| Issue |
E3S Web Conf.
Volume 256, 2021
2021 International Conference on Power System and Energy Internet (PoSEI2021)
|
|
|---|---|---|
| Article Number | 02022 | |
| Number of page(s) | 5 | |
| Section | Energy Internet R&D and Smart Energy Application | |
| DOI | https://doi.org/10.1051/e3sconf/202125602022 | |
| Published online | 10 May 2021 | |
An algorithm with LightGBM + SVM fusion model for the assessment of dynamic security region
1 Department of Electrical Engineering, Tsinghua University, Beijing, 100084, China
2 State Grid Ningxia Electric Power Co. Ltd., Yinchuan, 750000, China
* Email: liangll19@mails.tsinghua.edu.cn
With the development of energy transition, the complexity of power systems’ structure, planning and operation is continuously increasing. As to quickly and accurately assess the dynamic security region of power system, there are prominent problems with traditional manual analysis method, i.e. the rules’ roughness and a low calculation efficiency while data mining approach could provide a new way to get off such problems. Considering that the performance of SVM algorithm depends on feature selection and the LightGBM, a fast and efficient classification algorithm, can be used for feature selection, this paper proposes a new algorithm based on a fusion model. With the CEPRI-36 bus power system, the results of different algorithms are compared and the proposed algorithm verified.
© 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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