Short-term Load Forecasting Method Based on Artificial Intelligence Highway Neural Network

Zhang, Jinjin; Wang, Tao; Wu, Junyong; Zhu, Hainan; Dong, Liang; Li, Fengshuo

doi:10.1109/ei252483.2021.9713655

2021 IEEE 5th Conference on Energy Internet and Energy System Integration (EI2) 2021

DOI: 10.1109/ei252483.2021.9713655

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Short-term Load Forecasting Method Based on Artificial Intelligence Highway Neural Network

Jinjin Zhang

Tao Wang²,

Junyong Wu

et al.

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Two-Stage Short-Term Power Load Forecasting Based on RFECV Feature Selection Algorithm and a TCN–ECA–LSTM Neural Network

Liang

Zhang

et al. 2023

Energies

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To solve the problem of feature selection and error correction after mode decomposition and improve the ability of power load forecasting models to capture complex time series information, a two-stage short-term power load forecasting method based on recursive feature elimination with a cross validation (RFECV) algorithm and time convolution network–efficient channel attention mechanism–long short-term memory network (TCN–ECA–LSTM) is presented. First, the load sequence is decomposed into a relatively stable set of modal components using variational mode decomposition. Then, the RFECV-based method filters the feature set of each modal component to construct the best feature set. Finally, a two-stage prediction model based on TCN–ECA–LSTM is established. The first stage predicts each modal component and the second stage reconstructs the load forecast based on the predicted value of the previous stage. This paper takes actual data from New South Wales, Australia, as an example, and the results show that the method proposed in this paper can build the feature set reliably and efficiently and has a higher accuracy than the conventional prediction model.

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Two-Stage Short-Term Power Load Forecasting Based on RFECV Feature Selection Algorithm and a TCN–ECA–LSTM Neural Network

Liang

Zhang

et al. 2023

Energies

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Short-term Load Forecasting Method Based on Artificial Intelligence Highway Neural Network

Cited by 1 publication

References 1 publication

Two-Stage Short-Term Power Load Forecasting Based on RFECV Feature Selection Algorithm and a TCN–ECA–LSTM Neural Network

Two-Stage Short-Term Power Load Forecasting Based on RFECV Feature Selection Algorithm and a TCN–ECA–LSTM Neural Network

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