Research on Short-Term Load Forecasting of LSTM Regional Power Grid Based on Multi-Source Parameter Coupling
Regional power grid load has strong periodicity and randomness, and its load characteristics are affected by many factors. Traditional short-term power load-forecasting methods have certain limitations in accuracy and stability, especially when dealing with complex weather and voltage changes. To im...
Saved in:
| Main Authors: | Bo Li, Yaohua Liao, Siyang Liu, Chao Liu, Zhensheng Wu |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2025-01-01
|
| Series: | Energies |
| Subjects: | |
| Online Access: | https://www.mdpi.com/1996-1073/18/3/516 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Short-term Load Forecasting Based on CNN-LSTM with Quadratic Decomposition Combined
by: DENG Bowen, et al.
Published: (2023-08-01) -
A federated LSTM network for load forecasting using multi-source data with homomorphic encryption
by: Mengdi Wang, et al.
Published: (2025-03-01) -
Short-Term Water Demand Forecasting Based on LSTM Using Multi-Input Data
by: Dingtong Wang, et al.
Published: (2024-09-01) -
Hybrid Optimization based on Deep Learning Approach for Short-Term Load Forecast of Electricity Demand in Buildings
by: Charan Sekhar Makula, et al.
Published: (2024-06-01) -
Enhancing Short-Term Load Forecasting Accuracy in High-Volatility Regions Using LSTM-SCN Hybrid Models
by: Bingbing Tang, et al.
Published: (2024-12-01)