This paper proposes an online fault localization method for low voltage DC microgrids. This method is based on Artificial Neural Network (ANN) and only requires real-time measurements of a local power converter to locate a fault. During a DC fault, the current component fed by AC grid can contribute to time-variant non-linearity, which is undesirable to the development of data-driven method. A novel real-time scheme is thus proposed to exclude such component from DC fault current. The principle of the scheme is introduced and illustrated with time-domain analysis. The effectiveness is verified by case studies of locating a DC fault in a radial DC network fed by a 3-phase voltage source converter.
|Title of host publication||2020 IEEE 29th International Symposium on Industrial Electronics (ISIE)|
|Number of pages||6|
|Publication status||Published - 30 Jul 2020|
- Low-voltage DC Microgrid
- Fault localization
Javed, W., & Chen, D. (2020). Data-driven fault localization of a DC microgrid with refined data input. In 2020 IEEE 29th International Symposium on Industrial Electronics (ISIE) (pp. 1129-1134). IEEE. https://doi.org/10.1109/ISIE45063.2020.9152378