Slider Crank WEC Performance Analysis with Adaptive Autoregressive Filtering

Md Rakib Hasan Khan, H. Bora Karayaka, Yanjun Yan, Peter Tay, Yi Hsiang Yu

研究成果: Conference contribution同行評審

2 引文 斯高帕斯(Scopus)


This paper investigates a performance analysis of wave excitation force prediction to extract wave power for a slider crank power take-off system (PTOS) based on auto regressive (AR) filters. To efficiently convert wave energy into electricity, the prediction of wave excitation forces to keep the generator and the wave excitation force in sync is important for maximum energy extraction. The study shows a prediction methodology of half period and zero crossings in the practical scenario of irregular ocean waves. The prediction has been tested for different wave periods and with different filter orders. The prediction results have been used in the PTOS simulation to analyze the energy extraction. It has been shown that the prediction accuracy in the wave half period between the truth data and the predicted data drives the WEC energy extraction efficiency. The amplitude of the wave force is not used and hence the prediction deviation in the wave force amplitude does not affect the PTOS energy extraction. Further analysis shows that the optimum energy can be extracted at 15th order filter with moderate prediction horizon length.

主出版物標題2019 IEEE SoutheastCon, SoutheastCon 2019
發行者Institute of Electrical and Electronics Engineers Inc.
出版狀態Published - 4月 2019
事件2019 IEEE SoutheastCon, SoutheastCon 2019 - Huntsville, United States
持續時間: 11 4月 201914 4月 2019


名字Conference Proceedings - IEEE SOUTHEASTCON


Conference2019 IEEE SoutheastCon, SoutheastCon 2019
國家/地區United States


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