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 …

In recent years, aerial infrared thermography (aIRT), as a cost-efficient inspection method,
has been demonstrated to be a reliable technique for failure detection in photovoltaic (PV) …

High quality energy systems information is a crucial input to energy systems research,
modeling, and decision-making. Unfortunately, actionable information about energy systems …

Offshore floating solar power stations represent a new frontier in energy development.
These stations maximize solar energy use, reduce land consumption and promote algae …

Photovoltaic (PV) solar panels account for a major portion of the smart grid capacity. On the
other hand, the accumulation of solar panels dust is a significant challenge for PV‐based …

Solar home systems (SHS), a cost-effective solution for rural communities far from the grid in
develo** countries, are small solar panels and associated equipment that provides power …

Photovoltaic (PV) panels are prone to experiencing various overlays and faults that can
affect their performance and efficiency. The detection of photovoltaic panel overlays and …

In this paper, k-means and fuzzy c-means (FCM) algorithms have been used as it is efficient
in grou** based on classified data points. Then ant colony optimization (ACO) and …

The utilization of Machine Learning (ML) classifiers offers a viable approach to improving
diagnostic accuracy and system dependability in the pursuit of optimizing problem detection …

Fault detection and diagnosis are essential elements for the condition monitoring of
photovoltaic (PV) panels. This thesis proposes a new four-step strategy (modelling, pre …