Measuring cleanness of solar photovoltaic systems with Soltell's SWMT technology
Updated: May 10, 2021
The impact of soiling, including dust and dirt is accumulating over several weeks to over 20% impact on performance in the Mediterranean region, susceptible to dust from Middle Eastern and North African deserts. A similar effect is also observed in the South-Eastern and Southern US states. Furthermore, in urban environments an even more dramatic impact is made by fast accumulation of dust and soot. Manual or automatic cleaning is hence required to bring solar photovoltaic (PV) performance to optimal values. The means and the frequency of cleaning is of course a function of several variables, including system size, electricity generation tariff and local factors.
However, the timing of cleaning and its effectiveness for rooftop facilities has so far been a matter of an educated guess. The cleanness measurement capability of Soltell's SSMP management platform is a unique predictive maintenance tool for rooftop PV in terms of cleaning schedule, as well as optimizing other aspects of maintenance. It is powered with the SWMT technology, allowing a sensorless ability to measure dust on individual solar PV plants, with no need for sensor installation, calibration and maintenance.
Presenting our proprietary cleanness measurement of rooftop solar PV systems - ability to detect the precise soiling impact on PV system performance with no extra hardware, utilizing our Industrial IoT capability coupled with artificial intelligence. Above, you can see the comparison of automatically cleaned PV system (daily), periodically cleaned PV systems (once 2-3 weeks) and rarely cleaned PV system (once a season).
Commercial solar PV fleet managers, solar integrators and solar service companies - interested to learn more on the Smart Solar Management Platform to optimize your solar O&M management costs or offering your customers a solar monitoring portal with your brand? Fill the contact form to get more details or register your PV systems.