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Statistical Distributions and WEC Classes

Date: July 09, 2018 at 17:07 GMT

Classification systems have provided useful benefits when considering the design of energy conversion systems. Typically, a classification system aims to ensure that a new design is compatible with multiple sites across a significant number of locations around the globe, thus supporting the rollout of the technology. When designing a specific class of devices, technology developers may standardise their approach, potentially avoiding under- or over-designing the systems. Such practices can in turn help to limit the costs as well as contain the risks of failures during the project lifetime.
In the present work, a probabilistic approach to wave energy converter (WEC) design is considered. Extreme loads with 5, 25 and 50-year recurrence interval (surge and heave excitation forces) are calculated at a number of sites along the Western European (WE) coast for two types of point absorber WECs. In an attempt to define WEC classes, the results were analysed in parallel with the extreme values of the free-surface elevation at the sites.
To define the environmental conditions at the sites, the variation in the shapes of the environmental contours was assessed using multiple probability distributions (e.g. inverse gaussian or generalised extreme functions). Essentially, the variability observed in the results and the potential impact on the design process highlight the critical need for procedures to monitor the quality of the statistical fit. Future work can extend the assessment to the statistical distributions used to characterise resistance (load) and stress.
Using short-term extreme value analysis, the long-term extreme values for the free-surface elevation and the linear surge and heave excitation forces were derived, showing to a considerable spread which can be associated with the large range of environmental conditions across the WE coast, and its effects on the WEC responses. However, when combining the WEC forces and free-surface elevation data, a typical response emerges, and the long-term extreme values converge towards a reference distribution, highlighting a possible WEC class effect.
Although preliminary, the rationale presented in this study aims to contribute to the definition of a WEC classification system that may ultimately assist in the overall WEC design process.

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