Abstract：In order to improve the efficiency of identification and diagnosis of distribution network line faults and improve the reliability of power supply, this paper adopts a method based on wavelet entropy to construct a distribution network line operating condition characteristic gene bank. Firstly, the distribution network line simulation model is built to extract the operation data, and then, combined with the effective simulation data, the feature extraction algorithm model based on wavelet entropy is built, and finally, the characteristic gene bank is developed based on the feature data. The simulation results show that the feature extraction algorithm and characteristic gene bank based on wavelet entropy can effectively identify and diagnose a variety of operating conditions of distribution network lines, which meets the requirements of sustainable development of distribution network.
王良锋, 李瑞, 尚筱雅, 李沁雪, 邱泽锦. 基于小波熵的配电网线路运行工况特征基因库构建[J]. 电气技术, 2025, 26(2): 35-41.
WANG Liangfeng, LI Rui, SHANG Xiaoya, LI Qinxue, QIU Zejin. Construction of a distribution network line operating condition characteristic gene bank based on wavelet entropy. Electrical Engineering, 2025, 26(2): 35-41.
2025, Vol. 26 
