Editorial: New advancements in power system condition monitoring, fault diagnosis and environmental compatibility
Abstract
Rising electricity demand and higher consumption levels are pushing power systems toward stricter safety and stability requirements. To maintain dependable, secure, and efficient transmission and distribution, it is essential to continuously monitor system conditions and swiftly identify faults. This relies on aggregating and interpreting data from numerous sensors and measurement units placed across grid assets. Real-time health assessment of equipment enables early warning of potential failures, preventing them from developing into major incidents while also boosting overall grid performance. Over the past few decades, breakthroughs in data analytics, machine learning, and artificial intelligence have dramatically strengthened monitoring and diagnostic functions. Combining data from diverse sources improves anomaly detection accuracy, thereby reducing service disruptions, strengthening network reliability, and cutting maintenance costs. Furthermore, the broad adoption of these advanced technologies has also helped mitigate the environmental impact of power systems. This Special Issue, serves as a continuation of the previous special issue with 16 published articles, entitled "New Advancement in Power System Condition Monitor, Fault Diagnosis and Environmental Compatibility", collected 8 articles.The first research area of this Special issue is about Power System Condition Monitor and Optimization, which collected 5 papers. Liu et al. reported YOLOv8-FOD, a lightweight…
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