GGNet: A novel graph structure for power forecasting in renewable power plants considering temporal lead-lag correlations
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DOI: 10.1016/j.apenergy.2024.123194
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- Yeeun Moon & Younjeong Lee & Yejin Hwang & Jongpil Jeong, 2024. "Long Short-Term Memory Autoencoder and Extreme Gradient Boosting-Based Factory Energy Management Framework for Power Consumption Forecasting," Energies, MDPI, vol. 17(15), pages 1-21, July.
- Haoda Ye & Qiuyu Zhu & Xuefan Zhang, 2024. "Short-Term Load Forecasting for Residential Buildings Based on Multivariate Variational Mode Decomposition and Temporal Fusion Transformer," Energies, MDPI, vol. 17(13), pages 1-22, June.
- Afshin Tatar & Amin Shokrollahi & Abbas Zeinijahromi & Manouchehr Haghighi, 2024. "Deep Learning for Predicting Hydrogen Solubility in n-Alkanes: Enhancing Sustainable Energy Systems," Sustainability, MDPI, vol. 16(17), pages 1-24, August.
- Yanan Xue & Jinliang Yin & Xinhao Hou, 2024. "Short-Term Wind Power Prediction Based on Multi-Feature Domain Learning," Energies, MDPI, vol. 17(13), pages 1-25, July.
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Keywords
GNN; Renewable power plants; Multiple granularity groups; Adjacency matrix;All these keywords.
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