Wavelet Transform Convolution and Transformer-Based Learning Approach for Wind Power Prediction in Extreme Scenarios
Wind power generation is subjected to complex and variable meteorological conditions, resulting in intermittent and volatile power generation. Accurate wind power prediction plays a crucial role in enabling the power grid dis... | Find, read and cite all the research you need on Tech Science Press
Authors
- Hongzhu Tao
- Leibao Wang (ORCID: https://orcid.org/0000-0001-6748-4642)
- Yonghui Sun (ORCID: https://orcid.org/0000-0002-9507-8673)
- Jifeng Liang
- Xiaofei Li (ORCID: https://orcid.org/0000-0002-0470-7949)
- Ziwei Zhang (ORCID: https://orcid.org/0000-0002-6102-8117)
- Qiang Wang (ORCID: https://orcid.org/0009-0009-3117-9078)
Publication Details
- Journal
- Computer Modeling in Engineering & Sciences
- Published
- 2025-01-01
- DOI
- https://doi.org/10.32604/cmes.2025.062315
- Citations
- 6
- Primary Topic
- Energy Load and Power Forecasting
- Type
- article
- Field-Weighted Citation Impact
- 4.38
Funders
- State Grid Corporation of China
- Science and Technology Project of State Grid