The work presents a comprehensive picture of the wind energy potential in the coastal environment of the Black and the Caspian Seas. 10-year of data coming from the US National Centers for Environmental Prediction was considered as the main source. This dataset was subsequently compared with both in situ and remotely sensed measurements. The results show that the western side of the Black Sea has an enhanced wind power potential, especially in the vicinity of the Crimean Peninsula. As regards the Caspian Sea, the northeastern sector can be considered more energetic. A direct comparison of various wind parameters corresponding to the locations with higher potential in the two target areas considered was also carried out, in order to notice the similarities and the key features that could be taken into account in the development of an offshore wind project. Finally, it can be concluded that the coastal environments of the Black and the Caspian Seas can become in the near future promising locations for the wind energy extraction, as well as for the hybrid wind-wave energy farms that could play an important role also in the coastal protection.
The present work is focused on two enclosed seas, the Black and the Caspian Seas, and it has as main objective to assess the wind energy potential in these marine areas. The Black Sea is located between the Anatolian Peninsula and the southeastern part of Europe and it is connected to the Mediterranean Sea throughout the Marmara and Aegean seas, respectively. This basin can be divided into two main zones (west and east) with particular features, the coastlines of the sea being distributed between Bulgaria and Romania (west), Russia and Ukraine (north), and Georgia (east) and Turkey (south). Regarding the geographical characteristics of this sea, an average depth of 1315 m, a total area of 436402 km2, and a water volume of 547000 km3 can be mentioned (Rotaru [
Regarding the Caspian Sea, it can be mentioned that this is in fact the largest enclosed water body in the world (40% of the inland waters) being surrounded in about 7000 km by Russia and Kazakhstan (north), Turkmenistan (east), Iran (south), and Azerbaijan (west). It is located between Europe and Asia, and it has a surface of 371000 km2 and a volume of 78200 km3, while a particularity of this basin is that it is characterized by important oil fields (Rusu and Onea [
At this moment, the Black and Caspian Seas can be considered important sources of energy, but this regards mainly the fossil fuel reserves, while the possible benefits from the renewable energy resources are not yet well taken into consideration. From this perspective, the novelty of the present work consists in the fact that the wind energy potential in the vicinity of the coastlines of the two inland seas is discussed from a meteorological perspective.
Figure
The geographical locations of the reference points considered in the coastal environments of (a) the Black Sea, (b) meteorological stations, and (c) the Caspian Sea. The in situ stations are located in the Black Sea area; most of them are in sector A. Figures are processed from Google Earth (2015).
Regarding the Caspian basin, the C points are divided between Russia (C1–C3), Kazakhstan (C4–C6), Turkmenistan (C7-C8), Iran (C9-C10), and Azerbaijan (C11 and C12), respectively. For these target areas, it can be mentioned that Russia has coastlines in both seas, a fact which can be considered somehow an advantage, since the wind projects can be focused on one or another area according to the most favorable wind regime. The coastlines of Turkey can be also considered as representing another important area, since Turkey has the largest opening to the Black Sea (1595 km), compared, for example, with Romania (245 km).
In general, a gap in the assessment of the conditions in the marine environment is represented by the limited amount of the in situ measurements. Nevertheless, during the recent years, this aspect was overreached by the development of the numerical models, which can produce extended reanalysis databases in both space and time. This type of data was also used in some previous studies to assess the global renewable energy resources in the marine areas (Rusu [
This is based on a system which uses a 5-day average and 6-hour forecast, being capable to simulate various parameters on a global scale, such as precipitation, temperature, pressure at the surface, or ice thickness. The wind conditions are reported at 10 m above the sea level (a.s.l.) in terms of the
As a first step of the present work, the available NetCDF files were processed for the 10-year time interval 1999–2008, obtaining in this way daily values of the wind conditions with a step of 6 hours (00–06–12–18 UTC). In order to investigate different wind patterns, the initial data were particularly selected for the winter time period (October–March) and also for the diurnal (12–18 UTC) and nocturnal (00–06 UTC) intervals.
In Figure
Scatter plots of the
The statistical parameters associated with the scatter diagrams are presented in Table
Point |
|
|
Bias (m/s) | RMSE | SI |
|
---|---|---|---|---|---|---|
P1 | 7.21 | 6.42 | 0.78 | 4.49 | 0.62 | 0.12 |
P2 | 4.08 | 4.43 | −0.35 | 2.07 | 0.5 | 0.63 |
P3 | 4.46 | 6.03 | −1.57 | 3.37 | 0.75 | 0.44 |
P4 | 4.61 | 6.00 | −1.39 | 3.57 | 0.77 | 0.36 |
P5 | 3.28 | 6.27 | −2.98 | 4.46 | 1.35 | 0.22 |
Figure
Evaluation of the wind conditions reported to the meteorological station sites for the time interval 1999–2008. The analyses are based on the in situ measurements and the NCEP data and correspond to the mean values of (a) monthly wind speeds registered at the meteorological stations, (b) monthly wind speeds provided by the NCEP model, (d) and (c) diurnal-nocturnal variations of the wind speeds according to the in situ measurements and the NCEP data, respectively.
