The power output delivered by a solar photovoltaic module is highly dependent on the amount of irradiation that reaches the solar cells. Soiling, the accumulation of dust on solar panels, leads to a decrease in the solar photovoltaic (PV) system’s efficiency by reducing the irradiation impact directly on the solar cells. The decrease in output due to soiling can be of one of the two categories: soft shading (due to factors such as pollution), and hard shading (due to accumulation of dust on the surface of the solar panel).
It is crucial to keep track of the level of soiling of the array at any given point in time, during the operation of a solar PV plant. An overly soiled array results in loss of money, in terms of power that could have been generated, had the array been cleaned. However, premature cleaning of the array can be seen as a wastage of money, in terms of the manpower and resources invested in the process of cleaning.
Economics of module washing
The economics of module washing are not exactly very difficult to understand. If having a cleaner array saves more money than it costs to clean it, then it is advisable to clean the array.
The assessment of the level of soiling and to determine when an array needs to be washed requires a multi-variable equation, representing all the various factors that affect the level of soiling, including:
- Technology choices
- Racking configuration
- Inverter loading
- PPA rates
- Interconnection agreements, etc.
To simplify this process, we will discuss the most important factors involved in determining the frequency of washing the PV array.
Before delving into the discussion about energy recapture, it is important to define two terms which will appear repeatedly in the discussion: percent soiling and percent energy loss due to soiling.
Percent soiling: Percent soiling can be defined as the reduction in expected output between the soiled DC circuits (modules, strings, etc.) compared to the output of the same circuits under cleaner conditions.
While this quantity is easier to quantify, it doesn’t directly correlate to unrealised revenue, and hence cannot be used when trying to determine the economics of cleaning the array.
Percent energy loss due to soiling: This can be defined as the difference between the metered energy for a given period of time, compared to the energy that could have been harvested over the same time period with a clean array.
This term describes the energy available for recapture, which directly correlates to unrealized revenue.
Power limiting in PV arrays
PV systems are usually deployed with high array-to-inverter power ratio (DC-to-AC ratio) in an attempt to capture more energy, which forces the inverters to spend a lot of time operating at full power, to maximise revenue. Extended periods of power limiting results in a characteristic flat-topped power curve, which is referred to as power clipping.
The loss of power due to soiling is only a concern when it is possible to recapture the energy lost, which requires unused inverter capacity. Hence, more the time spent by an inverter at full power, lesser are the returns availed by increasing the irradiance on the solar cells. An inverter which is already operating at full power cannot increase its output power following an increase in the irradiance.
Figure 2 illustrates this point by comparing the solar irradiance (Blue) in the months of August and November, and the plant production curves (Red) on the same days, for a PV system. To compare the percent energy loss due to soiling for Day 1 vs Day 2, we have to filter out the time spent at full power (i.e., the hours during which no energy can be recaptured)
From the table below, it can be understood that the percent soiling is roughly the same on both Day 1 and Day 2. While the incident energy is greater on Day 1 than on Day 2, the percent energy loss and the net energy lost due to soiling are greater on Day 2. This means that the opportunity to recapture energy (and thus, revenue) is better on Day 2, in spite of the incident energy being lower. The challenge associated with soiling assessment is that we need to extrapolate this analysis to the near operational future for the PV plant. The estimate concerning the future mix of clear, cloudy or overcast days is what has an impact on the economics of module washing. A large number of models do exist to help predict the energy available for recapture. However, regardless of the methodology used, it is essential to account for inverter power limiting and have an accurate estimate of percent soiling.
Direct soiling measurements
The best way to estimate the percent soiling is to measure it directly – test the array, wash it, and test it again. The process is definitely time-consuming, but there is no way to dispute the results. Devices such as short circuit testers, soiling sensors, and IV-curve tracers also help in getting an estimate of soiling levels. It is important to remember that additional data analysis and filtering is necessary to extrapolate the percent energy loss due to soiling from percent soiling.
Soiling transfer function
The soiling transfer function is used to extrapolate data obtained from the devices to generalise the plant’s soiling conditions and to infer how much the measured soiling will affect energy production and performance. Percent soiling (which can be calculated directly) rarely reflects an equal – or proportional – percent decrease in production.
The operating data needs to be carefully filtered to complete the soiling transfer function. This could be as simple as removing power clipping points, which constrain the evaluation to periods of MPPT operation or involve applying complex filters to remove spurious data points which might possibly muddy the results, including low POA irradiance, excessive wind speeds, or unstable irradiance. Once the field measurements are obtained and cleaned, they need to be compared with the default value, to estimate the percent energy loss due to soiling.
The operational data of plant performance under clean conditions is called the plant baseline. This is a process of characterising the electrical performance of source circuits, combiners, inverters, etc. and isolating this data for comparison. This baseline helps understand how the system – or subsystem- work under known operating conditions when the array is free of faults.
The best opportunity to obtain a baseline for the entire plant is at the time of initial backfeed, testing and commissioning. However, it is not mandatory to establish the baseline at the time of commissioning. Parts of the system can always be revisited and recalibrated to ensure they fit the general performance trend.
The simplest form of estimating the percent loss in energy due to soiling is by comparing the performance of the PV array under soiled conditions, to the baseline performance. This method is effective for both long- and short-term analyses. The results can be compared on an inverter-level, or at the AC collector level, and the results can be used to make an informed decision about soil abatement.
Accuracy is critical in the baseline characterization method. Production losses are often very minor, typically only a few percentage points, before becoming noticeable. Thus, accuracy becomes vitally important to tying production losses to soiling.
For example, the simple characterization method catalogues the plant production at the meter and the measured irradiance at the plane of the array. This method, however, ignores the thermal differences within the array. For increased accuracy, temperature compensation needs to be applied to account for deviations from the weather station conditions.
A 5-step approach to isolating the effects of soiling on energy production based on measured data from operating PV plants is as follows:
- Catalog the IV-curve traces and other string-level commissioning tests to establish source-circuit behaviour with respect to nameplate power. This step provides the constant reference dataset which can be referred to when using periodic string testing for performance assessments.
- When commissioning the array and conducting energy performance tests, establish plant-level and inverter-level baselines using high-resolution data. These baselines should isolate trend data for clipping and non-clipping production as a function of POA irradiance and should be normalised to DC capacity by the inverter.
- Track plant performance using trend data from the time of commissioning through operations. Using the same filters employed to establish the baseline, determine approximate soiling levels while the plant operates
- If excessive soiling is suspected, perform a series of string-level field measurements before and after washing, and compare these results to the commissioning data. Next, compare these measured results to the soiling estimates generated from the trend data with the appropriate clipping filters applied. Establish the correlation between the measured and modelled results.
- When field measurements and data analysis align – and when the comparison to the baseline indicates that energy recapture will be cost effective – then it is time to schedule a wash. Over time, take advantage of these full-array washing opportunities to recalibrate the baseline, the energy model, and so forth.