Artificial intelligent platform to increase the performance of energy production of solar panels By Mohammed Ali Alghareeb Supervised: Dr.Walid Fahs & Dr.Jamal Haydar 1
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Artificial intelligent platform to increase the performance of energy
production of solar panels
By
Mohammed Ali Alghareeb
Supervised:
Dr.Walid Fahs & Dr.Jamal Haydar
1
Outline
Introduction
Problem statement
The factors effect on Solar cell
Weather forecasting system
Artificial neural network
Methodology
Result and testing
System advantages
Conclusion
2
Introduction
We use artificial intelligence
neural network (ANN) to
solve the dust problem on the
solar cell surface by
depending on the factors that
reduce the performance of
the solar cell .
3
Problem statement
4
The main problem to reduce the performance of the solar cell is dust
18,98 15,2 15,1
18,05 18 17,3 19,1 16,24 16
18,29 18,3 17,9
0
5
10
15
20
25
25/2/2018 23/3/2018 7/4/2018 5/5/2018 28/5/2018 24/6/2018
Open Circuit voltage Curve of clean and unclean Solar Panel
Unclean Clean
This chart shows the effect of the dust on Voltage
5
Dust Test
The factors effect on Solar cell
Temperature
Humidity
Weather
6
Temperature
19,9 19,74 18,16 17,48 16,35
0
5
10
15
20
25
15 C 25 C 30 C 40 C 50C
Temoerature
Voltage VS Temperature
Voltage [V]
7
This chart shows the effect of the Temperature on Voltage
17,1
16,72
16,53 16,45 16,41
16,33 16,32
15,8
16
16,2
16,4
16,6
16,8
17
17,2
25 30 35 40 45 50 55
Humidity
Voltage VS Humidity
This chart shows the effect of the Humidity on Voltage
Humidity
8
Day Monocrystalline
Multi crystalline
Sunny Day Higher power Higher power
Cloudy Day Low power Low power
9
Weather
This table shows the effect of the weather on solar cell
Weather
Weather forecasting system
Sunny
Good
Partially Cloudy
Bad
Rain
Very bad
10
Weather forecasting system
Five years data to predict the weather
11
Weather forecasting
Artificial neural network
12
Biological neuron model
A computer system similar to the human neural system
Methodology
13
Artificial Intelligence System to Predict Dust on Solar Cell surface
Result and testing
14
We apply on (Arduino, raspberry pi, Matlab) the results of the test lead to
the error rate (0.25) the below chart shows that
MATLAB simulation
System advantage
Water: The system uses 75% less water than manual-cleaning methods.
Automatically management: This system can be used in any place (forestry,
desert, mountains, hills snow area)
Less energy: Due to less times of cleaning.
smart and autonomous: Sensors help in receiving the data that are related to
weather, then start the cleaning process keeping in mind the weather
condition
Remote management: the cleaner’s system help monitoring and manage the
cleaning of solar panels from any place.
15
Conclusion
we find If solar cells
are not cleaned for a
month, solar cells
performance will be
reduced to 50%
which means we
must clean the
surface of the solar
cell always.
16
17
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