Open Journal of Energy Efficiency, 2017, 6, 80-86
ISSN Online: 2169-2645
ISSN Print: 2169-2637
10.4236/ojee.2017.63006 Aug. 11, 2017 80 Open Journal of Energy Efficiency
Solar Panels Cleaning Frequency for Maximum
Electrical Engineering Department, Philadelphia University, Amman, Jordan
Allowing the dust to accumulate on solar panels without adequate cleaning
leads to huge monetary losses. Proper judgment of
when to call for washing of
solar panels is a compromise between gross costs of cleaning the panels and
how much reduction in efficiency of solar panels can be tolerated. In this p
we derive a formula for the optimal number of days between cleaning
cycles of a solar array by minimizing the cost of cleaning the array and the lost
revenue from the unclean panels. The formula will aid in deciding cleaning
periods based on the environme
nt in which the solar panels are installed and
cost incurred from undertaking the washing process.
Dust Deposition, PV Efficiency Degradation, Optimal Cleaning Cycle
There is an established body of literature on the effect of dust on solar panel
performance and efficiency. However, the literature on the frequency of cleaning
solar panels from accumulated dust is limited.
One of the first rigorous experimental studies on the effect of dust on the I-V
characteristic curve was conducted by El-Shobokshy . They studied the effect
of dust deposition on the reduction of solar intensity and the power output of
the solar panel. Although the experimental procedure was very robust to under-
stand the ramifications of dust accumulation on solar panel efficiency, the re-
sults drawn were for a specific solar panel type which was used in the labora-
To understand the process of dust particles accumulation on glaze surfaces at
the microscopic level, Al-Hasan  made a theoretical analysis on the trans-
How to cite this paper:
Solar Panels Cleaning Frequency for
Maximum Financial Profit
of Energy Efficiency
March 23, 2017
August 8, 2017
August 11, 2017
Copyright © 201
7 by author and
Research Publishing Inc.
This work is licensed under the Creative
Commons Attribution International
License (CC BY
10.4236/ojee.2017.63006 81 Open Journal of Energy Efficiency
mittance of light through a layer of sand particles accumulated on the surface of
a photovoltaic panel. A mathematical relation was derived which relates trans-
mittance coefficient to the number of sand particles deposited on the surface.
In  an experimental study was performed on the relation between dust
accumulation and the tilt angle of the panel where horizontal panels caught the
most deposition of fine and coarse particles whereas vertical panels caught the
fine particles of dust only. Tilt angle effect on dust deposition has been further
studied in  and a regression-based model of the relationship between output
power and sand particle size and irradiance was derived.
In  performance degradation due to deposition of different types of sand
particles is investigated and a theoretical model is developed that is able to si-
mulate the dust deposition impact on the energy behavior of solar photovoltaic
To our knowledge  is the only reference that suggests cleaning cycles for
different regions. However, the paper only provides guidelines for cleaning the
panels when installed in different climatic zones and based on the weather and
dust activity level. Our approach is different in that it is based on a quantitative
analysis of dust and hence yields optimal results compared to the cleaning cycles
suggested in  which are based on qualitative understanding of dust activities.
2. Derivation of the Optimal Number of Days between
The effect of sand dust particles accumulation on light transmittance coefficient
is investigated mathematically and experimentally in . A transmittance coef-
ficient of 0 means the light beam did not pass and that it has been completely
reflected or absorbed while a coefficient of 1 means light has passed completely
without attenuation. The relation between transmittance coefficient (
number of particles accumulated (
) has been derived as 
is the radius of the sand particle and
is the particle extinction
efficiency which has been assumed to be equal to 2 since the sand dust particles
settle on the surface of the glass of the photovoltaic panel far away, in com-
parison to the size of dust particles, from where the light is detected by the
photovoltaic cells. This relation is linear with transmittance decreasing with
more sand dust particles settling on the surface. In  a comparison between
this mathematical derivation and experimental observation shows good agree-
ment for light transmittance values in the range 0.5 to 1. For transmittance
coefficients below 0.5 the relation observed starts to deviate from the linear
relationship and becoming more nonlinear. However, in practice to maintain the
efficiency of the photovoltaic panels, the cleaning of panels should be performed
before transmittance coefficient falls to such low values. So in our derivation of
the optimal solar panel cleaning cycle, the relation between efficiency and the
amount of dust accumulation will be assumed to be linear without much loss of
10.4236/ojee.2017.63006 82 Open Journal of Energy Efficiency
Dust accumulation on the surface of the solar panels will cause the efficiency
of the solar panel to decrement from its nominal value. So
is the average daily losses in solar conversion efficiency due to dust
is number of days between cleaning cycles. So the financial loss due to
power degradation as a result of dust accumulation on the PV system for
consecutive days is
123 N si
is the average sun hours per day,
is the capacity of installed PV
is the price of kWh.
