Solar Panel Energy Modeling by using Matlab Simulink

Tjerie Pangemanan

, Vecky C. Poekoel

, Alfrets Septy Wauran

and Arnold Robert Rondonuwu

Electrical Engineering Department, Manado State Polytechnic, Manado, Indonesia

Electrical Engineering Department, Sam Ratulangi University, Manado, Indonesia

Keywords: New Renewable Energy, Sunshine, Solar Panels, Matlab Simulink.

Abstract: New and renewable energy is one of the research priorities in Indonesia and even the world today. This is to

answer the limitations and the high cost of using conventional energy sources such as petroleum for

generators. By using new and renewable energy, we can save costs and also help governments and the world

to keep the air clean from the dangers of pollution. For Indonesia we have abundant natural resources

including constant and high intensity sunlight. This encourages us as researchers to make maximum use of

one of these renewable energy sources. Solar Panel, which is the application of new and renewable energy

technology that comes from solar insulation. In its use to the community, an analysis must be carried out in

advance of the intensity of sunlight in a certain area. This is to calculate the number of solar panels that will

be used to meet the energy needed by the community. Therefore, this study aims to create a solar panel model

with input in the form of light insulation data using Matlab Simulink. So that by modeling and analyzing the

amount of energy produced by a certain type of solar panel, it can determine how many solar panels are

needed for a certain area.

1 INTRODUCTION

Renewable energy is one of the most well-known

energy problems today. There are several potential

sources of renewable energy. One of the common and

simple renewable energies is solar energy. The big

problem with the current availability of energy is the

limited conventional energy sources such as fuel.

These all energy sources have a lot of problems

because they have a finite amount of energy. It is

important to create models and analyzes based on the

availability of energy sources. Solar energy is the

most preferred renewable energy in equatorial

countries today. It depends on the production of solar

energy in a particular area to have a good solar energy

design and analysis. To have a good analysis of that,

in this paper we make a predictive model of solar

energy based on solar irradiation data.

Solar Panel, which is the application of new and

renewable energy technology that comes from solar

insulation. In its use to the community, an analysis

must be carried out in advance of the intensity of

sunlight in a certain area. This is to calculate the

number of solar panels that will be used to meet the

energy needed by the community. Therefore, this

study aims to create a solar panel model with input in

the form of light insulation data using Matlab

Simulink. So that by modeling and analyzing the

amount of energy produced by a certain type of solar

panel, it can determine how many solar panels are

needed for a certain area.

2 RESEARCH LITERATURE

Modeling of Solar Panel/Photo voltaic Energy

System:

The output of PV-arrays is DC Power and this output

can be directly used to the DC load/appliances.

Hence, if the load is AC appliances, the DC power

has to be changed into AC form using power

electronic inverters (DC/AC). In the SOPRA HAN

system, the type of load is AC appliances. Hence, the

PV-arrays are connected to the battery pack via ESI

converter (AC-DC) which is a bi-directional DC/AC

converter. There are many mathematical models

developed to describe the behavior of PV. In this

project, the model reepresents the power output of

PV. Hourly power output from PV system with an

area Apv (m2) on an average day of jth month, when

total solar radiation of IT (kW h/m2) is incident on

PV surface, so the equation 1 of the system:

1410

Pangemanan, T., Poekoel, V., Wauran, A. and Rondonuwu, A.

Solar Panel Energy Modeling by using Matlab Simulink.

DOI: 10.5220/0010966300003260

In Proceedings of the 4th International Conference on Applied Science and Technology on Engineering Science (iCAST-ES 2021), pages 1410-1414

ISBN: 978-989-758-615-6; ISSN: 2975-8246

 2023 by SCITEPRESS – Science and Technology Publications, Lda. Under CC license (CC BY-NC-ND 4.0)

(1)

where system efficiency ƞ is given by

and, the module efficiency ( ) is given by

(2)

Where

IT = The total solar radiation is incident on PV

surface (W/m2)

Apv = Area of a single PV-panel (m2)

ƞ = System Efficiency

ƞm = module efficiency

ƞpc = Power converter efficiency

Pf = Packing Factor

ƞr = Module reference Efficiency

β = The array efficiency temperature coefficient

Tr = The reference temperature for the cell

efficiency (

Ta = The instantaneous ambient temperature (0C)

NOCT = Normal operating cell temperature (

IT,NOCT= The iradiation in NOCT (W/m2)

Ta,NOCT= The ambient Temperature in NOCT (

There are 2 types of PV Panels (SI185N and FS225)

used the system and their parameter which are used

for the calculation of powers from a PV panel can be

seen in the datasheets. Based on the equations, the

simulation model for the PV array is shown in fig 1

below:

Figure 1: Simulink Matlab model for output power of PV

Array SI185N.

