Inter-comparison of long-term wave power potential in the Black Sea based on the SWAN wave model forced with two different wind fields
Introduction
Wave energy is estimated to be the largest component of global ocean energy resources. The European Commission (2014) has estimated the wave energy potential to be 29,500 TW h/y, while global tidal energy potential is estimated to be 1200 TW h/year. Therefore, waves are a predictable source of energy and have immense potential for power production.
There are numerous positive aspects of wave en that contribute to it being considered an alternative or renewable (“green”) energy source. First, it is a useful, clean, and green energy source that is environmentally friendly and does not emit any harmful gases. Moreover, it does not destroy agricultural areas. Second, it is renewable and sustainable. Third, it is one of the most reliable renewable energy sources because the resource is high accuracy in energy prediction (Mwasilu and Jung, 2019). Fourth, wave energy has higher energy density than solar or wind energy (Fadaeenejad et al., 2014), thus giving it enormous potential for application. For example, power can be extracted from wave energy for approximately 90 % of the day on average, while the corresponding extraction ratios are 20 % and 30 % for wind turbines and solar panels, respectively (Fadaeenejad et al., 2014).
Wave power assessments have been performed by many researchers in various locations around the world. For instance, studies were carried out on the Madeira Islands Archipelago by Rusu and Soares (2012), the French coast by Gonçalves et al. (2014), western Scandinavia, Ireland, UK, Iberian Peninsula, the Mediterranean, and Black seas by Rusu and Onea (2015), the Greek Isles by Ganea et al. (2017), European marine sites by Onea et al. (2017), Asia by Khojasteh et al. (2018), and Latin American and European coasts by Rusu and Onea (2019). The main aim of these studies was the identification of optimal areas for the extraction of wave power and the implementation of suitable wave energy converters (WECs) (Rusu and Soares, 2012; Gonçalves et al., 2014; Rusu and Onea, 2015; Ganea et al., 2017; Onea et al., 2017; Rusu and Onea, 2019). A suitable converter depends on various parameters, such as supply chain logistics, the distance to the shore, bathymetry, water depth, energy storage, power demand, and wave resources. This situation makes it necessary to conduct long-term analyses of wave power.
This comprehensive study focuses on a long-term analysis of the wave power in the Black Sea. This location was selected because its geographic location, semi-closed basin, complex bathymetry, and shipping activities have attracted the attention of many researchers. In addition, various studies have shown that the Black Sea region has significant wave power potential; however, considerably different wave energy estimations have been reported for this region.
Valchev et al. (2013) evaluated the off-shore wave energy over a 59–year (1948–2006) period in the Black Sea. The third-generation WAM wave model forced with the wind output of the REMO regional atmospheric model was used to generate wave simulations. The maximum value of the mean wave power was found to be 3.5 kW/m in the southwestern Black Sea.
Akpinar and Kömürcü (2013) assessed the wave power potential of the Black Sea based on the SWAN (Simulating WAves Nearshore) model forced with 15–year (1995–2009) ERA-Interim wind fields. The maximum value of the mean wave power (3 kW/m) was found in the southwestern Black Sea. However, Akpınar et al. (2017) reported a maximum value of the mean wave power in the southwestern Black Sea of 5.7 kW/m. This value was almost twice that of their previous study because the wave power potential was calculated from the SWAN model using 31–year (1979–2009) CFSR wind fields.
Rusu (2015) evaluated the wave energy potential in the Black Sea using SWAN model simulations with a data assimilation system (15–year period, 1999–2013). The maximum value of the mean wave power was 4.5 kW/m in the southwestern Black Sea. Similarly, Galabov (2015) estimated maximum mean annual wave power values between 4.8 kW/m and 5.0 kW/m in the western Black Sea for a 4–year (2012–2015) period based on the SWAN model forced with ALADIN (Aire Limitée Adaptation Dynamique développement Inter-National) winds.
The wave and wind energy potentials in the western Black Sea were also assessed for a 30–year (1987–2016) period (Rusu, 2019). Wave simulations were performed using the SWAN model with the CFSR wind fields. The highest mean wave power (4.3 kW/m) was found in the southwestern Black Sea.
Divinsky and Kosyan (2017) investigated the wave climate over the Black Sea using 37–year (1979–2015) ERA-Interim wind fields. The analysis was performed using the DHI (Danish Hydraulic Institute) MIKE 21 SW (Spectral Wave) model. The mean wave power reached 8–10 kW/m in the southwestern Black Sea. However, these results appear to overestimate the wave energy potential over the Black Sea.
