Study on Fine Wave Forecasting for Offshore Wind Farms. (1st March 2023)

• Record Type: Journal Article
• Authors: Zhang, Guofeng; Yin, Junjie; Cheng, Chen; Han, Qiqi; Li, Lianbing
• Is Part Of: Journal of physics. Volume 2452(2023)
• Publication Date: 2023-03-01
• Subjects: Physics -- Congresses; 530.5
• DOI: 10.1088/1742-6596/2452/1/012008
• Languages: English
• ISSNs: 1742-6588

Abstract

Abstract: In order to ensure the safety of offshore operation and maintenance personnel and the smooth progress of major offshore projects, this paper establishes a prediction model of wave height and wave period based on support vector regression (SVR). First, the observation data of Xiaochangshan meteorological station from August 2021 to July 2021 are used to build a prediction model, and the data are preprocessed, and parameters are optimized. Then, the model trained with nine characteristics is evaluated for error under the test set, and the comparison image between the predicted value and the actual wind wave height and wind wave period is output. Finally, the observation data of the meteorological station in early August 2021 are used for verification of one hour and one day (24 hours). The experimental results show that the model can predict the wave height and wave period of the next hour and day, and the maximum error is not more than 0.4m, which can effectively provide a reasonable technical reference for the short-term prediction of the effective wave height of offshore waves.