Renewable energy resource inventories show that ocean waves are one of the most energy dense untapped resources in the world, and present an opportunity to generate significant quantities of electricity. To accurately assess the levels of usable energy over long periods, a parametric representation of the raw wave resource is required. This study investigates the variability across four wave energy assessment methods, and two input data sources, to quantify the uncertainties in WEC power production assessments. Two conventional methods were tested: a time-series method and a standard spectral method with a generic spectral shape. Two higher fidelity techniques were additionally studied; an aggregate spectral and a partitioned spectral method.
Annual WEC energy production assessments varied between 472 MWh and 543 MWh, a difference of 15%. The partitioned spectral method is shown to minimize prediction uncertainties, yet results in a 14% reduction in annual WEC energy production and increasing power variability. Spectral shape has limited impact on power estimates and energy production assessments, while the numerical wave model data can underestimate annual energy estimates by up to 13%. These uncertainties significantly impact the feasibility of wave energy developments and need to be accounted for as the industry matures.