Processing and Interpreting Soiling Data

PV modules perform best when they are clean and free from contamination. This is because sunlight is unable to reach the PV cell as contamination collects on the surface of modules, thus reducing the amount of electricity that is able to be generated. This performance loss is perceivable in the loss of transmission and the soiling ratio.

Processing and Interpreting Soiling Data

Image Credit: Kipp & Zonen

The DustIQ from Kipp & Zonen is a one-of-a-kind optical tool for precisely quantifying the soiling ratio of PV modules, providing the information that is required to make PV installations function successfully.

In this article, OTT HydroMet sheds light on DustIQ’s measurement principles and the phenomenon of soiling. The processing and interpretation of the readings are also outlined.

What is PV Soiling?

PV soiling is classed as the build-up of solid material on the surface of a PV module.

The PV module not only absorbs but also scatters incident light when particulate matter and dirt accumulate on it. This has a great impact on energy production. In addition to high temperatures, soiling is one of the main reasons for PV output degradation and is considered responsible for 3–4% of PV production losses across the world.

PV soiling can be caused by a variety of sources, such as bird droppings, mineral dust, organic growth (such as fungi, lichen, and mosses), engine exhaust, pollen, and agricultural emissions.

The pace at which these materials accumulate depends on a variety of factors, including the dust and PV module surfaces’ properties, as well as climate-based parameters such as rain, wind, irradiance, temperature, and humidity. A considerable impact can also be caused by PV module orientation.

Understanding and interpreting regional soiling losses are highly dependent on the careful consideration of all the aforementioned factors.

Processing and Interpreting Soiling Data

Image Credit: Kipp & Zonen

The impact of soiling is usually explained in two quantities:

  • Soiling Ratio (SR): The ratio of the soiled PV array’s actual power output to the power output that would be expected if the array were clean.
  • Soiling Level (SL) or Transmission Loss (TL): Fractional power loss owing to soiling given by 1-SR.

For instance, if a PV array was soiled to the extent that it generated 5% less power when compared to its clean state, the ratio of soiling would be 95%, whereas the transmission loss would be 5%.

For quantifying the soiling ratio of a PV array, two common approaches are used.

One approach is to set up two reference PV devices and allow one to soil naturally (at the same rate as the rest of the array) while keeping one clean. Although this method is popular, it has many limitations.

It creates an instant soiling ratio value with measurement uncertainties owing to misalignment between the two reference devices and to the angle-dependence of scattering by soiling. For this approach, one of the reference devices needs to be cleaned regularly.

The other approach is to employ an optical measurement device — like DustIQ. Optical systems function by generating an IR light pulse from within the module — i.e., from underneath the soiled surface — and quantifying the part that scatters and reflects back. With a calibration constant, this measurement could then be transformed into a soiling ratio measurement that is fully independent of the incidence angle.

Ensuring Reliable Data Collection

There are several factors that can impact the reliability of soiling measurements.

Location and Number of Sensors

IEC61724 lays out suggestions for the number of soiling sensors that need to be employed for a given AC system size in megawatts. This is, however, something of a rule of thumb.

It is possible to have significant variations in soiling profiles between sensors when following these recommendations, especially where there are variations in ground textures or wind speed and direction.

The best practice is to observe the site and verify whether it can be categorized into different “dust regions” — each of these regions needs to be observed, preferably by a centrally located sensor.

Installation, Commissioning, and Maintenance

DustIQ could be positioned anywhere on an array — at the side, top, or bottom of a PV module — but the ideal positioning is vertical: soiling typically differs most in the vertical direction; hence horizontal installation can be less effective at getting the full picture.

Investigating electrical protection is also recommended. DustIQ has been designed to ensure that it remains electrically protected in the field – however, it is always a good idea to provide external protection as well.

To assure a reliable commissioning process, it is also recommended to check and verify the Modbus input register values.

To make the best use of soiling data, the following factors should be considered:

  • Sampling frequency: Soiling is a rather slow phenomenon, so even sampling just once a day could provide insightful results. However, it is recommended that users carry out sampling every 15 minutes.
  • Environmental parameters: Soiling conditions are dictated by local environments; therefore, having information on environmental factors — such as weather — could offer a much better insight into soiling.
  • Local calibration: DustIQ is calibrated in the laboratory with a standard dust sample. The characteristics of particulate matter and dust can greatly vary — therefore, DustIQ needs to be calibrated locally at least once.
  • Taring: The compensating process for the zero offset of data is known as “Taring.” This needs to be done repeatedly to avoid drift over time. Taring is recommended every time the modules are cleaned.

Processing Data to Maximize Findings

Proper data handling is vital to optimizing the utility of DustIQ data. The below steps should thus be followed for easy-to-interpret data:

  • Reject outliers: Remove any data points that are unrealistic
  • Linearly interpolate missing data
  • Select solar noon values. Working with solar noon values minimizes the effects of “daily transients” due to frost and dew and also minimizes the effects of angle-of-incidence variation throughout the day. It is thus recommended to select data that was gathered between 12-2 pm
  • Average over solar noon data
  • Apply zero-offset compensation/taring: If a user's DustIQ is not routinely tared, it is essential to compensate for zero offset during data processing. Though it is best to tare data when carrying out cleaning, it is possible to address this even if the PV modules are not being cleaned by considering “environmental cleaning conditions.” Incorporating weather data allows users to tare soiling measurement data according to specific environmental factors.
  • Smooth data with a moving-average filter

Processing and Interpreting Soiling Data

Image Credit: Kipp & Zonen

Following the above simple steps will help users to convert any unclear noisy measurements into usable and simple-to-interpret soiling data, revealing trends and enabling efficient maintenance.

In 2022, a new DustIQ firmware update was also released that simplifies local calibration and taring and improves the sensitivity of measurements.

This information has been sourced, reviewed and adapted from materials provided by Kipp & Zonen.

For more information on this source, please visit Kipp & Zonen.


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