ABSTRACT
Productivity plays a significant part in the activity of a solar power generating system. Installing a photovoltaic (PV) system is in no way, shape, or form the end of the story: customary support is fundamental to guarantee ideal yield from the individual PV panels. In spite of the fact that PV frameworks are for the most part low-upkeep and can work for quite a long time without issues, they are, after all, an electrical framework. This implies that there are legalized necessities for customary maintenance that must be seen by system administrators. Deep learning–based arrangement of a predictive maintenance system represents as a fundamental field to keep high specialized and monetary exhibitions of solar PV panels over the long run. Scientific observing frameworks have been introduced worldwide to conveniently distinguish potential breakdowns through the appraisal of PV framework exhibitions. For this reason, administrators and planners can commission a specialist organization to complete this upkeep as framework checks and, if vital, refitting or repowering measures. Recent methodologies, opportunities, challenges, and future directions of PV panel’s predictive maintenance using deep learning are discussed in this chapter.
