2023
DOI: 10.56028/aetr.6.1.540.2023
|View full text |Cite
|
Sign up to set email alerts
|

Integrated forecasting model based on LSTM and TCN for short-term power load forecasting

Abstract: Power load forecasting is important to ensure the stability and reliability of regional power systems. Researchers have put forward many combined forecasting models, but most of them cannot capture the global characteristics of data well. So as to improve the accuracy of short-term power load forecasting, this paper puts forward a combined forecasting model based on long-term and short-term memory networks (LSTM) and time convolution networks (TCN). In terms of the power load data, the LSTM and TCN forecasting… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...

Citation Types

0
0
0

Publication Types

Select...

Relationship

0
0

Authors

Journals

citations
Cited by 0 publications
references
References 20 publications
0
0
0
Order By: Relevance

No citations

Set email alert for when this publication receives citations?