Performance Analysis of PV System on Real Time Sun Tracking

Structure for Grid Connection in Southern Algeria

Messaouda Khennane Benbitour

, Sliman Boughali

, Djamal Bechki

, Ali Malek

, Boubaker

Azoui

, Layachi Zaghba

, Amor Fezzani

, Idriss Hadj Mahammed

, Samir Hamid Oudjana

Applied Renewable Energy Research Unit, URAER, Renewable Energy Development Center, CDER, 47133,

Ghardaia, Algeria

Kasdi Merbah University, Ouargla,

Institute of Problem Solving, Algeria

Renewable Energy Development Center, CDER, Algeria

Université Batna 2 University, Algeria

Keywords: PV performance, inverter, sun tracking, modeling

Abstract: In this study, we analyze the experimental annual energetic performance of a photovoltaic system mounted

on a solar tracking structure. This equipment had been acquired by the Renewable Energy Applied Research

Unit (REARU) of Ghardaia. The pv field is constituted by a monocrystalline module (specification in

appendix) with a peak power of 2.25 kW, and an inverter Fronius IG15 power of 1.3 kW. The annual energy

produced by the system is 3.61 MWh and injected in the internal power grid of REARU, whereas its energy

calculated for the same period is 3.79 MWh, the annual produced energy of a same system with a fixed

angle is 2.13MWh. The performance ratio (PR) of the system is at its minimum in January with 0.44 and its

maximum in April with 0.88. Implantation site characteristics are : Latitude 32.4°, Longitude 3.80° and

Altitude 468.4 m, located in the desert at 600 km south of Algiers. We begin by the presentation of each part

of the system, and after that, the modeling of each sub-system. Performance indexes of the photovoltaic

system connected to the power grid (PVSGC), especially the PR are measured, and also the impact of losses

on energy production. All results obtained during the analyze period are presented and discussed, followed

by conclusions and specific recommendations for this system type and its environment.

1 INTRODUCTION

Nowadays, renewable energy became more and

more attractive and environment protection became

a recurrent theme.

Algeria is a country with a large number of

sunny days. The Algerian land is mainly is arid and

semi-arid, where the huge demand of electricity in

the warm season. To meet this demand, it is

recommended to inject renewable energy production

in the power grid.

In Algeria, most of electrical energy production

comes from fossil energy – petrol and natural gas.

The rest comes from renewable energy, mainly

made up of hydraulic and photovoltaic energy.

Thanks to its geographical position, Algeria is

one of the largest potential solar sites in the world.

Solar irradiation on the main part of the territory

exceeds 2000 h per year and 3900 h on the

Highlands and Sahara.

Daily energy received on a 1m2 horizontal area

is 5 kWh on the main part of the national territory,

comprised of 1700 kWh/m2/year in the North and

2263 kWh/m2/year in the South. "Renewable

Energy Portal"

The aim of the renewable energy development

national program (2015-2030) is to reach 27% of

national energy production from renewable one and

37% of installed capacity in 2030. The volume of

natural gas saved by renewable energy production of

Benbitour, M., Boughali, S., Bechki, D., Malek, A., Azoui, B., Zaghba, L., Fezzani, A., Mahammed, I. and Oudjana, S.

Performance Analysis of PV System on Real Time Sun Tracking Structure for Grid Connection in Southern Algeria.

DOI: 10.5220/0009775904090418

In Proceedings of the 1st International Conference of Computer Science and Renewable Energies (ICCSRE 2018), pages 409-418

ISBN: 978-989-758-431-2

409

22000 MW is approximately 300 Billion m3,

equivalent to 8 times consumption volumes of 2014

year. "Renewable Energy Portal"

(FİLİK et al., 2017) have analyzed the

comparison of the solar tracking photovoltaic (PV)

system and the same solar fixed photovoltaic system

in Eskisehir region (Central Anatolia), for the period

between July to October 2016. The result is the

tracking system provides nearly 33% higher

electricity generation than the fixed one.

(KIVRAK et al. , 2012), they evaluate the

performance between the system PV with reel time

sun tracker and another one with fixed tilted in

Denizli, Turkey. For the two months May and June

the energy generated by the subtracting is nearly

64% when it is compared with fixed PV system.

