The effect of dust, dirt, pollen, and other contaminant accumulation on PV modules, commonly referred to as soiling, is an important environmental factor that causes reduced PV power plant energy generation. Average annual energy losses due to soiling are typically in the range 1-6% but strongly depend on conditions at the site, with higher annual, short term, or monthly losses found in some cases. Therefore, accurate monitoring of soiling losses has become increasingly important, especially for utility-scale PV power plants, which might be subject to performance guarantees that mandate a limit on loss generation due to soiling.The SMS systems use a simple and reliable method for measuring soiling losses. It uses the side-by-side comparison of the measured output of two co-planar, normalized PV reference modules, the first of which is kept clean as a control and the second of which naturally accumulates soiling at the same rate as the power-producing modules of the plant. The control module is kept clean through manual washing. The comparison is made on the basis of the measured currents, which serve as a proxy for the effective irradiance received by the soiled versus the clean module, and also on the basis of the measured maximum powers, which represent actual power production of soiled versus clean modules. In both cases, the measurements are temperature-corrected and normalized. The soiling ratio SR is the instantaneously measured ratio of dirty-to-clean (test- to-control) module outputs at any given point in time.SR measurements can be performed with uncertainties on the order of 4% or better on an absolute basis, depending on calibration conditions, operating temperatures, angular alignments, and other factors.

• Does not require any kind of on-site programming.
• Operational in extreme environment with standard operating range of 0oC to +60oC
• Highly accurate and precise soil monitoring system specifically designed for Solar Power plants
• Simple and user-friendly to install
• Time synchronization with SCADA