Ultimately, a detailed strategy for dust prevention in PV panels is proposed, involving real-time monitoring, assessment of dust deposition, mathematical modeling for predicting performance losses, and informed decision-making regarding optimal cleaning measures to enhance panel efficiency. 2. Methodology
The cleaning methods of photovoltaic modules include manual dust removal, mechanical dust removal, electrostatic dust removal, self-cleaning coating and so on. In general, the self-cleaning coating has better performance in dust removal. It requires no power or manpower, relying on its own characteristics.
Many researchers have reviewed the effects of dust on the performance of PV panels and cleaning methods, but their coverage is narrow and lacks more in-depth summarization, comparison, and critique of key quantitative results.
Proper periodic PV cleaning can be considered the best way to reduce negative environmental impacts, so as to ensure a high rate of productivity, and efficiency (Biris et al., 2004). One of the easiest ways to clean PV is manual cleaning, which depends on water to remove dust accumulated on the PV.
Narvios et al. proposed an IoT-based system for monitoring and automatically cleaning dust from PV panels. The system employs a GPY1010AU dust sensor to detect dust accumulation, triggering the cleaning system once the threshold is surpassed. It also incorporates a DHT22 temperature and humidity sensor to monitor ambient conditions.
The researchers identified the proposed cleaning system for areas with dust storms, high irradiation and ambient temperatures. It is found that the proposed system promising to increase the PV productivity as it reduces the PV temperature in addition to PV cleaning.