Research on Model Integration Strategy in Shortterm Power Load Forecasting
- Resource Type
- Conference
- Authors
- Chen, Junxingxu; Li, Ting; Wang, Jian; Wang, Guorui; Zou, Yanhui; Lv, Fengyi
- Source
- 2019 IEEE 3rd Conference on Energy Internet and Energy System Integration (EI2) Energy Internet and Energy System Integration (EI2), 2019 IEEE 3rd Conference on. :1408-1412 Nov, 2019
- Subject
- Power, Energy and Industry Applications
Load modeling
Predictive models
Training
Load forecasting
Biological system modeling
Forecasting
Mathematical model
short-term load forecasting
ensemble model
model integration strategy
SVR
- Language
Multi-model ensemble model is an effective method to improve forecast accuracy in short-term load forecasting which is becoming popular in recent years. However, the research on model integration method is relatively limited. This paper investigates the performance of combining different load forecasting method based on multiple integration method. Nine integration strategies are considered and the effectiveness of these strategies are validated based on ISO New England public dataset. Case studies demonstrate that the accuracy of ensemble models significantly outperform that of the benchmark methods in terms of mean absolute percentage error.