Offshore wind turbine wind speed power anomaly data cleaning method based on RANSAC regression and DBSCAN clustering

Author:

Zou Mingheng1,Zhou Bin1,Wang Bubin1,Liu Qi1,Zhao Rong1,Dai Minglu1,Rao Zhao1,Wang Yijing1

Affiliation:

1. Southeast University,School of Energy and Environment,Nanjing,China

Funder

National Natural Science Foundation of China

Publisher

IEEE

Reference25 articles.

1. Construction and Evolution of China’s New Power System Under Dual Carbon Goal;Ren;Power System Technology,2022

2. Global wind report 2023[EB/OL],2023

3. Review of Voltage Source Converter-based High Voltage Direct Current Integrated Offshore Wind Farm on Providing Frequency Support Control;Yao;High Voltage Engineering,2021

4. Effect investigation of yaw on wind turbine performance based on SCADA data

5. Review of Key Technologies for Operation Control and Maintenance of Offshore Wind Farm;Ge;Proceedings of the CSEE,2022

Cited by 1 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Combined Cleaning of Abnormal Data of Offshore Wind Turbines Based on Deep Learning;2024 6th International Conference on Energy Systems and Electrical Power (ICESEP);2024-06-21

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