Recurrent Neural Network Based Short-Term Load Forecast with Spline Bases and Real-Time Adaptation

Recurrent Neural Network Based Short-Term Load Forecast with Spline Bases and Real-Time Adaptation

Short-term load forecast (STLF) plays an important role in power system operations. This paper proposes a spline bases-assisted Recurrent Neural Network (RNN) for STLF with a semi-parametric model being adopted to determine the suitable spline bases for constructing the RNN model. To reduce the expo...

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Bibliographic Details
Main Authors: Tzu-Lun Yuan, Dian-Sheng Jiang, Shih-Yun Huang, Yuan-Yu Hsu, Hung-Chih Yeh, Mong-Na Lo Huang, Chan-Nan Lu
Format: Article
Language:English
Published: MDPI AG 2021-06-01
Series:Applied Sciences
Subjects:
exponentially weighted moving average
LASSO model selection
semi-parametric model
short term load forecast
spline bases
Online Access:https://www.mdpi.com/2076-3417/11/13/5930

Internet

https://www.mdpi.com/2076-3417/11/13/5930

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