Short-Term Electricity Load Forecasting Based on Temporal Fusion Transformer Model

Electricity load forecasting plays an important role in the operation of power systems. Inaccurate forecast would reduce the safety of power supply and affect the economic and social activities as well as national defense and security. In addition, the forecast results also support decision-making o...

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Veröffentlicht in:	IEEE access 2022, Vol.10, p.106296-106304
Hauptverfasser:	Huy, Pham Canh, Minh, Nguyen Quoc, Tien, Nguyen Dang, Anh, Tao Thi Quynh
Format:	Artikel
Sprache:	eng
Schlagworte:	artificial intelligence Artificial neural networks Autoregressive processes Decision making Economic forecasting Electrical loads Electricity Forecasting load forecasting Load modeling Logic gates Neural networks Power systems Predictive models recurrent neural network Recurrent neural networks Statistical analysis Statistical models temporal fusion transformer
Online-Zugang:	Volltext
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