Exploring Uncertainties and Challenges in Wave Energy Resource Assessment

We evaluate the uncertainties in wave parameters that are critical for the wave energy sector using the high-quality Mediterranean waves dataset from the Copernicus Marine Service. The reanalysis dataset is benchmarked against data from buoys deployed offshore south Spain. While the reanalysis offers accurate predictions of wave height and period, wellcapturing their variability, it slightly underpredicts them within the operational range of wave energy converters. During extreme waves (wave energy converter survival mode conditions), the model underestimates the wave height marginally. We demonstrate the applicability of two bias correction techniques: Delta-change and empirical quantile mapping. While both are effective in reducing uncertainty, the empirical quantile mapping method outperforms the former for extreme waves. This study seeks to improve the accuracy of wave energy resource assessments by providing a comprehensive set of guidelines outlining a systematic approach to address uncertainties. The guidelines cover essential aspects such as data collection and preparation, uncertainty evaluation, and bias correction implementation and efficiency assessment. The framework ensures the integrity of the data and the robustness of the model performance, potentially facilitating the preparation of future resource projections.