Research on Power Load Forecasting Method Based on LSTM Model
- Resource Type
- Conference
- Authors
- Cui, Can; He, Ming; Di, Fangchun; Lu, Yi; Dai, Yuhan; Lv, Fengyi
- Source
- 2020 IEEE 5th Information Technology and Mechatronics Engineering Conference (ITOEC) Technology and Mechatronics Engineering Conference (ITOEC), 2020 IEEE 5th Information. :1657-1660 Jun, 2020
- Subject
- Communication, Networking and Broadcast Technologies
Components, Circuits, Devices and Systems
Engineered Materials, Dielectrics and Plasmas
Engineering Profession
Robotics and Control Systems
Transportation
Load forecasting
Load modeling
Predictive models
Logic gates
Data models
Time series analysis
Power dispatching and controlling
deep learning
power load forecasting
LSTM
- Language
Power load forecasting is an important part of power system planning and the foundation of power system economic operation. It is very important for power system planning and operation. The LSTM forecast model is used to Get more accurate power load prediction results. According to the time series rule of power load, the LSTM prediction model for load prediction is established in this paper. A verification experiment has been done to reflect the effect of this method. Experimental results show that accuracy of power load prediction is increased by using LSTM model.