Nowadays, due to the extensive integration of distributed new energy into low-voltage distribution networks, traditional passive distribution networks are gradually transitioning to more active distribution networks. Although it is economical and convenient, problems such as bidirectional flow of power flow, unstable output, and isolated operation in new energy power generation systems can lead to misjudgment in traditional fault identification and diagnosis, Therefore, it is necessary to study the identification methods for various faults (such as line break faults, neutral line faults, fault arc detection, etc.) in low-voltage active distribution networks containing distributed new energy, and propose new solutions to make the low-voltage distribution network system containing new energy more stable and reliable.

Multiple new methods can be used to analyze and improve the above issues, such as artificial intelligence, neural networks, multi information fusion, weight correction, etc., to achieve the improvement of traditional fault detection and recognition methods. It is important to fully consider the impact of new energy access and propose fault criteria with strong correlation based on the characteristics of new energy.

Through this special issue, we hope to find ways to solve various problems and difficulties in identifying faults in low-voltage distribution networks caused by new energy access. We aim to improve and innovate traditional fault identification methods and achieve safer and more stable operation of active distribution networks. We welcome researchers from various disciplines to provide interdisciplinary perspectives on new energy, active distribution network, fault identification. Your contributions will play a crucial role in advancing knowledge in this field.