Fault Protection Method for Low-Current Grounding Systems in Active Distribution Networks Based on an Improved Clustering Algorithm
With the increasing global focus on carbon neutrality and the development of renewable energy, a large number of distributed generation units have been integrated into the distribution network to enhance sustainability and reduce carbon emissions. As a result, fault signals often exhibit high-frequency, nonlinear, and weak characteristics, rendering traditional low-current grounding fault line selection methods ineffective. In this paper, by analyzing the differences between the transient zero-sequence currents of low-current grounding faults in active distribution networks, a fault protection method for low-current grounding systems based on an improved clustering algorithm with optimized initial cluster center selection is proposed. The proposed method involves filtering the transient zero-sequence currents, characterizing their phase differences using the cosine distance between each pair of zero-sequence currents, and performing clustering analysis with an improved k-means algorithm. By defining a range for the number of clusters k and determining the optimal value based on the within-cluster sum of squares (WCSS), the fault line can be accurately identified. Simulation results demonstrate that the method is applicable to both conventional low-current systems and low-current systems in active distribution networks, offering good practicality and anti-interference performance.
Authors
- Guojing Zhang (ORCID: https://orcid.org/0000-0003-3843-3672)
- Songlin Tan (ORCID: https://orcid.org/0000-0001-5195-4953)
- Jian Zhu (ORCID: https://orcid.org/0000-0002-2551-2024)
- Chen Liu (ORCID: https://orcid.org/0000-0003-1558-6836)
- Xue Chen (ORCID: https://orcid.org/0009-0000-8642-256X)
Institutions
- Shanghai Electric (China) (CN)
Publication Details
- Journal
- IEEE Access
- Published
- 2025-01-01
- DOI
- https://doi.org/10.1109/access.2025.3605355
- Citations
- 1
- Primary Topic
- Power Systems Fault Detection
- Type
- article
- Field-Weighted Citation Impact
- 1.21
Funders
- State Grid Jiangsu Electric Power