A Spatiotemporal Directed Graph Convolution Network for Ultra-Short-Term Wind Power Prediction
Author:
Affiliation:
1. College of Information and Electrical Engineering, China Agricultural University, Beijing, China
2. Department of Electrical Power Engineering, Tsinghua University, Beijing, China
Funder
Science and Technology Project of State Grids Corporation of China
Science and Technology Project
National Natural Science Foundation of China
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
Renewable Energy, Sustainability and the Environment
Link
http://xplorestaging.ieee.org/ielx7/5165391/9994274/09857618.pdf?arnumber=9857618
Reference32 articles.
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4. Spatiotemporal Optimization Through Gaussian Process-Based Model Predictive Control: A Case Study in Airborne Wind Energy
5. Scientometric review of artificial intelligence for operations & maintenance of wind turbines: The past, present and future
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