Long-term analysis of wave power potential in the Black Sea, based on 31-year SWAN simulations

Adem Akpınar*, Bilal Bingölbali, Gerbrant Ph Van Vledder

*Corresponding author for this work

Research output: Contribution to journalArticleScientificpeer-review

52 Citations (Scopus)


This study analyzes the wave energy potential in the Black Sea based on long-term model simulations. A dataset covering the period of 1979–2009 is produced using a calibrated numerical wave prediction model (SWAN). This dataset was analyzed in detail to determine the wave energy potential to enable a reliable and optimal design of wave energy conversion devices in the Black Sea. This analysis provides information on the long-term variability as well as on the annual, seasonal and monthly averages. The analysis of the hindcast results is conducted on a spatial and a location scale. The spatial analysis provides information for the entire Black Sea on; the averaged mean wave energy flux over the period 1979–2009, and the decades 1980–1989, 1990–1999, and 2000–2009, seasonal and monthly averages of wave energy flux during 31 years, variability indices for the 1979−2009 period, and variabilities on monthly and seasonality basis based on inter-annual averages during 31 years. The location scale considered nine locations providing information on; wave power roses, probabilities of occurrence and cumulative distribution functions of wave power in different power ranges, variation and trend of yearly average wave power, seasonal average wave power and its annual variations, and quantities of wave energy flux for different Hm0 and Tm-10 ranges. Results show that areas with the highest wave energy potential are located in the south-western part of the Black Sea. These areas are; Burgas – Rezovo (BR) with an average annual total energy of 43.9 MW h/m followed by Dolni Chiflik – Shkorpilovtsi (DCS) with 37.3 MW h/m and Istanbul – Alacali (IA) with 36.1 MW h/m.

Original languageEnglish
Pages (from-to)482-497
Number of pages16
JournalOcean Engineering
Publication statusPublished - 15 Jan 2017


  • Black Sea
  • Resource variability
  • Spatial distribution
  • SWAN model
  • Wave power assessment


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