Abstract:

Aiming at the problem of wide range of fault section identification and low classification accuracy in UHVDC transmission line, a method of fault section identification and classification based on energy ratio optimization and fuzzy logic (FLS) is proposed. Firstly, the energy ratio of fault signal is optimized by using full current instead of low frequency component, and the energy ratio variation characteristic of fault region is used for fault feature extraction. Then, the fault features obtained are used as the input of the three FLS modules, which respectively realize the fault detection of AC and DC sections, the identification of fault sections and the identification and classification of fault poles. Finally, the Matlab platform is used to build a circuit model to verify the performance of the proposed method under the influence of fault distance, power angle, DC bias and other factors. The experimental results demonstrate that the proposed method has short time-consuming and high accuracy of fault detection.

Key words: UHVDC transmission, energy ratio optimization, fuzzy logic system(FLS), fault section detection, feature extraction