Soiling Assessment in Large-Scale PV Arrays: Page 2 of 5
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Table 1 presents these filtered results. Compared to baseline values for a clean array, the percent soiling is roughly the same on Day 1 and Day 2 (3.7% versus 3.6%). However, we can recapture energy only during hours when the PV plant is not power limiting. This leads to a slightly counterintuitive result: Even though the incident energy on Day 1 is nearly twice that on Day 2 (10.4 kWh/m2 versus 5.3 kWh/m2), the percent energy lost and the net energy lost due to soiling are greater on Day 2. This means that Day 2 presents the better opportunity for revenue recapture via washing, even though the available solar resource value is lower.
The challenge associated with soiling assessment is that we need to extrapolate this analysis to the near operational future for a PV power plant. The estimate concerning the future mix of clear, cloudy or overcast days is what determines the economics of module washing. A host of models and methods are available to predict and back-calculate the energy available for recapture, including hourly energy models, exceedance probability calculations and regression analyses. Regardless of the methodology used, you must account for inverter power limiting and have an accurate estimate of percent soiling.
Direct Soiling Measurements
The best way to estimate percent soiling is to measure it directly: Test the array, wash it, and test it again. While the process is time-consuming, there is no disputing the results. Soiling sensors and IV-curve tracers are proven tools for getting an accurate answer to the question “How dirty are my modules?” It is also possible to use other devices, such as short-circuit testers, to get a general estimate of soiling levels. Just keep in mind that additional data analysis and filtering is required to extrapolate from percent soiling to percent energy loss due to soiling.
Soiling sensors. Soiling sensors are essentially stand-alone evaluation tools that compare the actual output of a naturally soiled PV reference module to the expected output of a clean PV reference device. Some soiling sensors use short-circuit current (Isc) as the basis of comparison; others incorporate a microinverter and compare maximum power point values (Vmp, Imp, Pmp); some devices use a hybrid technique that compensates for temperature and normalizes results to STC. All of these approaches yield a high-quality data stream that you can easily use to assess the soiling level of the modules in the test rig.
IV-curve tracers. To get the best possible in situ soiling measurements, put a good IV-curve tracer in the hands of a competent technician. Curve tracing is slow but definitive. You can compare PV source-circuit curve traces to STC or use a dirty versus clean approach. As long as technicians capture a representative set of IV-curve traces under roughly the same conditions, the results of the study will be accurate and useful. While it is quick and easy to analyze these IV-curve data, it is incumbent on the technicians to choose representative strings to test in the field.
Other devices. Another option that works well is to use instruments that measure short-circuit current or operating current, or that can extrapolate measured data to a baseline condition—such as PVUSA Test Conditions (PTC) or STC—to estimate percent soiling. Since these devices are not explicitly intended to perform soiling measurements, the correlation process is left to you. However, the process does not need to be complex. A simple multimeter with a current loop sensor is sufficient to get a general idea of soiling conditions. If necessary, you can assess soiling with a Fluke meter, a few gallons of water and a squeegee.
SOILING TRANSFER FUNCTION
Soiling stations, IV-curve traces and other assessments that compare “before” (dirty) and “after” (clean) conditions give an excellent indication of the soiling conditions on a specific set of modules or test array. The trick is to take data from these devices and extrapolate it twice: once to generalize the entire plant’s soiling condition, and once more to infer how much the measured soiling will affect energy production or performance. We call this the soiling transfer function. Direct soiling measurement is a great start, but it is a rare instance where the estimated percent soiling value will reflect an equal (or even proportional) percent decrease in production. As illustrated in Table 1, percent soiling does not correlate directly to energy lost due to soiling when PV plants spend a lot of time operating at maximum power.
To complete the soiling transfer function from percent soiling to percent energy loss due to soiling, you need to filter the operational data strategically. The data filtering process can be as simple as removing power clipping points, which has the effect of constraining the evaluation to periods of MPPT operation. You can also apply additional filters to remove spurious data points that may muddy the results, such as measurements associated with low POA irradiance, unstable irradiance or excessive wind speeds. Once you have obtained field measurements and filtered the operational data, you just need something with which to compare these to estimate percent energy loss due to soiling.