Short-term power load forecasting: an integrated approach utilizing variational mode decomposition and TCN–BiGRU

Z Zou, J Wang, NE, C Zhang, Z Wang, E Jiang - Energies, 2023 - mdpi.com
Accurate short-term power load forecasting is crucial to maintaining a balance between
energy supply and demand, thus minimizing operational costs. However, the intrinsic …

Short-term load forecasting based on VMD and deep TCN-based hybrid model with self-attention mechanism

Q Xiong, M Liu, Y Li, C Zheng, S Deng - Applied Sciences, 2023 - mdpi.com
Due to difficulties with electric energy storage, balancing the supply and demand of the
power grid is crucial for the stable operation of power systems. Short-term load forecasting …

A New Hybrid Model Based on SCINet and LSTM for Short-Term Power Load Forecasting

M Liu, Y Li, J Hu, X Wu, S Deng, H Li - Energies, 2023 - mdpi.com
A stable and reliable power system is crucial for human daily lives and economic stability.
Power load forecasting is the foundation of dynamically balancing between the power …

Short-term load forecasting using EMD with feature selection and TCN-based deep learning model

M Liu, X Sun, Q Wang, S Deng - Energies, 2022 - mdpi.com
Short-term load forecasting (STLF) has a significant role in reliable operation and efficient
scheduling of power systems. However, it is still a major challenge to accurately predict …

Deep Learning‐Assisted Short‐Term Power Load Forecasting Using Deep Convolutional LSTM and Stacked GRU

FUM Ullah, A Ullah, N Khan, MY Lee, S Rho… - …, 2022 - Wiley Online Library
Over the decades, a rapid upsurge in electricity demand has been observed due to
overpopulation and technological growth. The optimum production of energy is mandatory to …

Deep learning-driven hybrid model for short-term load forecasting and smart grid information management

X Wen, J Liao, Q Niu, N Shen, Y Bao - Scientific Reports, 2024 - nature.com
Accurate power load forecasting is crucial for the sustainable operation of smart grids.
However, the complexity and uncertainty of load, along with the large-scale and high …

[HTML][HTML] Short-term power load forecasting based on AC-BiLSTM model

F Liu, C Liang - Energy Reports, 2024 - Elsevier
The practice of ultra-short-term power load forecasting serves as a critical strategy for
enabling rapid response and real-time dispatch in power systems. By improving the …

[HTML][HTML] A 24-Step Short-Term Power Load Forecasting Model Utilizing KOA-BiTCN-BiGRU-Attentions

M Xu, W Liu, S Wang, J Tian, P Wu, C Xie - Energies, 2024 - mdpi.com
With the global objectives of achieving a “carbon peak” and “carbon neutrality” along with
the implementation of carbon reduction policies, China's industrial structure has undergone …

Short-term load forecasting using channel and temporal attention based temporal convolutional network

X Tang, H Chen, W Xiang, J Yang, M Zou - Electric Power Systems …, 2022 - Elsevier
Load forecasting is the foundation of power system operation and planning. Accurate load
forecasting can secure the safe and reliable operation of the power system, cut power …

Short-term power load forecasting based on hybrid feature extraction and parallel BiLSTM network

J Han, P Zeng - Computers and Electrical Engineering, 2024 - Elsevier
Electricity is a vital resource for societal and economic activities. Accurate electricity load
forecasting can effectively reduce costs and enhance energy efficiency. Nevertheless …