Temporal-Spatial Graph Neural Network for Wind Power Forecasting Considering the Blockage Effects
Author:
Affiliation:
1. Smart Innovation Norway,Energy Markets,Halden,Norway
2. Management and Economics Technical University of Denmark,Department of Technology,Lyngby,Denmark
3. Smart Innovation Norway,Section of Energy Markets,Halden,Norway
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10193875/10193865/10193907.pdf?arnumber=10193907
Reference29 articles.
1. Time Series Auto-Regressive Integrated Moving Average Model for Renewable Energy Forecasting
2. M2GSNet: Multi-Modal Multi-Task Graph Spatiotemporal Network for Ultra-Short-Term Wind Farm Cluster Power Prediction
3. Short-Term Wind Energy Forecasting Using Support Vector Regression
4. Deterministic and probabilistic wind power forecasting using a variational Bayesian-based adaptive robust multi-kernel regression model
5. Short-term wind power forecasting approach based on Seq2Seq model using NWP data
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