Fine-grained ultra-short-term wind power forecasting based on Temporal Fusion Transformers integrated with turbine power time series clustering

This publication has 33 references indexed in Scilit:

• Review of several key processes in wind power forecasting: Mathematical formulations, scientific problems, and logical relations
  Applied Energy, 2024
• A novel ultra-short-term wind power forecasting method based on TCN and Informer models
  Computers and Electrical Engineering, 2024
• A review of short-term wind power generation forecasting methods in recent technological trends
  Energy Reports, 2024
• Wind power forecasting method of large-scale wind turbine clusters based on DBSCAN clustering and an enhanced hunter-prey optimization algorithm
  Energy Conversion and Management, 2024
• Interpretable building energy consumption forecasting using spectral clustering algorithm and temporal fusion transformers architecture
  Applied Energy, 2023
• A review of ultra-short-term forecasting of wind power based on data decomposition-forecasting technology combination model
  Energy Reports, 2022
• Spatial–temporal short-term load forecasting framework via K-shape time series clustering method and graph convolutional networks
  Energy Reports, 2022
• M2TNet: Multi-modal multi-task Transformer network for ultra-short-term wind power multi-step forecasting
  Energy Reports, 2022
• Ultra-short term wind prediction with wavelet transform, deep belief network and ensemble learning
  Energy Conversion and Management, 2020
• Time series clustering and classification via frequency domain methods
  WIREs Computational Statistics, 2018