Divinsky and Kosyan (2019) investigated the average and maximum power of wind seas, swell, and mixed waves based on the MIKE 21 SW model results for a 40–year (1979–2018) ERA-Interim dataset. The authors noted that the characteristics of swell in the Black Sea are limited by the geographical size and isolation of the sea basin. Van Vledder and Akpinar (2016) determined the swell climate of the Black Sea using a 31–year CFSR wind fields with SWAN model and reported that the total significant wave height is usually composed of only a wind sea and where the significant wave height is strongly coupled with the local wind speed. On the other hand, swell has been studied on the oceanic scale (Chen et al., 2002; Semedo et al., 2011; Zheng et al., 2020), and these studies show that swell plays an important role in the oceanic scales for the wave power but not in semi-closed basin similar to the Black Sea.
The present study aims to understand the significant discrepancies in the maximum reported values of the mean wave power and gain a better perspective on the wave power potential in the Black Sea by providing extensive data for long-term assessments of the wave power over the period from 1979 to 2018. This study highlights the importance of correct identification of the mean wave power, which is crucial for the implementation of proper WECs. To evaluate the usability of different wind sources, two well-known wind fields (ECMWF ERA-Interim and NCEP/CFSR) were used to generate wave simulations with the calibrated and validated SWAN model. The long-term and seasonal averages of the wave power and their variabilities over the entire Black Sea were investigated, and some local points were analyzed in detail.
Section snippets
Method
The Black Sea has attracted the attention of researchers owing to its complex bathymetry, complicated orography, and variety of different climatic conditions (Islek et al., 2020a). In addition, the basin acts as a commercial connector between the ports of Europe, Asia, and Africa across the coastlines of six countries and it connects to the Mediterranean through the straits (Lyratzopouoou and Zarotiadis, 2014). Therefore, this study focused on the entire Black Sea, which spans longitudes of
Evaluation of the SWAN model performance compared to measurements
The accuracy of the SWAN model results was calibrated using wave measurements including the significant wave heights and mean wave periods recorded at Gelendzhik station for the year 2000 and Karaburun station for the year 2004. The characteristics of the measurement stations are presented in Table 2, and the locations of the two stations are shown in Fig. 1.
The calibration process was performed separately for the two different wind sources to determine the optimal model settings and obtain the
Wave power assessments
In this study, the wave power potential or energy flux (kW/m) can be determined using Eq. (1) (Rusu and Onea, 2016):where P is the wave power, Hs is the significant wave height, Te (Tm-1,0) is the energetic period of the waves, ρ is the density of the Black Sea (1015 kg/m3), and g is the acceleration due to gravity. Eq. (1) can be simplified as follows:
As can be seen in Eq. (1), the wave power depends on the wave period and strongly depends on the wave height, as
Long-term trends
To determine the appropriate location for the wave power applications, it is necessary to investigate the locations where the wave power is reliable, stable, and sustainable. For this purpose, trends in the wave power over the 40–year period are calculated using linear regression based on the line of best-fit for the yearly wave power. The least-squares method is the most commonly used method for fitting a regression line. This method calculates the line of best fit for the considered data by
Occurrence of wave power
To determine the availability of resources, to make long-term planning of the wave power generation, the occurrence of wave power was analyzed for quantifying the richness of the wave energy. Zheng and Li (2011) proposed the key indicator of “Energy Level Occurrence” at home and abroad such as the effective wave height occurrence (EWHO), available level occurrence (ALO), moderate level occurrence (MLO), rich level occurrence (RLO). In this study, the occurrence of wave power above 2 kW/m, more
Local analyses of the wave power potential
To investigate the wave power at a local scale, detailed analyses were performed for twelve points on the Black Sea. These reference points are concentrated in the western Black Sea, which has the least long-term variability in the wave power and the greatest wave power potential. The selected locations are shown in Fig. 1. The main characteristics of the reference points and some statistical parameters are presented in Table 6, and the annual variation is shown in Fig. 14 for both datasets.
Conclusions
The present study provides more reasonable results for wave power assessments than the previous studies because the results of the present study are based on reliable datasets that have been calibrated and validated with seven different wave measurement stations. In addition, reliable information is obtained in the present study owing to the use of sufficiently large datasets (Swain, 1997). Moreover, the SWAN model results driven by wind fields with different spatial and temporal resolutions
Recommendations
Swell plays an important role in coastal engineering it is recommended to study the extraction of the wave power from swell in the Black Sea.
Declaration of Competing Interest
The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
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