So the financial loss due to power degradation as a result of dust accumulation
per annum is
365 123C N si
= +++ +
is the cost of cleaning solar array, then the cost of cleaning the panels
per annum is
So the total cost is
2N si P
Finding the optimal number of days between cleaning cycles is achieved by
with respect to
ˆarg min .
d 365 365 0,
J si P
10.4236/ojee.2017.63006 83 Open Journal of Energy Efficiency
3. Determination of Parameter Values
3.1. Average Daily Loss in Solar Conversion Efficiency
The factors that affect rate of dust deposition on PV panels are the concentration
of airborne dust particles, wind speed, and relative humidity. It was reported in
 that the higher the concentration of dust particles in the air, the higher the
rate of dust deposition on the PV panels. Also relative humidity is positively
correlated with rate of dust deposition since the dust particles become stickier in
humid weather. On the contrary, wind speed was negatively correlated with dust
deposition since higher wind speed aid in the removing of dust particles from
the surface of the solar panels. These three factors differ from region to region
and hence will affect the average daily loss in solar conversion efficiency in the
region. For example, in California the average daily loss in solar conversion
efficiency was 0.051% . In Santiago, Chile the values ranged from 0.14% to
0.56% depending on the season and pollution level . In the middle east, the
values are high as well due to dusty weather conditions. For example, in Qatar
the average daily loss in solar conversion efficiency could be as high as 0.55%
3.2. Cleaning Cost
The process of cleaning the solar array should be performed by professional
cleaner. The cost of cleaning include the cost of materials used in the cleaning
process plus labor cost . The cost will vary from case to case depending on
the soiling type and country where the PV system is installed . In the middle
east region, for example, the soiling of panels is mainly due to dust accumulation
and hence cleaning can be performed relatively easy with basic tools, water, and
some cleaning chemicals. In cases where other types of dirts exit such as bird
dropping or extra pollution, the cleaning process may involve more cost and
Depending on the cost of cleaning and the level of dust accumulation, the
cleaning operation may be justified or it may not be justified. In a study by
, it was found that cleaning cost of PV panels installed in Perth,
Western Australia will be much higher than loss caused by dust and hence
cleaning is not justified. So the system operator can rely on natural cleaning such
as rain and wind to clean the panels. In another study by Stridh  in three
locations in Europe: Murcia in spain, Munich in Germany, and Stockholm in
Sweden, it was concluded that cleaning is justified in Murcia, and to some degree
in Munich, but not justified for Stockholm.
4. Results and Discussion
The following is a hypothetical example that shows how the result of the paper
10.4236/ojee.2017.63006 84 Open Journal of Energy Efficiency
appearing in Equation (14) can be used. The parameter values used are typical
for the middle east in general. Note that the cleaning cost of the 1 MW array
which is $250 is relatively small compared to other countries. This is due to the
fact that the type of soiling predominant in the middle east is sand which does
not require much material or labor in order to be cleaned.
MW solar PV system is subjected to dust accumulation that
causes an average daily loss in solar conversion efficiency of
If the PV
system receives an average of
sun hours per day, the price of
and the cost of cleaning a solar array is
How often should the solar array
be cleaned to maximize the gain
ˆ500 22 days.
0.002 5 1000 0.1
= = ≈
• Our derivation is based on the assumption that dust accumulation is linearly
increasing with time. However, the climatological system is more complex
and the linear assumption can work most of the time as an approximation
only. Two special climatological events should be observed: rainfall and sand
storms. Rainfall event will aid in cleaning the solar panels while sand storms
will accumulate huge amounts of dust on the panels and cleaning should be
usually performed after such event. Also it should be noted that in dry
regions dust removal can occur naturally when wind blows on dusty solar
panels which will further aid in the cleaning of the panels. Based on these
different scenarios, our result is expected to be conservative in maintaining
the solar panels clean.
• To compare the result of this paper to the approach followed in the literature
by the scientific community thus far , we find that it will take almost 22
days till the cost due to lack of energy production becomes 250 dollars. And it
is at this instant when the cleaning of the panels should be performed.
However, this coincidence will not necessarily hold true if dust accumulation
is not a linear function of time.
• The optimal number of days between cleaning cycles depends on a number
: the cost of cleaning solar array in units of $,
: the average daily losses in solar conversion efficiency due to dust in
units of day−1,
: average sun hours per day in units of hours/day,
: capacity of installed PV system in units of kW,
: price of 1 kWh of electricity in units of $/kWh.
Note that the multiplication of the last four factors (
) which appears in
the denominator of (14) represents the decremental daily loss in revenue due to
dust accumulation on the PV panels in units of $/day/day.
• This paper is considered as first attempt toward making decisions about
cleaning solar panels based on quantitative analysis. Generally these decisions
10.4236/ojee.2017.63006 85 Open Journal of Energy Efficiency
are made based on understanding the environment in which the solar panels
are installed which might not be the best decision made. We believe further
studies on the effect of dust on solar panel efficiency should be performed on
a region by region bases similar to the studies performed in  and  for
From economic perspective, solar panels should be regularly cleaned to improve
the efficiency and maximize gain. However, cleaning process incurs a cost and
could not be performed very frequently. Here we show a mathematical result
that maximizes the gain from the solar array. The main result of the paper
appearing in (14) was based on minimizing the cost function (9). Adopting this
cost function is the correct approach to find the optimal number of days between
cleaning cycles. And it is more appropriate than the approach followed in the
literature by the scientific community thus far which is based on comparing the
cleaning cost to the cost due to lack of energy production due to dust, and it is at
the instant when these two costs become the same the cleaning activity should be
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