Issue |
E3S Web Conf.
Volume 375, 2023
8th International Conference on Energy Science and Applied Technology (ESAT 2023)
|
|
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Article Number | 03026 | |
Number of page(s) | 5 | |
Section | Energy Sustainability & Energy-Related Environmental Science | |
DOI | https://doi.org/10.1051/e3sconf/202337503026 | |
Published online | 27 March 2023 |
Medium- and long-term power load forecasting model
1
Yongchuan Power Supply Branch, State Grid Chongqing Electric Power Company,
Chongqing,
402160, China
2
North China Electric Power University,
Beijing,
102206, China
Power load is an important part of power system, and power load forecasting has an important impact on power system analysis, design and control. With the development of smart micro grid, load forecasting has gradually become an important module in the energy management system, It is “source, network, load and storage” “An important link in energy flow matching. The staged combined demand forecasting model of power grid based on neural network and polynomial regression is adopted, and judgment conditions are added to the neural network. If the training sample data does not converge in the neural network training process, the neural network forecasting is terminated, and the data is automatically transferred to the polynomial regression model to obtain the forecasting results. This method can be initially used for annual and monthly load forecasting. It is an intelligent micro grid The planning of has laid a certain technical foundation.
Key words: Load forecasting / Neural network / polynomial regression
© The Authors, published by EDP Sciences, 2023
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