SEM-REV energy site extreme wave prediction. (February 2017)
- Record Type:
- Journal Article
- Title:
- SEM-REV energy site extreme wave prediction. (February 2017)
- Main Title:
- SEM-REV energy site extreme wave prediction
- Authors:
- Gaidai, Oleg
Ji, Chunyan
Kalogeri, Christina
Gao, Junliang - Abstract:
- Abstract: Accurate estimation of extreme wave conditions is critical for offshore renewable energy activities and applications. Wave power is the transport of energy by wind waves, and the capture of that energy to do useful work. Wave energy converter (WEC) devices are designed to sustain the wave-induced loads that they experience during both operational and survival sea states. The extreme values of these forces are often a key cost driver for WEC designs. These extreme loads often occur during severe storms; therefore careful examination of harsh wave conditions during the device design process is needed. Consequently the development of a specific extreme condition modeling method is essential. This paper presents a novel method for estimating extreme wave statistics, based on the hourly measured wave height maxima at the location of interest. Wave measurements, analyzed in this paper, were collected at SEM-REV offshore sea station located near the coast of France, during years 2001–2010. Note that applied statistical methodology is general and can be well applied to a measured WEC response, and its technology risk assessment. Accurate estimation of extreme wave conditions is critical for offshore renewable energy activities and applications. SEM-REV is known French wave energy test site. The method, referred to as ACER method, is presented in brief detail. ACER method provides an accurate extreme value prediction, utilizing available data efficiently. In this study theAbstract: Accurate estimation of extreme wave conditions is critical for offshore renewable energy activities and applications. Wave power is the transport of energy by wind waves, and the capture of that energy to do useful work. Wave energy converter (WEC) devices are designed to sustain the wave-induced loads that they experience during both operational and survival sea states. The extreme values of these forces are often a key cost driver for WEC designs. These extreme loads often occur during severe storms; therefore careful examination of harsh wave conditions during the device design process is needed. Consequently the development of a specific extreme condition modeling method is essential. This paper presents a novel method for estimating extreme wave statistics, based on the hourly measured wave height maxima at the location of interest. Wave measurements, analyzed in this paper, were collected at SEM-REV offshore sea station located near the coast of France, during years 2001–2010. Note that applied statistical methodology is general and can be well applied to a measured WEC response, and its technology risk assessment. Accurate estimation of extreme wave conditions is critical for offshore renewable energy activities and applications. SEM-REV is known French wave energy test site. The method, referred to as ACER method, is presented in brief detail. ACER method provides an accurate extreme value prediction, utilizing available data efficiently. In this study the estimated return level values, obtained by ACER method, are compared to the corresponding return level values obtained by Gumbel method. Based on the overall performance of the proposed method, it is concluded that the ACER method can provide a robust and accurate prediction of extreme wave height at a given location. Highlights: New state of art statistical method is applied for measured wave heights. Practical and accurate prediction of extreme wave height is done. New method is benchmarked versus another classical one and is proven to be superior. … (more)
- Is Part Of:
- Renewable energy. Volume 101(2017)
- Journal:
- Renewable energy
- Issue:
- Volume 101(2017)
- Issue Display:
- Volume 101, Issue 2017 (2017)
- Year:
- 2017
- Volume:
- 101
- Issue:
- 2017
- Issue Sort Value:
- 2017-0101-2017-0000
- Page Start:
- 894
- Page End:
- 899
- Publication Date:
- 2017-02
- Subjects:
- Wave height statistics -- Probability -- SEM-REV -- Extreme value statistics -- Gumbel distribution -- Wave energy
Renewable energy sources -- Periodicals
Power resources -- Periodicals
Énergies renouvelables -- Périodiques
Ressources énergétiques -- Périodiques
333.794 - Journal URLs:
- http://www.sciencedirect.com/science/journal/09601481 ↗
http://www.elsevier.com/journals ↗
http://www.journals.elsevier.com/renewable-energy/ ↗ - DOI:
- 10.1016/j.renene.2016.09.053 ↗
- Languages:
- English
- ISSNs:
- 0960-1481
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 7364.187000
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 2478.xml