| Autor: |
Miao Yu, Jingjing Wei, Shuoshuo Tian, Jianqun Sun, Yixiao Wu, Shouzhi Zhang, Jingxuan Hu |
| Jazyk: |
angličtina |
| Rok vydání: |
2024 |
| Předmět: |
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| Zdroj: |
Journal of Electrical and Computer Engineering, Vol 2024 (2024) |
| Druh dokumentu: |
article |
| ISSN: |
2090-0155 |
| DOI: |
10.1155/2024/2088540 |
| Popis: |
The complexity of the interconnected grid and the continuous increase of new energy sources have led to an acute problem with low-frequency oscillation (LFO) in power system. Identification and monitoring of LFO in power grid are prerequisites for effective control of low-frequency oscillation phenomena. To address matter that the traditional S-transform time-frequency window function has a fixed scale and cannot be applied to the specific local characteristics of different signals, an adaptive generalized S-transform algorithm based on a bat algorithm is proposed in this paper. It uses adjustment parameters to control the generalized Gaussian window function. The parameters are automatically adjusted by a bat algorithm adaptive optimization to find the best time-frequency characterization. Secondly, the PMU data waveform with implicit low-frequency oscillation information is converted into a two-dimensional time-frequency figure including the onset moment, frequency, and amplitude. The system enables identification and visual monitoring of low-frequency oscillations. After that, simulation experiments of New England system are conducted. The superiority of the proposed method is verified, which can greatly improve the time-frequency resolution of PMU active power data signal and has effective noise immunity. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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