonita (the beautiful island). Its fauna and flora are also remarkable, with a host of endemic species; this is attested by the island’s status as a UNESCO Biosphere Reserve. La Palma is aiming for energy self-sufficiency. A framework project to this effect has been passed by the island’s authoritiesdand wave energy is part of it. Developing wave energy in La Palma makes sense for several reasons. First, the resource is substantial (as shown below), the main reason being that La Palma, as the most northwestern island of the Canary Islands, is directly exposed to the energetic IV quadrant swellseswells generated over
* Corresponding author. Tel.: þ34 982 285900; fax: þ34 982 285926. E-mail address: [email protected] (G. Iglesias). 0360-5442/$ e see front matter Ó 2010 Elsevier Ltd. All rights reserved. doi:10.1016/j.energy.2010.08.020
the long Atlantic fetch by the westerlies prevailing in the midlatitudes. Second, its high altitudes (culminating at 2423 m) allow for energy storage by means of water reservoirs; the variability inherent to the wave resource can thus be absorbed. Third, the power grid of La Palma is isolated by the surrounding water depths. This is due to the volcanic origin of the Canary Islands and the corresponding lack of continental shelfdLa Palma is a 7 km high structure with its base on the ocean floor, in water depths exceeding 4000 m. Finally, the goal of energy self-sufficiency is made easier in La Palma by its relatively small population (85,000). In addition to its wave resource, the subject of this research, La Palma has also a significant wind and solar resource; the goal of the island’s authorities is to create a 100% renewable energy system by integrating the three resources. A 100% renewable energy system was investigated by [1], and the integration of wave, wind and PV power was analysed by [2e4]. Assessments of the wave resource range from the global perspective [5,6] to the European [7,8] or national leveldSpain [9e13], Portugal [14e18], and other countries. The present research deals with the wave resource in La Palma. Section 2 presents the material and methods: the atmospheric and wave models used to obtain the hindcast dataset (2.1), the procedure used to compute wave power at the study sites (2.2), and the validation of the dataset with wave buoy data (2.3). Results are presented and discussed in Section 3, which is divided into three subsections: the area with the highest potential for a wave farm is determined in 3.1; the seasonal variations of the resource in that area are analysed in 3.2; finally, the sea states composing the
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G. Iglesias, R. Carballo / Energy 35 (2010) 5013e5021 29.5 LA PALMA
Lanzarote
Latitude (º)
29
Fuerteventura
Tenerife
28.5
CGP
WB
28
El Hierro
La Gomera
Morocco Gran Canaria
27.5
Western Sahara
-19
-18
-17
-16
-14
-15
-13
Longitude (º)
Fig. 1. Map of the Canary Islands showing the location of the seven study sites around La Palma, the wave buoy (WB) and closest grid point (CGP) used for validating the hindcast dataset.
resource, their different contributions to the total annual energy, and how this should be taken into account in the selection of Wave Energy Converters (WECs) for La Palma is discussed in 3.3. The article is closed by Section 4, Conclusions.
a system moving with the current). The WAM model solves the spectral action balance equation:
v v v v v S ðNÞ þ ðcx NÞ þ cy N þ ðcq NÞ þ ðcs NÞ ¼ ; s vt vx vy vs vq
2. Material and methods
where cx and cy are the propagation velocity components in the xand y-space, respectively; cq is the propagation velocity in the q-space; cs is the propagation velocity in the s-space; and S¼S(s,q) represents sources or sinks of wave energy. The physical meaning of the terms on the left-hand side of Equation (2) is straightforward: the first term represents the local rate of change of action density in time, the second and third terms represent propagation of action in geographic space, the fourth term represents depthinduced and current-induced refraction, and the fifth term represents shifting of the relative frequency due to variations in depth and currents.
