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Solar Panels Cleaning Frequency for Maximum Financial Profit

January 2017
Open Journal of Energy Efficiency 06(03):80-86

DOI:10.4236/ojee.2017.63006

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CC BY 4.0

Authors:

Philadelphia University

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 paper, 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 environment in which the solar panels are installed and cost incurred from undertaking the washing process.

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Open Journal of Energy Efficiency, 2017, 6, 80-86

http://www.scirp.org/journal/ojee

ISSN Online: 2169-2645

ISSN Print: 2169-2637

DOI:

10.4236/ojee.2017.63006 Aug. 11, 2017 80 Open Journal of Energy Efficiency

Solar Panels Cleaning Frequency for Maximum

Financial Profit

Mohammad Abu-Naser

Electrical Engineering Department, Philadelphia University, Amman, Jordan

Abstract

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

per,

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.

Keywords

Dust Deposition, PV Efficiency Degradation, Optimal Cleaning Cycle

1. Introduction

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 [1]. 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-

tory.

To understand the process of dust particles accumulation on glaze surfaces at

the microscopic level, Al-Hasan [2] made a theoretical analysis on the trans-

How to cite this paper:

Abu-Naser, M.

(201

Solar Panels Cleaning Frequency for

Maximum Financial Profit

Open Journal

of Energy Efficiency

, 80-86.

https://doi.org/10.4236/ojee.2017.63006

Received:

March 23, 2017

Accepted:

August 8, 2017

Published:

August 11, 2017

7 by author and

Scientific

Research Publishing Inc.

This work is licensed under the Creative

Commons Attribution International

License (CC BY

4.0).

http://creativecommons.org/licenses/by/4.0/

Open Access

M. Abu-Naser

DOI:

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 [3] 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 [4] and a regression-based model of the relationship between output

power and sand particle size and irradiance was derived.

In [5] 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

(PV).

To our knowledge [6] 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 [6] which are based on qualitative understanding of dust activities.

2. Derivation of the Optimal Number of Days between

Cleaning Cycles

The effect of sand dust particles accumulation on light transmittance coefficient

is investigated mathematically and experimentally in [2]. 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 (

) and

number of particles accumulated (

) has been derived as [2]

1π

nQ r

= −

(1)

where

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 [2] 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

M. Abu-Naser

DOI:

10.4236/ojee.2017.63006 82 Open Journal of Energy Efficiency

accuracy.

Dust accumulation on the surface of the solar panels will cause the efficiency

of the solar panel to decrement from its nominal value. So

nominal

η γη

(2)

and

γα

= −

(3)

where

is the average daily losses in solar conversion efficiency due to dust

and

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

αβ

+++ +

(4)

where

is the average sun hours per day,

is the capacity of installed PV

system, and

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

αβ

= +++ +

(5)

( )

365 12

N si

αβ

= +

(6)

()

365 1

2N si

αβ

= +

(7)

and if

is the cost of cleaning solar array, then the cost of cleaning the panels

per annum is

365 .CP

(8)

So the total cost is

JCC= +

(9)

( )

365 365

2N si P

αβ

=++

(10)

Finding the optimal number of days between cleaning cycles is achieved by

minimizing

with respect to

ˆarg min .

(11)

d 365 365 0,

J si P

αβ

= −=

(12)

ˆ,

Nsi

αβ

(13)

M. Abu-Naser

DOI:

10.4236/ojee.2017.63006 83 Open Journal of Energy Efficiency

ˆ.

Nsi

αβ

(14)

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

[7] 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% [8]. In Santiago, Chile the values ranged from 0.14% to

0.56% depending on the season and pollution level [9]. 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%

[7].

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 [10]. The cost will vary from case to case depending on

the soiling type and country where the PV system is installed [11]. 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

labor.

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

Tanesab

et al.

[12], 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 [13] 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

M. Abu-Naser

DOI:

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.

Example 1.

MW solar PV system is subjected to dust accumulation that

causes an average daily loss in solar conversion efficiency of

0.002.

If the PV

system receives an average of

sun hours per day, the price of

1 kWh

$0.1,

and the cost of cleaning a solar array is

$250.

How often should the solar array

be cleaned to maximize the gain

2 250

ˆ500 22 days.

0.002 5 1000 0.1

N×

= = ≈

×× ×

(15)

Remarks:

• 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 [10], 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

of factors;

: 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 (

αβ

) 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

M. Abu-Naser

DOI:

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 [8] and [14] for

California region.

5. Conclusion

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

performed.

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Sep 2013
SOL ENERGY

Soiling is the accumulation of dust on solar panels that causes a decrease in the solar photovoltaic (PV) system’s efficiency. The changes in conversion efficiency of 186 residential and commercial PV sites were quantified during dry periods over the course of 2010 with respect to rain events observed at nearby weather stations and using satellite solar resource data. Soiling losses averaged 0.051% per day overall and 26% of the sites had losses greater than 0.1% per day. Sites with small tilt angles (<5°) had larger soiling losses while differences by region were not statistically significant.

