Research on a Fast Fault Location Method for Distribution Networks Based on Improved Transient Feature Extraction

To address the reduced reliability of fault location caused by complex branches, transient noise, fault resistance and variable operating conditions in distribution networks, a fast fault location method based on improved transient feature extraction is proposed. The method combines parameter-adaptive variational mode decomposition with wavelet packet energy entropy to extract multi-scale transient current features, and uses a lightweight extreme learning machine for faulty-section identification and distance estimation. The proposed framework balances feature interpretability and online computational efficiency, providing an engineering-oriented implementation scheme for coordinated fault location between distribution automation terminals and master stations.