Issue |
MATEC Web Conf.
Volume 336, 2021
2020 2nd International Conference on Computer Science Communication and Network Security (CSCNS2020)
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Article Number | 05021 | |
Number of page(s) | 5 | |
Section | Computer Science and System Design | |
DOI | https://doi.org/10.1051/matecconf/202133605021 | |
Published online | 15 February 2021 |
Short-term power load forecasting based on I-GWO-KELM algorithm
1 Shandong Xiehe University, Computer College, Jinan, China
2 Jinan Bodor CNC Machine Co., Ltd. Jinan, China
* Corresponding author: buct_cxy@163.com
In this paper, I-GWO-KELM algorithm is used for short-term power load forecasting. Normalize the power data and meteorological data of the short-term power load, and use GWO to optimize the regularization coefficient of KELM and the RBF kernel parameters. To apply the model to short-term power load forecasting to obtain simulations for the next 24 hours and 168 hours curve. Experiments show that the improved model I3-GWO-KELM proposed in this paper has the best effect. The improvement of GWO in this paper is effective and feasible. In the application of short-term power load forecasting, the IGWO-KELM model is more accurate than the ELM and KELM models.
© The Authors, published by EDP Sciences, 2021
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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