Developing wave energy converter technology requires physical-scale model experiments. To use and compare such experimental data reliably, its quality must be quantified through an uncertainty analysis. To avoid uncertainty analysis problems for wave energy converter models, such as providing partial derivatives for time-varying quantities within numerous data
reduction equations, we explored the use of a practical alternative:the Monte Carlo method (MCM). We first set out the principles of uncertainty analysis and the MCM. After, we present our application of the MCM for propagating uncertainties in a generic Oscillating Water Column wave energy converter experiment. Our results show the MCM is a straightforward and accurate method to propagate uncertainties in the experiment; thus, quantifying the quality of experimental data in terms of power performance. The key conclusion of this work is that, given the demonstrated relative ease in performing uncertainty analysis using the MCM, experimental results reported in the future literature of wave energy converter modelling should be
accompanied by the uncertainty in those results. More broadly, this study aims to precipitate awareness among the wave energy community of the importance of quantifying the quality of
modelling data through an uncertainty analysis. We therefore recommend future guidelines and specifications pertinent to uncertainty analysis for wave energy converters, such as those
developed by the International Towing Tank Conference (ITTC) and International Electrotechnical Commission (IEC), to incorporate the MCM with a practical example.