Sandia National Laboratories: Vincent Neary
North Carolina State University: Ruoying He, M. Nabi Allahdadi
October 2018 – September 2019
Technical and business decision-making by the wave energy converter industry is currently hindered by a lack of wave resource data. It needs wave energy resource maps to identify the best project sites (hot spots); data sets consisting of a multitude of parameters, e.g., those recommended by the IEC Technical Specification, IEC 62600-101 TS (Folley et al. 2012); information on wave climate and energy resources to characterize opportunities and risks at these project sites; and a wave energy resource/power classification scheme, similar to the wind industry, to codify these opportunities and risks, and to standardize their designs. A basic wave resource classification has been developed based on the available wave energy, primarily using WWIII 30-year hindcast data (Chawla et al., 2013). This data set focuses primarily on deep and intermediate water depths, with very limited data available for shallow water sites. In addition, the design of the technology to be used for energy generation depends greatly on secondary wave parameters such as the directional and frequency spread of the spectrum.
NCSU will provide technical support to develop a high-resolution spectral wave model for the Puerto Rico and Gulf of Mexico coastal region and to generate a 31-year hindcast to allow calculation of statistics used for wave energy resource classification.
Work is in progress.