2.1. Atmospheric and wave models Given that there are no wave buoys in the vicinity of La Palma, the wave resource assessment was based on hindcast data obtained through numerical modelling, integrating a high-resolution atmospheric model and a wave model. Both models were run on a grid that covered the North Atlantic with a resolution of 0.5 0.5 , enhanced near the coastlines to 0.25 0.25 . The atmospheric model, REMO, solved not only the large-scale flow but also the smaller-scale effects associated with the topography of land masses using a spectral nudging technique [19]; it was forced with data from the global atmospheric reanalysis carried out by the U.S. National Center for Environmental Prediction, Washington, D.C., USA (NCEP) and the National Center for Atmospheric Research, Boulder, Colorado, USA (NCAR) integrating satellite and instrumental data [20]. The result was a high-resolution atmospheric dataset which was in turn used to force the spectral wave model WAM cycle 4 [21,22]. WAM is a third-generation wave model, i.e. no particular shape is assumed for the wave spectrum, which is free to evolve according to the energy sources and sinks. For convenience, a brief description of WAM is given here; further details may be found in [23e26]. The model is based on spectral action density because, unlike energy density, action density is conserved in the presence of currents [27]. Action density is defined as
Nðs; qÞ ¼
Eðs; qÞ
s
;
(2)
2.2. Computation of wave power As a result of the volcanic origin of La Palma, the seven study sites (Fig. 1) are located in deepwater, so wave fields are unaffected by refraction or shoaling [26,28]. It follows that wave power may be computed directly from the results of the WAM model (without running a coastal wave model). Wave power is given [29] by:
J ¼
rg2 2 Te Hm0 ; 64p
(3)
where Te is energy period, Hm0 is significant wave height, r is seawater density, and g is gravitational acceleration. The (spectral) significant wave height is defined as
(1)
1
Hm0 ¼ 4ðm0 Þ2 ;
E ¼ E(s,q) is the energy density, with q the propagation direction and s the relative radian frequency (i.e. the radian frequency in
(4)
where m0 is the zeroth moment (the variance) of the wave spectrum. In general, the nth spectral moment is given by
Table 1 Wave height, power and energy statistics at the study sites [Hm0, significant wave height; J, power per metre of wave front; (E)annual, total annual energy per metre of wave front]. Site No.
Latitude, Longitude
(Hm0)mean std. dev.(m)
S1 S2 S3 N1 N2 N3 N4
28.5 N, 18.0 W 28.25 N, 17.75 W 28.5 N, 17.5 W 28.75 N, 18.25 W 29.0 N, 18.0 W 29.0 N, 17.75 W 28.75 N, 17.5 W
1.50 1.71 1.80 2.07 2.14 2.11 1.99
0.76 0.65 0.71 0.85 0.87 0.87 0.79
(Hm0)max(m)
Jmean(kW/m)
Jmax(kW/m)
(E)annual(MWh/m)
10.1 9.4 7.8 10.3 10.0 9.3 8.5
15.92 15.99 18.76 27.36 28.46 27.84 24.04
671.1 589.1 437.9 698.0 677.2 672.8 573.3
139.6 140.2 164.5 239.9 249.5 244.0 210.7
G. Iglesias, R. Carballo / Energy 35 (2010) 5013e5021
N2
29.1
5015
N3
29 3000m
28.9
Pt. del Mundo
1000m
N1
N4
500m 2000m
Pt. Cumplida
28.8
Latitude (º)
Pt. del Aserradero
LA PALMA
28.7
Pt. Salinas
Puerto de Tazacorte
S3
28.6
S1
28.5
Pt. de Fuencaliente
28.4
2000m
28.3 S2 28.2 −18.3
−18.2
−18.1
−18
−17.9
−17.8
−17.7
−17.6
−17.5
−17.4
Longitude (º) Fig. 2. Map of La Palma with the annual wave roses for the study sites.
Z2p ZN mn ¼ 0
f n Eðf ; qÞdf dq;
(5)
0
where f is wave frequency and E ¼ E(f,q) is energy density (e.g. [26]). As regards the energy period, it represents the period of a sinusoidal wave with the same energy as the sea state and is defined as a function of the spectral moments:
Te ¼
m1 ; m0
(6)
Among the various characteristic values of the wave period of a sea state (peak period, significant period, mean period, etc.), the energy period is normally used for energy studies because it weights waves according to their spectral energy content.
