MULTI-CRITERION IDENTIFICATION OF LOW-FREQUENCY MAIN TRANSFORMER INRUSH CURRENT OF OFFSHORE WIND POWER BASED ON FUZZY PROXIMITY DEGREE

Gao Shuping; Wu Xinyu; Xi Ali; Quan Zhe; Wang Chenqing

doi:10.19912/j.0254-0096.tynxb.2024-1435

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Acta Energiae Solaris Sinica ›› 2025, Vol. 46 ›› Issue (12) : 599-608. DOI: 10.19912/j.0254-0096.tynxb.2024-1435

MULTI-CRITERION IDENTIFICATION OF LOW-FREQUENCY MAIN TRANSFORMER INRUSH CURRENT OF OFFSHORE WIND POWER BASED ON FUZZY PROXIMITY DEGREE

Gao Shuping^1,2, Wu Xinyu^1,2, Xi Ali^1,2, Quan Zhe^1,2, Wang Chenqing^1,3

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Abstract

Since both ends of the AC transmission and output lines of the low-frequency transmission system of offshore wind power are power electronic equipment, current distortion in the process of grid failure may cause the adaptability decline of the existing protection . To solve these problems, this paper proposes a new method of multi-criterion comprehensive identification of transformer excitation inrush current based on fuzzy progress. The method synthesizes several characteristics of transformer inrush current, including the second harmonic, waveform symmetry, waveform sine and the ratio of reactive fundamental wave to active DC. By using different membership functions and combining the characteristics of each criterion, different weights are calculated. By synthesizing multiple criteria, the similarity degree between the comprehensive fuzzy set and the preset inrush current or internal fault standard fuzzy set is calculated using the progress function. At last, PSCAD is used to build the low-frequency transmission system model, and the operation state of the low-frequency transformer under different working conditions is simulated. The current data generated under different working conditions are processed and analyzed by Matlab, and the proposed identification method is verified. The results show that this method can synthesize the advantages of each criterion and realize the accurate and reliable identification of inrush current and internal fault in low-frequency offshore wind power system.

Key words

offshore wind power / fuzzy inference / feature extraction / low-frequency transformer / inrush current / closeness function

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Gao Shuping, Wu Xinyu, Xi Ali, Quan Zhe, Wang Chenqing. MULTI-CRITERION IDENTIFICATION OF LOW-FREQUENCY MAIN TRANSFORMER INRUSH CURRENT OF OFFSHORE WIND POWER BASED ON FUZZY PROXIMITY DEGREE[J]. Acta Energiae Solaris Sinica. 2025, 46(12): 599-608 https://doi.org/10.19912/j.0254-0096.tynxb.2024-1435

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