The differences between the diurnal and nocturnal intervals, as reflected by the in situ measurements, can be observed in Figure
Figure
Assessment of the wind conditions in the Black Sea reported to a height of 10 m. The results are based on the NCEP data (1999–2008) for the mean values of (a) wind speeds—total and winter time, (b) power density—total and winter time, (c) monthly wind speed (B2, B5, B7, and B10), and (d) monthly wind speed (B2, B5, B7, and B10)—diurnal and nocturnal.
Besides the wind speed, another parameter that is used frequently to express the wind energy potential is the power density (in W/m2), which can be defined as (Fiedler and Adams [
The monthly distribution of the parameter
For the Caspian Sea area, a similar analysis is presented in Figure
Assessment of the wind conditions in the Caspian Sea reported to a height of 10 m. The results are based on the NCEP data (1999–2008) for the mean values of (a) wind speeds—total and winter time, (b) power density—total and winter time, (c) monthly wind speed (C3, C6, C7, and C11), and (d) monthly wind speed (C3, C6 C7, and C11)—diurnal and nocturnal.
The evolution of the power density is presented in Figure
The diurnal/nocturnal distributions of the wind conditions are given in Figure
Table
Statistical analysis of the NCEP data, corresponding to the total time (TT) and winter time (WT), respectively. The results cover the ten-year time interval 1999–2008.
Point | |||||||||
---|---|---|---|---|---|---|---|---|---|
Results | Time interval | Black Sea | Caspian Sea | ||||||
B2 | B5 | B7 | B10 | C3 | C6 | C7 | C11 | ||
|
TT | 6.71 | 6.04 | 4.17 | 4.52 | 6.31 | 6.59 | 5.86 | 3.91 |
WT | 7.70 | 7.00 | 4.58 | 4.81 | 6.63 | 7.47 | 6.02 | 4.20 | |
|
|||||||||
95% (m/s) | TT | 12.37 | 11.86 | 8.06 | 8.93 | 11.22 | 12.57 | 10.42 | 7.61 |
WT | 13.28 | 13.16 | 8.62 | 9.53 | 11.62 | 13.64 | 10.73 | 8.28 | |
|
|||||||||
Extreme (m/s) | TT | 24.81 | 21.92 | 16.33 | 19.39 | 18.8 | 18.83 | 18.49 | 16.83 |
WT | 24.81 | 21.92 | 16.33 | 19.39 | 17.41 | 18.83 | 18.49 | 16.83 | |
|
|||||||||
Power density (W/m2) | TT | 319.6 | 260.4 | 86.05 | 109.6 | 251.3 | 314 | 198.9 | 71.5 |
WT | 436.9 | 370.7 | 107.9 | 131 | 285.6 | 426.3 | 216.6 | 88.3 |
Another important parameter in the process of evaluating a particular location is the direction from which the wind is blowing. Figure
Wind roses reported to the meteorological stations, during the time period 1999–2008. The results are structured in the diurnal and nocturnal intervals, corresponding to the points (a) P1, (b) P2, (c) P3, and (d) P4.
Based on the NCEP dataset, Figure
Wind roses corresponding to some relevant points from (a) the Black Sea and (b) the Caspian Sea. The NCEP data correspond to the 10-year time interval (1999–2008).
A closer look at the wind conditions of the two target areas is presented in Figure
Comparison of the wind conditions corresponding to the points B2 (the Black Sea) and C6 (the Caspian Sea), where (a) monthly mean power density, (b) diurnal and nocturnal wind roses for the reference point B2, and (c) diurnal and nocturnal wind roses for the reference point C6 are reported.
Figure
The most severe variation can be associated with the diurnal/nocturnal distribution of the wind direction, which is illustrated for the point B2 in Figure
Although at this moment in Europe, the ocean boundaries present more interest, since the wind conditions seem to be in general more energetic there, possible benefits can be obtained also from the inland basins such as the Mediterranean and Black seas (Ahmed Shata and Hanitsch [
Since the NCEP dataset can be considered a blended source of data, from the comparisons with the in situ measurements (wind speed and direction), it was noticed that this type of data tends to average the wind conditions both in the offshore or the nearshore locations. In order to provide a better perspective on the results obtained for the two basins, in this section, also some satellite measurements will be analyzed, which were processed corresponding to the locations of the same reference points, respectively: B1–B12 (Black Sea) and C1–C12 (Caspian Sea). These measurements are coming from the AVISO (Archiving, Validation and Interpretation of Satellite Oceanographic Data) program [
Figure
Evaluation of the wind conditions in the Black Sea based on satellite measurements. The results are reported to the time interval 2010–2014, for (a) mean wind speed for the total and winter time, respectively, (b) the monthly evolution of the
A similar analysis is performed in Figure
Evaluation of the wind conditions in the Caspian Sea based on satellite measurements. The results are reported to the time interval 2010–2014, for (a) mean wind speed for the total and winter time, respectively, (b) monthly evolution of the
Table
Statistical analysis of the satellite measurements, corresponding to the total time (TT) and winter time (WT), respectively. The results cover the five-year time interval 2010–2014.