Fig. 3. Hindcast data (..) vs. wave buoy measurements (dd) from 1 January to 30 December 2001. [Hm0, significant wave height; J, power per metre of wave front].
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G. Iglesias, R. Carballo / Energy 35 (2010) 5013e5021
Fig. 4. Distribution of mean wave power around La Palma.
Fig. 5. Distribution of annual wave energy around La Palma.
G. Iglesias, R. Carballo / Energy 35 (2010) 5013e5021
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Fig. 6. Annual wave power roses at sites N1 e N4 (high-energy area) [J, power per metre of wave front].
2.3. Validation of hindcast data with wave buoy measurements The hindcast dataset thus obtained covers a 44-year period, from 1 January 1958 to 30 December 2001. As there are no wave buoys in the vicinity of La Palma, the wave buoy near Gran Canaria was used for validation; its measurements were compared with the hindcast data corresponding to the closest grid point (Fig. 1). The validation period included 54 months of data, from 20 June 1997 at 21:00 UTC to 30 December 2001 at 12:00 UTC. Very good agreement was found (Fig. 3), with correlation coefficients of RH ¼ 0.8243 (significant wave height) and RJ ¼ 0.8121 (wave power) over the whole period. The last 12 months, from 1 January 2001 to 30 December 2001, are shown in Fig. 3 (the whole validation period is not depicted for the sake of clarity). 3. Results 3.1. Area with the largest wave resource Apart from the data used in the previous section for validating the hindcast dataset, the data used in the present research correspond to the seven grid points closest to La Palma (Fig. 1). Their
main wave height, power and energy statistics are shown in Table 1. The last column, total annual energy, is referred to an average year (the average of the 44 years in the dataset). It is apparent from the figures in the table that the study sites can be classified into two groups or areas: a high-energy area to the north (N1 to N4) and a low-energy area to the south (S1 to S3). The explanation for the difference between the two areas is straightforward: northerly waves (from NW to NE) prevail in the Canary Islands region, and the north of La Palma is fully exposed to them; in contrast, the south is sheltered by the island itself (Fig. 2). As for the differences within each area, they are clearly related to the position of each site relative to the island. Within the low-energy area the most sheltered are S1 and S2, hence they are also the least energetic. Within the high-energy area the most exposed are N2 and N3; in any case, their differences with N1 are minor (less than 2% in terms of annual energy), so the area with the largest wave resource is the north and northwest of the island. These geographical variations around the island are represented in Fig. 4 (mean wave power) and Fig. 5 (total annual energy). The wave roses in Figs. 6 and 7, for the high-energy and lowenergy areas, respectively, have a colour scale graded according to wave power. Focusing on the high-energy area (Fig. 6) it is clear that
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G. Iglesias, R. Carballo / Energy 35 (2010) 5013e5021
Fig. 7. Annual wave power roses at sites S1 e S3 (low-energy area) [J, power per metre of wave front].