When a tracker is used a system that is set up in the

area of 1000m² needs only 600m².

( Roshan et al ., 2015), report the performance of

two identical PV systems, one at a fixed latitude tilt

and the other on a two axis tracker. From August

2012 to March 2013 the tracker panel generates

21.2% more electricity than the fixed one, in India.

(De Simon Martin et al.,2014), have analyzed

the performance of three reel PV systems, fixed,

horizontal axis tracking and dual axis mount

tracking located in the same geographical area in

Spain.

(Bazyari et al., 2014), they study the effect of

the single axis and the two axes to the fixed one in

Qeshm Island of Iran in the summer of 2011. The

results of analyses show that the energy received by

the single axis system is 35% greater than energy

received by the fixed system, while the dual axis

received 4% more energy compared to the one axis

system. They conclude that the single axis tracker is

benefit to the Qeshm Island of Iran. Sharma et al.

[6], they analyze the performance of a 190kW PV

system in Khatkar-Kalan India, The performance

ratio of the PV system is 74% which is higher than

those in Greece, Poland and Germany but lower than

that in Ireland.

(Russin et al., 2013), they study performance of

PV systems from April 2012 to March 2013, in

Malaysia; the performance ratio for mono crystalline

was 77% while for polycrystalline was found to be

80%.

Performance study of a photovoltaic system

depends directly on the installation site, weather

conditions and environment. The region of Ghardaïa

has a very high solar energy potential which led us

to consider the production of electrical energy by

photovoltaic means. On the other hand the

geography of the site (rocky) imposes temperature

picks between day and night during the winters and

summer, as well as the peaks of wind speed in

autumn and spring (sand wind), which affects the

production of the systems.

To the best of our knowledge we have not found

a study of the performance of photovoltaic systems

with real time solar tracking, injecting the

production in the Sonelgaz grid, in our region.

In this column, the performance study of the first

2.25kWp PV system connected to the grid, mounted

on the real time solar tracking, located in the

Saharan climate. The system is installed in the site

named Noumirat Ghardaïa located 600km south of

Algiers.

2 PRESENTATION AND

MODELING OF THE SYSTEM

The solar panel is mounted on a real solar

tracker (figure 1), the Degger tracker 3000NT (the

characteristics of the 3000NT are in the appendix),

equipped with two circuits based on photo diode,

one fixed at the highest point of the panel for

horizontal scanning and the other fixed on the lateral

side for vertical scanning in order to track the focal

point of the power of the sun and positioning the

photovoltaic field always perpendicular to the solar

ray. The photovoltaic field has a power of 2.25kWp,

and is composed of 15 black mono-crystalline

modules (the module’s characteristics are quoted in

appendix), are connected in a single branch. The

IG15 Fronius inverter connected to the grid, has a

power of 1.3kW (the characteristics are in

appendix).

For the simulation of the system mounted

on fixed annual fixed angle structure facing south,

consisting of 15 modules. Black mono-crystalline

and an IG15 Fronius inverter, we proceeded to the

capture of weather data of the site on a horizontal

plane.

Figure: 1. Photovoltaic system mounted on the

sun tracker

ICCSRE 2018 - International Conference of Computer Science and Renewable Energies

410

The system is equipped with a meteorological

station that monitors the meteorological parameters of the

site (temperature, global irradiation on the module plan);

as well as an input and output electrical data acquisition

chain of the inverter (current and voltage of the DC input,

and current and voltage of the AC output). All

meteorological and electrical data is captured at a pace of

10 minutes and stored on a micro computer. These data

allowed us to monitor and analyze the performance of the

PVSGC. The system is in total sales mode; during the first

year (May 2016 to May 2017) of operation, all the energy

produced (3.614MWh) is injected into the internal grid of

the REARU, helping to reduce the unit electricity bill.