Dust effects on the PV plant efficiency: A new monitoring strategy

Conference Paper

Jan 2014

As well known dust deposition on PV panels results in a decrease of the electrical power produced by the panel/photovoltaic system. In order to assess this decrease and carry out a long-term economic analysis, it is desirable to make an accurate prediction of the efficiency of the system and of the maintenance costs. Starting from this assumption, an economic model that takes into account the relationship between the losses in the energy production and the cost of maintenance is very useful. In this paper the losses due to the dust will be evaluated considering radiation data provided by public meteorological stations installed which are few kilometers far from the considered PV system.

Characterization of power losses of a soiled PV panel in Shekhawati region of India

Article

Jun 2016
SOL ENERGY

This paper introduces a model that quantifies the relationship between power output, incident irradiance and soil particle size composition of soiled photovoltaic panels. Soil samples used in artificial soiling experiments were collected from Shekhawati region in India and their relative percentage of standard particle sizes is determined from sieve analysis. A non-linear relationship between irradiance and power is obtained using regression analysis showing the effect of particle size composition present on the panel. Further, the tilt angle for maximum power extraction is determined for each soiled panel and the deviation from the optimum tilt angle of a clean panel is observed. It is concluded that, when the soil present on the panel is rich in the particles with diameter (75 μm and below), the deviation from the tilt angle of a clean panel is 4°, however if the soil contains higher composition of both 150 μm and 300 μm particle sizes the deviation is 8°.

Effect of soiling and sunlight exposure on the performance ratio of photovoltaic technologies in Santiago, Chile

Article

Apr 2016
ENERG CONVERS MANAGE

Evaluation of economical benefit of cleaning of soiling and snow in PV plants at three European locations

Conference Paper

Jun 2012

Bengt Stridh

Energy loss due to soiling is one of the most important factors than can be influenced by the operator during the life of a PV plant. Snow cover can be seen as a special case of soiling applicable in countries with colder climate. A break-even analysis between energy loss due to soiling and cleaning cost was conducted for a 1 MW plant by modeling with PVsyst for three different European locations, considering both fixed tilt angle and with 2-axis tracking. As basis for net present value calculations feed-in tariffs, consumer price or spot price for electricity was used.

Simulating the dust effect on the energy performance of photovoltaic generators based on experimental measurements

Article

Aug 2011
Fuel Energ Abstr

One of the least analyzed side effects of atmospheric air pollution is the degradation of PV-panels’ performance due to the deposition of solid particles varying in composition, size and type. In the current study, the experimental data concerning the effect of three representative air pollutants (i.e. red soil, limestone and carbonaceous fly-ash particles) on the energy performance of PV installations are analyzed. According to the results obtained, a considerable reduction of PVs’ energy performance is recorded, depending strongly on particles’ composition and source. Subsequently, a theoretical model has been developed in order to be used as an analytical tool for obtaining reliable results concerning the expected effect of regional air pollution on PVs’ performance. Furthermore, experimental results concerning the dust effect on PVs’ energy yield in an aggravated – from air pollution – urban environment are used to validate the proposed theoretical model.

The effect of soiling on energy production of large-scale photovoltaic plants

Article

May 2011
SOL ENERGY

This work aims to evaluate the effect of soiling on energy production for large-scale ground mounted photovoltaic plants in the countryside of southern Italy. Since the effect of pollution can seriously compromise the yield of solar parks, the results obtained in this study can help the operation and maintenance responsible in choosing the proper washing schedule and method for their plants and avoid wasting money. In order to determine the losses due to the dirt accumulated on photovoltaic modules, the performances at Standard Test Conditions (STC – Irradiance: 1000W/m2; Cell temperature: 25°C; Solar spectrum: AM 1.5) of two 1MWp solar parks before and after a complete clean-up of their photovoltaic modules have been compared. The performances at STC of the two plants have been determined by using a well-known regression model that accepts as an input two climate data (the in-plane global irradiance and the photovoltaic module temperature), while the output results in one electrical parameter (the produced power). A regression model has been preferred to a common performance ratio analysis because this latter is too much influenced by the seasonal variation in temperature and by the plant availability. The results presented in this work show that both the soil type and the washing technique influence the losses due to the pollution. A 6.9% of losses for the plant built on a sandy soil and a 1.1% for the one built on a more compact soil have been found. Finally, these results have been used in order to compare the washing costs with the incomings due to the performance improvement.

Degradation of photovoltaic cell performance due to dust deposition on to its surface

Article

Sep 1993
RENEW ENERG

The effects of dust accumulation on the surface of photovoltaic cells were experimentally investigated. The dust used in this study was prepared in the laboratory from known materials, then examined under an optical microscope to determine the size distribution of the particles. The two main parameters of the size distribution were determined, namely, the mean diameter and the standard deviation. A solar simulator consisting of halogen lamps was used to carry out controlled experiments. The dust particles were dispersed uniformly over the test photovoltaic panel and the characteristics were determined. The dust deposition density in g/m2 of panel surface area was determined in each test run. The effect of dust deposition density on the short circuit current, output power and the fill factor was determined and discussed. It was concluded that dust accumulation considerably deteriorates the performance of the photovoltaic cells. However, in carrying out the investigation on the effect of dust and particulate pollution, the physical characteristics of dust must be determined and correlated to the observed effects.