the largest wave power values correspond to IV quadrant directions, in particular NNW, followed by NW and N (strictly speaking, N waves are 50% IV quadrant, 50% I quadrant); certain directions from the I quadrant (NNE) also have large probabilities of occurrence, but are associated with less energetic waves. This is explained by the Canary Islands’ location near the eastern boundary of the Atlantic Ocean, which results in longer fetch distances along IV quadrant directions, and by the northwesterly winds prevailing in the Atlantic north of the Canary Islands (where the IV quadrant swells in Fig. 6 are generated). The lower wave power values of I quadrant waves relative to IV quadrant waves account for the lower energy levels of the northeast of La Palma (site N4) relative to the northwest (site N1). For all its importance, the wave resource is not the only issue to consider when selecting the area for a wave power installation. Two other major issues, the construction and operational costs, are influenced by various factors: technological options, financing, public subsidies, taxation, etc. These factors are outside the scope of this work; there is, however, one factor that can be weighed here: proximity to a port. Its importance is obvious if the technological options are centred around offshore Wave Energy Converters. But even if an onshore wave power plant were envisageddwhich is
unlikely given La Palma’s status as a UNESCO Biosphere Reservedthe construction and operational costs would increase with road distance to the nearest port, not least in view of the winding roads of La Palma. While there are no ports along the north of the island, there is one on its west coast: Tazacorte (Fig. 2). On these grounds, the northwest (the area around site N1) has the highest potential for the installation of a wave farm. 3.2. Seasonality of the wave resource Having established the area with the highest potential for a wave farm, the seasonal variations of the resource in this area are considered next. Seasonal wave roses for study site N1 (Fig. 8) indicate that the prevailing wave direction veers from NW-NNW in winter to NNE in summer; the prevailing directions in the intermediate seasons are also intermediate: N in spring, NNW in autumn. Two more facts may be observed in Fig. 8. First, the largest waves occur in winter, followed by autumn; significant wave heights are clearly smaller in spring and summer. Second, there is a correlation between wave height and directiondthe larger wave heights are associated with NW and NNW waves. As indicated, this is a direct result of the long (oceanic) fetch along these directions.
G. Iglesias, R. Carballo / Energy 35 (2010) 5013e5021
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Fig. 8. Seasonal wave height roses at site N1 [Hm0, significant wave height].
In view of these seasonal variations it is clear that, alongside the installation of a wave farm, provisions should be made for storing wave energy. The mountainous nature of La Palma provides an excellent basis for inexpensive energy storage using water reservoirs at altitude. The integration of wave power with other renewable energies will also help to mitigate the effects of its variability.
3.3. Characterisation of the wave resource and WEC selection In the preceding sections the wave resource around La Palma was assessed, the area with the highest potential was determined, and the seasonal variations in this area were investigated. There is a further point of interest with respect to the wave resourcedone that influences the selection of the Wave Energy Converters to be installed. This point concerns the characteristics of the resource in terms of sea states, or in other words, the characteristics of the waves providing the power. There are many different technologies in different degrees of development for transforming this power into electricity [30]. Each technology has different operational ranges, and what is more, different efficiencies under different sea states (e.g. [31]). It follows that the WECs selected should have
Fig. 9. Contribution to the total annual energy of the different sea states at site N1 [Te, energy period; Hm0, significant wave height].
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Table 2 Probability of occurrence of the different sea states at site N1 expressed in number of hours in the average year. [Hm0, significant wave height; Te, energy period]. Hm0(m)
Te(s) <¼2
2e4
4e6
6e8
8e10
10e12
12e14
14e16
16e18
18e20
>20
Total
>10 9e10 8e9 7e8 6e7 5e6 4e5 3e4 2e3 1e2 <¼1
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.3 0.5
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 8.7 381.0 19.6
0.0 0.0 0.0 0.0 0.0 0.0 0.6 20.1 362.7 1323.8 161.0
0.0 0.0 0.0 0.0 0.1 1.6 14.0 96.2 385.9 1584.9 62.5
0.0 0.0 0.0 0.2 2.7 10.4 36.4 147.6 995.1 1259.5 35.3
0.1 0.1 0.6 1.4 4.9 16.8 59.1 284.4 610.4 325.4 12.0