FIG. 2 represents the daily irradiation on the

modules plan with real time solar tracking and on the

modules plan without solar tracking and the ambient

temperature during all the day of February 08, 2017. The

maximum powers are reached between 9h and 16h, for the

tracker 1152W / m², while for the fixed 785.67W / m². At

the beginning of the day, at 7:30, the ambient temperature

is 10.6 ° C and at the end of the day, at 16:00 the

temperature reaches 19.7 ° C.

Figure: 2. The daily irradiation with sun tracking

and fixed slope, and the ambient temperature of the site,

08.Fubrary.2017 .

FIG. 3 shows the different parts of the

photovoltaic system connected to the grid in total sales

mode of the energy produced:

- The photovoltaic field consisting of

photovoltaic modules connected in parallel series in order

to obtain the voltage and the current in adequacy with the

inverter. A photovoltaic field is characterized by its

efficiency, and either its peak power or its surface.

- The inverter is the driver element of the

system; it transforms the continuous input energy into

output alternative energy injected into the grid. An

inverter is characterized by its power rating and its load

yield.

- The load for our case is the electrical grid,

which is characterized by its voltage 220V and a

frequency of 50Hz.

Figure: 3. Power plant grid-connected PVSGC

2.1. Photovoltaic Field Modelling

The most likely photovoltaic cell equivalent mathematical

model is the one composed of 5 parameters with only one

probe, the equivalent system is presented on figure 4.

Figure:4.Photovoltaic cell model

The expression of the current is (Ali et al, 2002), (Koussa

et al, 2012), (Habbati et al, 2013), (Azzedine et al, 2016),

(Attou et al, 2015), (Miric et Nedeljkavic, 2015), (Amrani

et DDib, 2016), (Ozcelik et Serdar, 2016), (Sarothi et Pal2,

2017) :

(1)

: photo generated current or photocurrent; I

: saturation

current of the diode; K: Boltzmann's constant (K=1.38*10

J/°K); e: electron charge ,(e=1.6 10

-19

C); m: ideality

factor of the diode (m=1-1.3); T: junction temperature

(°K); R

: series resistance due to the resistivity of grid,

(Ω); R

: shunt resistance due to a leakage current, (Ω).

Neglecting the effect of different resistances (very high

Rsh, very small Rs), le

electric current is

expressed by :

(2)





IRV

mKT

IRVq

III

































 1exp



























 1exp

III

Performance Analysis of PV System on Real Time Sun Tracking Structure for Grid Connection in Southern Algeria

411

As example if I

= 10

–12

A.cm

–2,

kT/q = 0,025 V, and Isc

= 4 x 10

–2

A.cm

–2

, Voc = 0,6 V

2.2 Photovoltaic Field Yield

We introduce the photovoltaic field yield model thanks to

the measures taken of the field PV. It is function of the

maximum power of the field PV P

max

, the received

irradiation on the surface of the field PV G, and the total

field surface PV Apv, following the formula (Koussa et al,

2012) :











∗



 (3)

On the other hand, the commonly used relationship to

measure the photovoltaic field yield is function of the

reference temperature T

ref

= 25°, the junction temperature

TC and the coefficient of temperature is ( Macagnan et

Lorenzo, 1992) :





th





1β∗



TcTref



(4)

Where





: is the reference efficiency of the PV field (given at

standard conditions);











∗l



(5)





0.95, returns linked to losses in the PV

field (diodes, cables ...)







0.085∗0.950.08075 (6)

The literature about systems PV studies shows that the

parameter β range of values is :

β0.0025K

-1

and β0.008K

-1

.β0.0043K

-1

The equation of the cell internal temperature is function of

ambient temperature Nominative Operating Cell

Temperature (NOCT) (Koussa et al, 2012) and (Poggi,

2007) is :







∗ (7)

The figure 5 graphs the yield evolution during the day of

08/02/2017, and shows clearly the temperature effect on

the yield. Indeed, the theoretical field PV yield perfectly

fits the real field PV yield as long as the junction

temperature is high, that is, between 7:40 AM (sunrise) to

6:20 PM (sunset). The following tab reports it clearly :

Table 1:

Time Real yield PV Theoretical

Yield PV

07 :40 0.0139 0.1467

13 :20 0.1188 0.1215

18 :20 0 0.1472

We deduce that the theoretical yield of the

equation (4) perfectly describe the evolution of system PV

during the day.



