Offshore renewable energy systems, such as Wave Energy Converters or an Offshore Wind Turbine, must be designed to withstand extremes of the weather environment. For this, it is crucial both to have a good understanding of the wave and wind climate at the intended offshore site, and of the system reaction and possible failures to different weather scenarios. Based on these considerations, the first objective of this thesis was to model and identify the extreme wind speed and significant wave height at an offshore site, based on measured wave and wind data. The extreme wind speeds and wave heights were characterized as return values after 10, 25, 50, and 100 years, using the Generalized Extreme Value method. Based on a literature review, fragility curves for wave and wind energy systems were identified as function of significant wave height and wind speed. For a wave energy system, a varying failure rate as function of the wave height was obtained from the fragility curves, and used to model the resilience of a wave energy farm as a function of the wave climate. The cases of non-constant and constant failure rates were compared, and it was found that the non-constant failure rate had a high impact on the wave energy farm's resilience. When a non-constant failure rate as a function of wave height was applied to the energy wave farm, the number of Wave Energy Converters available in the farm and the absorbed energy from the farm are nearly zero. The cases for non-constant and an averaged constant failure of the instantaneous non-constant failure rate as a function of wave height were also compared, and it was discovered that investigating the resilience of the wave energy farm using the averaged constant failure rate of the non-constant failure rate results in better resilience. So, based on the findings of this thesis, it is recommended that identifying and characterizing offshore extreme weather climates, having a high repair rate, and having a high threshold limit repair vessel to withstand the harsh offshore weather environment.
| Identifer | oai:union.ndltd.org:UPSALLA1/oai:DiVA.org:uu-445650 |
| Date | January 2021 |
| Creators | Beyene, Mussie Abraham |
| Publisher | Uppsala universitet, Institutionen för elektroteknik |
| Source Sets | DiVA Archive at Upsalla University |
| Language | English |
| Detected Language | English |
| Type | Student thesis, info:eu-repo/semantics/bachelorThesis, text |
| Format | application/pdf |
| Rights | info:eu-repo/semantics/openAccess |
| Relation | ELEKTRO-MFE ; 21001 |
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