Abstract
Experimental results for common wave energy converter (WEC) metrics such as power capture, capture width, wave-to-wire efficiency, and power take-off (PTO) forces are all subject to uncertainty. These uncertainties are inherent due to the accuracy of the sensors that collect measurements (epistemic or Type B) and from the repeatability of the experiments (aleatoric or Type A). Understanding the uncertainty of common WEC metrics is important for advancing the technological readiness level (TRL) of devices and improving confidence in their performance, but relatively little work has been performed in this area and uncertainty often goes unreported. This work aims to identify the major sources of uncertainty in WEC testing and recommend methods to reduce uncertainty in experimental testing and inform hydrodynamic models.
Nonlinearities in the waves and the WEC may be a major consideration for uncertainty. In this work, we tested linear and higher-order nonlinear waves in both regular and irregular conditions to understand the effect they may have on commonly reported metrics. This testing was conducted with the Laboratory Upgrade Point Absorber (LUPA) at the O.H. Hinsdale Wave Research Laboratory in a 3.695-meter water depth. LUPA is an open-source, two-body point absorber wave energy converter built by Oregon State University. It has a 1-meter diameter float connected through a belt-driven PTO to a spar with a heave plate. LUPA was moored in the Large Wave Flume and operated with six degrees of freedom to represent a more realistic deployment of a floating WEC.
The PTO controls utilized impedance-matched informed values for the velocity-dependent damping and positive and negative position-dependent stiffness to maximize power capture and increase the complexity and therefore the applicability of the uncertainty analysis. Additionally, viscous drag coefficients and frictional damping terms were characterized in previous testing for validation of a WEC-Sim numerical model which is used to incorporate uncertainty into models. The temperature dependency of friction and uncertainty will also be explored in this work. Uncertainty analysis is important for rigorous data analysis and communicating findings with confidence; therefore, suggestions will also be given for standards development (e.g., IEC).