Figure: 5. Evolution of theoretical and experimental

efficiencies during the day 08.Fubrary.2017.

On the Figure 6 is reported the irradiation and the junction

temperature of the stationary modules, and the irradiation

and junction temperature of the modules mounted on solar

tracker.

Table 2:

ime

tationary

rradiatio

[W/m²]

tationary

c [°]

racker

Irradiatio

n [W/m²]

racker

Tc [°]

07 :40 15.36 11.013 183.85 17.31

13 :20 785.67 46.28 1152.49 58.53

18 :20 11.69 18.48 19.16 18.137

PVefficiency

Time

RealPVefficiency

ICCSRE 2018 - International Conference of Computer Science and Renewable Energies

412

The cumulated irradiation received by the stationary field

PV is 4.42 (kWh/m

), and the cumulated irradiation

received by the solar tracking field PV is 7.95 (kWh/m

that is, double for the day partially covered 08/02/2017.

Figure: 6. Evolution of the irradiation and the junction cell

temperature on the fixed slope and real time sun tracking,

during the day on 08.Fubrary.2017.

After the modelling of the photovoltaic field described by

its yield, its peak power and its solar irradiation collecting

surface, we focus now on the inverter modelling, which is

the photovoltaic systems’ core.

2.3 Inverter Modelling

The Inverter is completely defined by its instant yield,

which is function of the power determined by the charge.

The Inverter yield is defined as follows (Poggi, 2007) ,

( Macagnan et Lorenzo, 1992) , (Schmid et Shmidt, 1991):



/















(8)

Where the denominator represents inverter losses:













(9)

According to ref. [20], the power loss is given by:













(10)

Where





: is a constant on-load loss, it is independent of the

power demand, : is a constant which expresses the

resistive losses of the inverter, p : the inverter nominal

power, Then the efficiency becomes:



 

⁄













(11)

Specific constants P

and k of the inverter are expressed

function of inverter yields at 10/100

(





87%)and 100/100 of its nominal charge







93.5%

So:



























9 , and 











1 (12)

In this case 



0.01439 , and 0.0055129 .

The correlation coefficient is 99.7%, so the calculated

values and the measured values are identical.

The type of the inverter is limiting so the output power

cannot exceed the inverter nominal power. So we can

instantly measure the output power and calculate the

system production.

then,



11

0_/__0

^2_0_/_0_01



(13)

On the figure 7, is reported the efficiency of the

inverter according to the DC voltage. In the beginning of

the day when the DC voltage is 212.6V , the efficiency is

22%, and when DC voltage is 272V the efficiency

becomes 94% for the day, but at 16:30 (h) the efficiency

decrease to off the inverter.

Figure: 7. Inverter efficiency [%], according to the in

voltage DC [V], during the day on 08.Fubrary.2017.

Temperature'°c)

Irradiation(W/m²)

Time

Irrfixe(W/m²)

Inverterefficiency

IninverterDC[V]

Efficiency

Performance Analysis of PV System on Real Time Sun Tracking Structure for Grid Connection in Southern Algeria

413

The figure 8 shows the instant yields evolution on typical

days of all months of the year, between May 2016 and

April 2017. As soon as the sunrise, and when the input

voltage DC reaches the start value of the inverter, the yield

range of values is about 94% from 9:00 AM to 4:00 PM,

and can rise depending on seasons.

Figure: 8 Yield performances for each typical day of each

month of the year

The Figure 9 shows the monthly average value of the

yield. The yield is higher in cold period, because the

temperatures of warm periods lower the yield.

The yearly average yield of the inverter is 93.33%.

Figure 9: Average monthly efficiency of the inverter

3 STUDY OF THE SYSTEM

PERFORMANCES

To conduct the study of the energy performances of

PVSCG, the evolution of the predicted and real energy

produced by horizontal fixed slope and real sun tracking

system are measured.

3.1 Comparison between Sun Tracking

System and Horizontal Fixed Slope

Figure 10, we report all real values of daily month average

irradiation on the surface of PV modules of horizontal

fixed slope and on the surface of PV modules of sun

tracking system.

