Online-algorithm using adaptive filters for short-term wave prediction and its implementation

The control of wave energy converters can be significantly improved by taking into account the future incident wave elevation. For optimized energy yield it is, therefore, highly desirable to include wave prediction algorithms in the real-time control system. Recent research has shown that it is possible to predict up to one wave period with reasonable accuracy using rather simple autoregressive models, forecasting the wave elevation based on the past time series measured at the device itself. So far, the focus has been on the theoretical feasibility of short term wave prediction. Comparably less publications deal with issues related to the real-time implementations of these prediction algorithms: causality, simplicity and robustness. In this study, adaptive filters are employed to estimate the future wave elevation. It is shown that they achieve about half a wave period with reasonable accuracy. Their real-time implementation is undemanding. Furthermore, their adaptability makes them robust to changing environmental conditions and only a minimum of supervisory control is required. The real-time feasibility is demonstrated by an example implementation on a programmable logic controller and measurement data from a wave rider buoy located in the North Sea.