3 RESEARCH METHODS

This study uses statistical modeling based on data on

wind speed, sunlight insulation and the amount of

electricity used. MATLAB application software is

used as a simulator to obtain the amount of power

generated by solar panels. Wind speed data is

obtained from secondary data in the form of data from

a certain area. Likewise, the type of solar panel used

is the type ES225 / SI185N. This statistical modeling

uses physical formulas based on mathematical and

physics models with the input of sunlight insulation

excel data. The variables and system equations will

be simulated in the MATLAB application software.

Solar panels are devices that consist of solar cells

that convert light into electricity. They are called solar

or sun or "sol" because the sun is the strongest light

source that can be utilized. Solar panels are often

called photovoltaic cells, photovoltaic can be

interpreted as "electric light". Solar cells rely on the

photovoltaic effect to absorb energy. In general, a

solar cell is a semi-conductor expanse that can absorb

photons from sunlight and convert it into electricity.

These solar cells are made of tiny pieces of silicon

coated with a special chemical to form the basis of the

solar cell. Solar cells generally have a minimum

thickness of 0.3 mm and are made of slices of

semiconductor material with positive and negative

poles. In a solar cell there is a connection (function)

between two thin layers made of semiconductor

material, known as "P" type semiconductors

(positive) and "N" type semiconductors (Negative),

respectively. P type silicon is a surface layer that is

made very thin so that sunlight can penetrate directly

to reach the junction.

This part P is given a ring-shaped nickel coating,

as the positive output terminal. Below the P section,

there is a type of N section coated with nickel as a

terminal. The process of converting or converting

sunlight to electricity is possible because the material

that makes up solar cells is a semiconductor. More

precisely, it consists of two types of semiconductors,

namely the n type and the p type. An n-type

semiconductor is a semiconductor that has an excess

of electrons, so that the excess is negative, (n =

negative). Meanwhile, p type semiconductors have

excess holes, so it is called p (p = positive) because of

the excess positive charge. Initially, the manufacture

of these two types of semiconductors was intended to

increase the level of conductivity or the electrical and

thermal conductivity of natural semiconductors. In

this natural semiconductor, the electrons and holes

have the same number. Excess electrons or holes can

increase the electrical and thermal conductivity of a

semicoductor. These two types of n and p

semiconductors, when put together, form a p-n

connection or p-n diode. negative output.

Solar energy is the most preferred renewable

energy in equatorial countries today. It depends on the

production of solar energy in a particular area to have

a good solar energy design and analysis. To have a

Solar Panel Energy Modeling by using Matlab Simulink

1411

good analysis of that, in this paper we make a

predictive model of solar energy based on solar

irradiation data. We are modeling solar energy using

Matlab and Simulink.

Figure 2: Solar Panel Power Matlab Script.

At the figure 2 we transform the mathematical

equations of the PV Model into matlab script. It is a

statistical model. So, we get the input from the excel

file consist of solar insulation data sheet as the input

of the model.

At the figure 3 we make a simulation based on the

time series excel input into the simulator. I will

display the power produced by the PV Array in the

system. So, the output of power produce the pattern

based on the various time series input of the solar

irradiation. All of the Matlab Script is written with the

explanation to have a good understanding for the

analiys for the power.

Figure 3: Solar Panel Energy Graph Matlab Script.

Validation of Power Output Model of Solar Panel/

Photo Voltaic

This section describes the procedure to validate or

verify the power output model of components of

SOPRA HAN. The first plan before the project will

be done, the validation will use the measurement data.

However, until this report is writen the SOPRA plant

still has some technical problem so that it is not

possible to validate with it. Hence, the verify or

validation the power output components are done by

comparing it with information or data from datasheet

components.

As explained in section 3.2.1, there are two

models of solar panel that represents two types of

Solar panel that used in SOPRA as model of PV

SI185N and FS225. To see the performance of the

model simulation of solar panel, we generate the

artificial dataset of weather input that represents the

normal operating condition of PV SI185N and FS225.

For the type PV SI185N, the max power output for a

single PV panel with the test condition with

temperature ambient (Ta) 20oC and the maximum

input iradiation 1000 W/m2 is 185 Watt with

efficiency module 14.5%. While the type PV FS225

the max power output for a single PV panel is

225Watt with efficiency module 14.5% in test

conditions with 20oC and the maximum input

iradiation 1000 W/m2. The figures below show the

simulation power output of a single PV panel for both

type of PV panel.

Figure 4: The output Power of a single of PV SI185N with

constant Iradiation 1000 W/m

Figure 5: The output Power of a single of PV FS225 with

constant Iradiation 1000 W/m

Figure 4 and Figure 5 show the simulation of PV

model with keep the iradiation in 1000 W/m2 and

iCAST-ES 2021 - International Conference on Applied Science and Technology on Engineering Science

1412

variance of temperature ambient (Ta). It can be seen

the output power of PV affected by Ta. It will affect

the temperature cell of PV which there is a decrease

of efficiency of PV if there is an increase Ta surround

the PV panel. Both of the simulation result of PV

SI185N and PV FS225 show that for the iradiation

1000 W/m2 and Ta 20

C, then the power output of

both PV are 185 W and 225 W respectively.

