Mr Thobani Hlophe¹

¹The University of Western Australia, Crawley, Australia

Many offshore operations can benefit from real-time forecasting of ocean surface waves, even for a few wave periods into the future. These operations include but are not limited to, ship navigation, load mitigation on floating offshore wind turbines, and control of wave energy converters. However, for sea states with directional spreading, wave prediction becomes increasingly difficult for currently existing models as the spreading increases. This study validates our newly developed prediction model which has a unique capability to exploit concurrent ocean surface displacement time histories measured by a buoy in three degrees of freedom. The model decomposes the observed time histories using the Fourier transform and finds an approximate representation of the whole wave field using a finite number of directional components by solving an over-determined system of equations. We optimize the buoy locations and representative directions to minimize the prediction error at the target prediction location. The performance of the scheme is tested using field data collected from the Southern Ocean off Albany, Western Australia. Good agreement is obtained between the prediction and the target time series which, in the tests, is measured by another buoy downwave of the array of observing buoys. With the availability of multiple solutions of optimal representative directions for the same observing array, we show that aggregating and weighted-averaging multiple predictions obtained using different sets of optimal representative directions improves the quality of prediction compared to individual predictions. Though the model is based on linear calculations of the initial phase information, it demonstrates robustness to the higher harmonics present in real wave records. It is also fast enough to be used for prediction in real-time.

Biography:

Thobani is a final-year Ph.D. student at the University of Western Australia’s Wave Energy Research Centre. His research focuses on developing a phase-resolved model for predicting ocean surface waves with particular applications in wave energy generation. This has the potential to improve the performance and survivability of wave power machines and hence make wave energy more economically viable. Ocean waves being a stochastic process, modeling entails heavy use of statistics and other mathematical techniques which suits Thobani’s background in mathematics. Thobani aspires to offer a cost-effective and easily accessible solution for the marine renewables sector.