Short-term load forecasting based on multi-frequency sequence feature analysis and multi-point modified FEDformer
Given the complexity and dynamic nature of short-term load sequence data, coupled with prevalent errors in traditional forecasting methods, this study introduces a novel approach for short-term load forecasting. The method integrates multi-frequency sequence feature analysis and multi-point correcti...
Saved in:
Main Authors: | Kaiyuan Hou, Xiaotian Zhang, Junjie Yang, Jiyun Hu, Guangzhi Yao, Jiannan Zhang |
---|---|
Format: | Article |
Language: | English |
Published: |
Frontiers Media S.A.
2025-01-01
|
Series: | Frontiers in Energy Research |
Subjects: | |
Online Access: | https://www.frontiersin.org/articles/10.3389/fenrg.2024.1524319/full |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Short-Term Power Load Prediction Method Based on VMD and EDE-BiLSTM
by: Yibo Lai, et al.
Published: (2025-01-01) -
Short-Term Load Forecasting in Power Systems Based on the Prophet–BO–XGBoost Model
by: Shuang Zeng, et al.
Published: (2025-01-01) -
Forecasting consumption of electric energy by using wavelet transform
by: V. I. Skorokhodov, et al.
Published: (2021-06-01) -
Fusion ConvLSTM-Net: Using Spatiotemporal Features to Increase Residential Load Forecast Horizon
by: Abhishu Oza, et al.
Published: (2025-01-01) -
Comparison of artificial neural network models of categorized daily electric load
by: Vildan Evren, et al.
Published: (2021-04-01)