Photovoltaic (PV) fault detection and classification are essential in maintaining the reliability
of the PV system (PVS). Various faults may occur in either DC or AC side of the PVS. The …

The rapid development of photovoltaic (PV) technology and the growing number and size of
PV power plants require increasingly efficient and intelligent health monitoring strategies to …

With the popularization of the intelligent manufacturing, much attention has been paid in
such intelligent computing methods as deep learning ones for machinery fault diagnosis …

This paper provides a comprehensive literature review on Predictive Maintenance (PdM)
with emphasis on system architectures, purposes and approaches. In industry, any outages …

Artificial intelligence techniques lead to data-driven energy services in distribution power
systems by extracting value from the data generated by the deployed metering and sensing …

Currently, a huge number of photovoltaic plants have been installed worldwide and these
plants should be carefully protected and supervised continually in order to be safe and …

This paper presents a state-of-the-art review on machine learning (ML) based intelligent
diagnostics that have been applied for partial discharge (PD) detection, localization, and …

This systematic review aims to investigate recent developments in the area of arc fault
detection. The rising demand for electricity and concomitant expansion of energy systems …

A microgrid can be formed by the integration of different components such as loads,
renewable/conventional units, and energy storage systems in a local area. Microgrids with …

Data-driven fault diagnosis has been a hot topic in recent years with the development of
machine learning techniques. However, the prerequisite that the training data and the test …