Paper Key : IRJ************577
Author: Pritam Shraddhe,Aniket Khedkar,Pratik Banbare,Prof.s.n.chaughule
Date Published: 12 Nov 2024
Abstract
Solar energy surpasses all other sources of energy generation and is the cleanest, most sustainable source of energy. Generally speaking, solar panels don't require constant maintenance and require little care. But because a malfunctioning panel might impact the generation of the entire array, a number of problems could result in a production loss of up to 20 percent. If the power plant is properly maintained on schedule, it will live longer and produce more electricity overall, which will reduce the cost of repairs. Remote solar plantations are more difficult for humans to access, and large solar farms necessitate costly and time-consuming manual panel monitoring. In this article, thermal images from an unmanned aerial vehicle (UAV) fitted with infrared sensors are used to demonstrate deep learning-based techniques for identifying issues in solar systems. With the help of previously observed voltage and current values, the software that will be created as a result of this research and work will be able to precisely identify internal solar panel faults and forecast how much solar energy will be generated as a result of these defects. In the future, this software might also be able to recognize flaws in solar panel photos.Keyword:- Maximum Power Output, Artificial Neural Network, Deep Learning, Solar Panel Fault Detection, Preprocessing, and Photovoltaic-Cells.
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