Figure 6 :The output Power of a single of PV SI185N with

constant Ta 20

Figure 7: The output Power of a single of PV FS225 with

constant Ta 20

Based on the figure 6 and Figure 7, it can be seen

the output power of both type PV depends on the solar

iradiation. The output of PV will decrease when the

amount of solar iradiation is become smaller. The

changing of amount of solar iradiation gives high

impact to the power output of PV. Otherwise, the

effect of temperature to the output power of PV is in

small amount.

All of the simulation result above is represented

to see the performance of the power output models of

a single PV panel of both type PV. And one of must

be considered that each region has typical weather.

For instance, in tropical region like thailand has a

high average solar iradiation and also high average

temperature where the last give decrease impact to the

power output. Otherwise the west region has the

opposite condition. The next chapter (chapter 4) will

shows the result of solar panel as a PV array and the

efect of this power output by teh real weather

condition.

4 RESULTS AND DISCUSSION

The simulation and analysis of the system design

above is to use statistical modeling based on wind

speed data, sunlight insulation and the load of a

certain area. The data is analyzed into the Matlab

application using the physical equations of the system

components. The following is modeling using the

Matlab Editor:

Figure 8: Power Produced in 1 Year.

Based on the Figure 8, the various output as the power

of PV Array in a year. It describe a maximum power

in the middle of the year. I caused by the solar

insulation has a pattern in every year.

Figure 9: Simulation of Sunlight Insulation per Month in 1

Year.

Based on the Figure 9, it describe the pattern of every

month power produced by the PV Array. I shows that

July is the maximum power produced every year.

PV Power for 1 year [W]

PV-Arrays Power (W)

Time [hour]

Solar Irradiation [W / m2]

Time [Hour]

Jan

Feb

Mar

Apr

May

Jun

Jul

Aug

Sep

Oct

Nov

Dec

Solar Panel Energy Modeling by using Matlab Simulink

1413

Because the position of the earth toward the sun

namely aphelium and perilium.

Figure 10: Irradiation in 1 Year.

From the figure 10 above, it describes the various

solar irradiation in 3 serial months. At the middle of

the year from July to September produced more

power because the distance between the sun and the

earth.

5 CONCLUSION

From these results it can be concluded that the value

of solar irradiation varies each month. This

determines the amount of energy produced by the

solar panels. The more renewable components

available, the greater the value of the power.

However, this will result in an even greater cost.

Therefore, it is necessary to find the ideal amount of

these components to produce energy as efficiently as

possible. Likewise, the graphs taken in this study look

too large, resulting in unstable power. The value of

the power generated to be efficient must be in

accordance with the amount of load and data on

sunlight insulation in the area.

REFERENCES

Anwar Ramadhan, Eri Diniardi, Sonny Mukti. (2016).

Analisis Disain Pembangkit Listrik Tenaga Surya

Kapasistas 50 WP E-Journal Teknik UNDIP.

Hardianto, H. E., Rinaldi, R. S. (2012). Perancangan

Prototype Penjejak Cahaya Matahari Pada Aplikasi

Pembangkit Listrik Tenaga Surya. Program Studi

Teknik Elektro,Universitas Bengkulu, Bengkulu.

Hasan, H. (2008). Perancangan Pembangkit Listrik Tenaga

Surya Di Pulau Saugi. Jurusan Teknik Perkapalan,

Fakultas Teknik Universitas Hasanudin, Makasar.

Lilia Trisyathia Quentara, Erma Suryani. (2017). The

Develompment of Photovaltaic Power Plant of

Electrricity Demand Fullfilment of Remote Regional of

Madura Island using Dinamic Model. Proceedings of

ISICO International Conference, Bali, Indonesia.

Siahaan, A. (2017) Implementasi Panel Surya yang

diterapkan Pada Daerah Terpencil Di Rumah Tinggal

Di Desa Teknik Elekro UMRAH.

Yuwono, B. (2005). Optimalisasi Panel Sel Surya Dengan

Menggunakan Sistem Pelacak Berbasis

Mikrokontroller AT89C51. Skripsi, Jurusan Fisika,

FakultasMatematika dan Ilmu Pengetahuan Alam

Universitas Sebelas Maret, Surakarta.

Jan-Feb-Mar

Apr-May-Jun

Jul-Aug-Sep Oct-Nov-Dec

iCAST-ES 2021 - International Conference on Applied Science and Technology on Engineering Science

1414