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  • 标题:Long-term wave prediction and analysis based on time-series analysis
  • 本地全文:下载
  • 作者:Liangliang Liu ; Shuting Huang ; Yanjun Liu
  • 期刊名称:IOP Conference Series: Earth and Environmental Science
  • 印刷版ISSN:1755-1307
  • 电子版ISSN:1755-1315
  • 出版年度:2020
  • 卷号:514
  • 期号:3
  • 页码:1-5
  • DOI:10.1088/1755-1315/514/3/032002
  • 语种:English
  • 出版社:IOP Publishing
  • 摘要:The efficiency of the oscillating float-type wave energy devices is closely related to the wave conditions in its working area. Seasonal changes in actual sea conditions are obvious, and they vary greatly throughout the year. Therefore, it is necessary to analyse and predict the wave, and adjust the oscillating float-type wave energy device's parameters according to the wave conditions to improve the efficiency. Based on the analysis of the long-term wave variation and the short-term stationary characteristics of the wave, the moving regression algorithm is used to predict the wave. Adjust the device parameters according to the wave condition prediction data, and match the wave power and load power to achieve a certain efficiency in the wide power range of the device. The research results can be used for variable load control of wave energy devices.
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