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Solar photovoltaic (PV) technology can be considered a suitable option for fossil fuels because of its free availability and ease of use. The deprivation of power generation from PV systems due to environmental factors shows a major flaw in solar PV systems. As a result, they are unreliable in deserts or remote locations. The accumulation of dust in solar PV systems is a major problem. Solar PV energy prediction is a critical factor in future ecological and reliable energy sources for system stability. Real-time observing systems are essential in a remote PV system for collecting all the parameters needed to evaluate and optimize system performance. Many existing studies use costly and difficult-to-use wired data acquisition systems that run on LABVIEW licensed software. PV panels must be cleaned on a regular basis to achieve maximum efficiency. Most existing cleaning methods require water for cleaning the PV system. In this study, a wireless data acquisition system and a method of self-cleaning the PV panels are developed and tested. The proposed cleaning system not only cleans the PV system but also protects it from hailstorms. We investigate the performance of a 106 W PV system under Jaipur weather conditions over a one-year period using a proposed wireless data acquisition and monitoring system. The results revealed that the exposure of 12 months of 106 W PV panels under different seasons in Jaipur reduced the PV system’s efficiency by 24.5% in summer, by 15.6% in winter, by 5.14% in post-monsoon and by 1.95% in monsoon. The PV panels’ maximum efficiency is reached at a panel temperature of 41°C in the summer and 48°C in the winter. We observed that the proposed data acquisition system is applicable, durable, efficient, and appropriate for severe outdoor conditions for observing and collecting operational information about the PV system. The efficiency of a fixed PV system with daily manual cleaning was compared to that of a proposed cleaning PV system for a month and the proposed cleaning PV system’s efficiency was only 1.13% lower. The result shows that the proposed cleaning PV system performs well even in semi-arid environments.

Performance Analysis of Solar PV system using Customize wireless data acquisition system and novel cleaning technique