Point | |||||||||
---|---|---|---|---|---|---|---|---|---|
Results | Time interval | Black Sea | Caspian Sea | ||||||
B2 | B5 | B7 | B10 | C3 | C6 | C7 | C11 | ||
|
TT | 4.18 | 3.82 | 2.96 | 3.84 | 4.74 | 5.32 | 4.98 | 4.712 |
WT | 5.12 | 4.59 | 3.57 | 4.65 | 5.83 | 6.62 | 6.12 | 5.735 | |
|
|||||||||
95% (m/s) | TT | 9.37 | 8.41 | 6.89 | 8.43 | 9.32 | 10.81 | 10.17 | 9.642 |
WT | 10.23 | 9.17 | 8.16 | 9.56 | 11.29 | 11.96 | 11.75 | 11.37 | |
|
|||||||||
Extreme (m/s) | TT | 15.88 | 15.4 | 12.99 | 15.06 | 16.35 | 22.43 | 21.76 | 20.24 |
WT | 15.88 | 15.4 | 12.99 | 15.06 | 16.35 | 22.43 | 21.76 | 20.24 | |
|
|||||||||
Power density (W/m2) | TT | 109 | 80.52 | 44.43 | 80.72 | 133.7 | 190.4 | 160.4 | 139.1 |
WT | 160.9 | 115.3 | 66.01 | 119.3 | 217.1 | 296.1 | 245.3 | 211.7 |
In the present work a comprehensive picture of the wind energy potential in the Black and the Caspian Seas is provided from a meteorological point of view. The analysis is based both on the reanalysis data coming from the National Centers for Environmental Prediction (NCEP), which cover a 10-year interval (1999–2008), and also throughout some measured data (both in situ and remotely sensed).
By dividing each target area into four rectangular domains, it was possible to identify in each basin the most promising locations from the point of view of the wind energy potential. Regarding the Black Sea region, it was found that the windiest locations seem to be situated in the northwestern part of the sea, especially in the vicinity of the point B2, which is located close to Ukraine. For the Caspian region, the points C5 and C6 (Kazakhstan) stand out with significant values, especially during the winter time. The less energetic areas were found to be in the southern part of the Black Sea, while in the Caspian Sea lower values of the wind speed and power density were reported in the points located in the southern and southwestern parts of the basin.
These results are also confirmed by the satellite measurements, which indicate, with a good accuracy, the most or the less energetic points from the two areas targeted, with the mention that the values are usually below the ones provided by the NCEP model. If we take into account that the most energetic area presents also relevant wave energy resources, it can be expected in the near future to be developed hybrid wind-waves farms, which might also play an important role in the coastal protection (see, e.g., Zanopol et al. [
Based both on the NCEP data and on the satellite measurements, it is shown that the two enclosed seas targeted in the present work can provide suitable conditions for the implementation of the offshore wind parks. On the other hand, if we take a step back looking at the big picture, it can be assumed that since the Caspian Sea is an area rich in oil, there are few chances at this moment to see a renewable project in this area. As regards the Black Sea, although the strongest wind conditions were noticed near the coastlines of Ukraine, considering the current geopolitical climate, it might be rather unrealistic to make plans there for an offshore farm. In this context, it can be concluded that one of the most interesting regions is located in the vicinity of the Romanian coast, nearshore that has a good wind potential as also the capacity to develop a renewable project in the offshore areas.
The authors declare that there is no conflict of interests regarding the publication of this paper.
This work was supported by a grant of the Romanian Ministry of National Education, CNCS-UEFISCDI PN-II-ID-PCE-2012-4-0089 (project DAMWAVE). The work of the first author has been funded by the Sectoral Operational Programme Human Resources Development 2007–2013 of the Ministry of European Funds through the Financial Agreement POSDRU/159/1.5/S/132397. The wind dataset corresponding to the Ukrainian coastal environment of the Black Sea was kindly provided by the Ukrainian Research Hydrometeorological Institute. The altimeter products were produced by Ssalto/Duacs and distributed by Aviso with support from Cnes.