Wave prediction using wave rider position measurements and NARX network in wave energy conversion
Wave prediction using wave rider position measurements and NARX network in wave energy conversion
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DOI：
10.1016/j.apor.2018.10.016
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发表时间：
2019-01-01
影响因子：
4.3
通讯作者：
Abdelkhalik, Ossama
中科院分区：
文献类型：
--
作者：
Desouky, Mohammed A. A.;Abdelkhalik, Ossama
波浪能转换器（WEC）的几种控制方法需要预测未来的波面高程。可以使用即将到来的波浪中受控 WEC 前方位置处的表面高程测量来执行波浪表面高程的预测。人工神经网络 (ANN) 是一种强大的数据学习工具，本研究提出使用前方传感器（乘波浮标）测量波浪高程来预测 WEC 位置的表面高程。本研究采用外生输入非线性自回归网络（NARX NN）作为预测方法。模拟显示了预测波面高程的有希望的结果。本文还讨论了使用真实测量数据的挑战。
Several control methods of wave energy converters (WECs) need prediction in the future of wave surface elevation. Prediction of wave surface elevation can be performed using measurements of surface elevation at a location ahead of the controlled WEC in the upcoming wave. Artificial neural network (ANN) is a robust datalearning tool, and is proposed in this study to predict the surface elevation at the WEC location using measurements of wave elevation at ahead located sensor (a wave rider buoy). The nonlinear autoregressive with exogenous input network (NARX NN) is utilized in this study as the prediction method. Simulations show promising results for predicting the wave surface elevation. Challenges of using real measurements data are also discussed in this paper.