0.0 0.2 0.5 2.4 5.1 17.9 60.2 128.0 131.7 72.0 1.6
0.0 0.0 1.0 1.4 5.8 10.1 22.6 30.6 25.8 11.5 0.1
0.0 0.0 0.0 0.0 0.1 0.6 1.8 4.1 3.5 1.0 0.0
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
0.1 0.3 2.0 5.5 18.7 57.6 194.8 711.0 2524.0 4959.6 292.5
Total
0.0
0.8
409.4
1868.2
2145.2
2487.3
1315.3
419.7
109.1
11.1
0.0
8766.0
maximum efficiency in the ranges of wave heights and periods that provide the bulk of the energy in the area of interest. The contribution of the different sea states to the total annual energy at study site N1, representative of the area with the highest potential, is presented in Fig. 9. Sea states are classified into ‘energy bins’ of 0.5 s 0.5 m (DTe DHm0), the colour of each bin representing its contribution. Wave energy is concentrated between 9.5 s and 13.5 s (energy period) and between 1.5 m and 3.5 m (significant wave height), so the selection of the WECs should aim for maximum efficiency in these ranges. Wave power isolines based on Equation (3) are also depicted in Fig. 9. From these isolines and the colours in the energy bins it is clear that the bulk of the energy is provided by sea states between w15 kW/m and w90 kW/m. At first sight it may seem odd that the most powerful sea states (some of them with wave power values beyond 250 kW/m) contribute so little to the total annual resource; there is, however, a simple explanation: high-power sea states are associated with waves of large heights and periods (Equation (3)), and these have low probabilities of occurrence. For illustration, the probability of occurrence of the different sea states at site N1 is shown in Table 2, expressed in number of hours in the average.
occur in winter, followed by autumn; wave power decays in spring and, especially, summer. Wave directions also present a seasonal pattern: the prevailing direction veers from NW-NNW in winter to NNE in summer. In fact, there is a correlation between wave direction and powerdthe most energetic waves are the NNW-NW swells. These seasonal variations should be taken into account by providing for energy storage alongside the wave power installation; thanks to the high elevations in La Palma, this storage can be achieved by means of water reservoirs at altitude combined with a hydropower scheme. Finally, the resource was characterised in terms of sea states, i.e. significant wave heights and energy periods. It was found that the bulk of the energy in the wave farm area was provided by sea states between 9.5 s and 13.5 s of energy period and 1.5 m and 3.5 m of significant wave height, so the selection of Wave Energy Converters should ensure maximum efficiency in these ranges. In sum, the wave resource in La Palma was assessed using a 44-year hindcast dataset validated with wave buoy measurements; a considerable resource was found in certain areas, which should be put to use to make La Palma’s goal of energy self-sufficiency a reality.
4. Conclusions
Acknowledgements
La Palma is the most northwestern of the Canary Islands, a volcanic archipelago in the Atlantic; dubbed La Isla Bonita for its natural beauty and environmental values, it is a UNESCO Biosphere Reserve. The island’s authorities are aiming for energy self-sufficiency using wave, wind and PV power. This research focused on the wave resource, which was investigated based on a hindcast dataset covering 44 years. This dataset is the result of two numerical modelsda regional atmospheric model and a wave model. For validation the hindcast data were compared with wave buoy data; excellent agreement was found. The wave resource presents significant differences around the islanddit is substantial off its north and northwest coast, but less abundant elsewhere. This is explained by the location of the Canary Islands in the Atlantic Ocean and that of La Palma within the archipelago, which leaves its north and northwest directly exposed to powerful IV quadrant swells; as a result, mean power and annual energy in the area are above 25 kW/m and 220 MWh/m, respectively. Comparing the north and northwest, their energy resource is very similar, but the northwest is nearer to a portdan advantage with respect to the construction and operational costs. Having selected the northwest as the area with the highest potential for a wave farm, the seasonal variations of the wave resource in this area were analysed. The most energetic waves
The authors are grateful to three anonymous reviewers, whose kind suggestions contributed to improve the manuscript. This research is part of the project “Assessment of Renewable Energy Resources” (DPI2009-14546-C02-02) supported by Spain’s Ministry of Science and Innovation (Ministerio de Ciencia e Innovación). Its authors are indebted to Spain’s State Ports (Puertos del Estado), in particular to Dr. I. Rodríguez-Arévalo, Dr. E. Fanjul, Ms. P. Gil and Ms. S. Pérez.
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