Super-resolution perception for wind power forecasting by enhancing historical data

Liu, Guolong and Zhang, Shuwen and Zhao, Huan and Liu, Jinjie and Liang, Gaoqi and Zhao, Junhua and Sun, Guangzhong (2022) Super-resolution perception for wind power forecasting by enhancing historical data. Frontiers in Energy Research, 10. ISSN 2296-598X

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Abstract

As an important part of renewable energy, wind power is crucial to the realization of carbon neutrality. It is worth studying on how to accurately predict the wind output so that it can be integrated into the power grid as much as possible to enhance its utilization rate. In this article, a data enhancement method and a framework are proposed to assist wind power forecasting. The proposed method uses the super-resolution perception technology to first detect the completeness and correctness of historical meteorological and wind power data collected by industrial devices. Then, the detected errors are corrected and the missing data are recovered to make the data complete. The frequency of the data is then increased using the proposed method so that the data become complete high-frequency data. Based on the enhanced complete high-frequency data with more detailed characteristics, more accurate forecasts of wind power can be achieved, thereby improving the utilization rate of wind power. Experiments based on public datasets are used to demonstrate the effectiveness of the proposed method and framework. With the proposed method and framework, higher frequency data with more detailed information can be achieved, thereby providing support for accurate wind power prediction that was not possible before.

Item Type: Article
Subjects: West Bengal Archive > Energy
Depositing User: Unnamed user with email support@westbengalarchive.com
Date Deposited: 13 May 2023 07:00
Last Modified: 18 Jun 2024 07:31
URI: http://article.stmacademicwriting.com/id/eprint/754

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