- 1School of Mechanical and Electrical Engineering, Guangzhou University, Guangzhou, Guangdong, China
- 2College of Electrical Engineering, Guangxi University, Nanning, China
Editorial on the Research Topic
Impacts of complex terrain on wind power output and mechanisms to improve prediction accuracy
Random and intermittent shocks generated by large-scale wind farms continue to affect the safe and stable operations of power systems significantly (Hong et al., 2024; Li et al., 2024); hence, it is necessary to investigate the impacts of complex terrains on wind power outputs and mechanisms to improve their prediction accuracies. To this end, we host this Research Topic that contains nine final articles. Among these works, Kristianti et al. investigated the influences of air flow features on alpine wind energy potential. Man et al. proposed a multidevice wind turbine power generation forecasting model aimed at wind farms. Zhang et al. present a meta reservoir computing method while Konstantinou and Hatziargyriou establish a model combining convolutional neural networks and DeepSHAP to enhance the accuracy of wind power forecasting. Wang et al. present an incremental feedforward collective pitch control method for the wind turbine. Zhou et al. propose an interval model for the wind turbine power curve. Xu et al. survey some energy management strategies for a loop microgrid with wind energy prediction and energy storage systems. Wang and Liao propose a short-term hybrid prediction model for wind speed prediction. Finally, Gao et al. present a detailed review of the interval reservoir computing approach and examine some case studies. Overall, these articles cover a wide range of research topics and provide highly valuable research methods and models that are expected to serve as excellent references for researchers working on related research topics, particularly those related to the impacts of complex terrains on wind power outputs and mechanisms to improve their prediction accuracies.
Author contributions
LC: formal analysis, funding acquisition, project administration, supervision, writing–original draft, and writing–review and editing. LY: formal analysis, validation, writing–original draft, and writing–review and editing.
Funding
The authors declare that financial support was received for the research, authorship, and/or publication of this article. This work was supported by the Guangdong Basic and Applied Basic Research Foundation (no. 2022A1515010699).
Conflict of interest
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
Publisher’s note
All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations or those of the publisher, editors, and reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.
References
Hong, S., McMorland, J., Zhang, H., Collu, M., and Halse, K. H. (2024). Floating offshore wind farm installation, challenges and opportunities: a comprehensive survey. Ocean. Eng., 304, 117793. doi:10.1016/j.oceaneng.2024.117793
Li, B., Dong, Y., Jiao, X., Chen, X., Li, B., and Ji, L. (2024). Study on the calculation method of electrical quantity for connection line open-phase operation of wind farm connected to MMC-HVDC Considering negative sequence current suppression. Int. J. Electr. Power and Energy Syst., 159, 110056.doi:10.1016/j.ijepes.2024.110056
Keywords: accurate wind power forecasting, renewable-energy grid connection and consumption, wind turbine parameter optimization, data-driven approach, economic scheduling considering wind power fluctuations
Citation: Cheng L and Yin L (2024) Editorial: Impacts of complex terrain on wind power output and mechanisms to improve prediction accuracy. Front. Energy Res. 12:1468799. doi: 10.3389/fenrg.2024.1468799
Received: 22 July 2024; Accepted: 05 August 2024;
Published: 20 August 2024.
Edited and reviewed by:
David Howe Wood, University of Calgary, CanadaCopyright © 2024 Cheng and Yin. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
*Correspondence: Lefeng Cheng, chenglefeng@gzhu.edu.cn