This article deals with the case study of a marina located in Roccella Jonica (Italy), where a wave energy harvester belonging to the family of U-Oscillating Water Columns (U-OWC) is going to be installed. U-OWCs are wave energy harvesters composed by a water column exposed to the action of random sea waves and an air pocket connected to the atmosphere by a Power Take - Off (PTO) system. In Roccella Jonica, this device is going to be embedded in a vertical breakwater expanding the main layout of the infrastructure. For ensuring the structural safety of the system, to characterize statistically its response peaks in severe environmental conditions is important. In this context, one of the main difficulties is utilizing appropriate environmental conditions representing real extreme events at the installation site. This article proposes to adopt the DNV trapezoidal storm model for representing the time history of an extreme event in conjunction with a nonlinear U-OWC model. Relevant Monte Carlo simulations show that the DNV storm model provides peak distributions that are rather close to the ones obtained by processing real storm time histories. Thus, it can be adopted for checking the performance of the system in extreme conditions.

Response Statistics of U-Oscillating Water Column Energy Harvesters Exposed to Extreme Storms: Application to the Case Study of Roccella Jonica (Italy)

Arena Felice;Valentina Laface;Giovanni Malara
;
2021-01-01

Abstract

This article deals with the case study of a marina located in Roccella Jonica (Italy), where a wave energy harvester belonging to the family of U-Oscillating Water Columns (U-OWC) is going to be installed. U-OWCs are wave energy harvesters composed by a water column exposed to the action of random sea waves and an air pocket connected to the atmosphere by a Power Take - Off (PTO) system. In Roccella Jonica, this device is going to be embedded in a vertical breakwater expanding the main layout of the infrastructure. For ensuring the structural safety of the system, to characterize statistically its response peaks in severe environmental conditions is important. In this context, one of the main difficulties is utilizing appropriate environmental conditions representing real extreme events at the installation site. This article proposes to adopt the DNV trapezoidal storm model for representing the time history of an extreme event in conjunction with a nonlinear U-OWC model. Relevant Monte Carlo simulations show that the DNV storm model provides peak distributions that are rather close to the ones obtained by processing real storm time histories. Thus, it can be adopted for checking the performance of the system in extreme conditions.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.12318/77377
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