Your Location:
Home >
Browse articles >
Power Prediction Method for Offshore Wind Farms Based on Temporal Convolutional Network-Transformer
Power Generation Technology Vol. 46, Issue 6, Pages: 1123-1132(2025)
New Energy|Updated:2026-06-29
|
Power Prediction Method for Offshore Wind Farms Based on Temporal Convolutional Network-Transformer
- “The prediction of offshore wind power is relatively difficult. The research team has integrated time-series convolutional networks with Transformer architecture and introduced discrete cosine transform technology to extract frequency domain features, significantly improving the accuracy of power generation prediction and providing strong support for the efficient operation of offshore wind farms.”
DOI:10.12096/j.2096-4528.pgt.24251
Revised:2025-03-28
Scan QR Code
17
Views
14
Downloads
4
CSCD
Alert me when the article has been cited
Submit
Related Articles
Research on Large-Signal Stability Assessment Methods of DC Microgrids Based on Artificial Intelligence
Equivalent Modeling for Active Distribution Network Based on Hierarchical Double Deep Q Network
Multi-User Short-Term Load Prediction Method Based on Frequency-Domain Enhanced Transformer
Review of Research on Wind-Solar-Hydro Complementary Power Generation Systems
Analysis of Key Technologies and Development Prospects for Renewable Energy-Powered Water Electrolysis for Hydrogen Production Based on Artificial Intelligence
Related Author
LIU Sucheng
LI Long
HONG Tao
LIU Xiaodong
LUAN Li
WANG Chen
LU Jiangang
GUO Wenxin
Related Institution
School of Electrical and Information Engineering, Anhui University of Technology, Maanshan
Key Lab of Power Electronics and Motion Control (Anhui University of Technology), Maanshan
Power Dispatching Control Center, Guangdong Power Grid Co., Ltd.
School of Electric Power, South China University of Technology
Faculty of Electrical and Control Engineering, Liaoning Technical University