The table 3: reports all specific values of the energy:

Epv fixe Epv sun tracking

January(low

alues)

4.42kWh/m² 7.954kWh/m²

June(high values) 6.635kWh/m² 10.265kWh/m²

The sun-tracking configuration is capable to provide

significant increase in the energy production over

horizontal fixed system of equivalent characteristics.

The annual daily average horizontal fixed slope irradiation

is (5.6215kWh/m²), and the annual daily average sun

tracking is (9.227kWh/m²). The energy produced by

system fixed on sun tracking structure is higher than one

fixed on horizontal fixed slope structure, by 64%.

Figure: 11 Daily month average of real DC energy and

predicted DC energy of PVSGC, and predicted Ep fixe.

Efficiency

Time

January

Febrary

March

April

May

June

July

Month

Everage monthly

efficiency

Energy(kWh)

Month

predictedEPfixe

ICCSRE 2018 - International Conference of Computer Science and Renewable Energies

414

In figure 12, the monthly energy produced by the

real PV system with the intelligent control of

DEGERtraker, and the monthly energy injected to the

network. The report between the Epv and the Eac is equal

to (93%), so this is the inverter efficiency.

Figure12 Monthly energy produced by PV field Epv;

monthly energy injected into the power grid Eac.

3.2 Performance of the System

For normal operation, the change in the production

of electric energy from a PV system follows the change in

the sunshine. A detailed study of parameters that describe

clearly and precisely how the various components of the

system for the duration of the study is necessary. For this,

the normalized performance parameters (standard IEC

61724) (IEC, 1998) are used to define the overall

performance of the system in terms of energy production,

solar resource and the overall effect of the system losses.

The normalized performance parameters were established

to provide the necessary information on the design of the

PV system, the evaluation of their performance. They are

normalized to compare the performance of PV systems,

according to the geographical location, technology and

design. These parameters (Haeberlin and Beutler, 1995);

(Marrion et al, 2005), are (Schmid et Shmidt, 1991), (

Hadj Arab et al, 2005), (Haeberlin. et Beutler, 1995),

(Marion et Hayden , 2005):

‐ Array yield Y

Fig: 13, it is a system

productivity in a period of time (day, week,

month, year…). This parameter is defined as a

ratio of the energy produced by PVSGC plants

in a period of time t to the installed PV power.



,

,

(14)

Figure : 13 Array yield Ya.

‐ Field Yield YF, Fig:14, defined as the ratio of

the useful energy generated by the system in a

period of time with a rated power installed.

Gnom

tEGPV



(15)

Figure: 14 Normalized final productivity of PV generator

‐ Reference Yield Y

, Fig:15, is the ratio of solar

irradiance received by the PV array to the solar

irradiance at the standard conditions.





,



(16)

Figure : 15 Normalized reference productivity

‐ Performance ratio PR, Fig:16, defined as the

global efficiency of the system. It is determined

Monthlyenergy(kWh)

Month

Epvmonth

Month

Performance Analysis of PV System on Real Time Sun Tracking Structure for Grid Connection in Southern Algeria

415

by the ratio of the final yield to the reference

yield. This parameter is independent of the PV

plant size and its emplacement. Also, it is used

to compare the behavior.

Pr









 (17)

Figure:16: Pr performance index

PR is therefore an estimate of all the losses that

distinguishes the real system without theoretical loss

system. We find that this PVSGC system gives very

satisfactory results. Based on the Fig. 16, the average

yearly value of Pr is 80%, for the installed system.

In the table 4, is recorded the PV module efficiency,

the inverter efficiency and the performance index Pr, for

installed PV systems all around the world. The parameters

of our PV system are as well as other systems.

Table 4: Comparison with other installed systems in the

world.

Country



(%)



inverter

(%)

Pr Reference

Spain 13.7 89.5 0.69

(Miguel et al,

2002)

Italy 3.7 90-91 0.66

(Dunlop et al,

1997)

Brazil 3.7 91 0.5-0.81

(Ruther et

Dacoregio,

2000)

Ireland 7.5-10 87 0.6-0.62

[27] (Mondol

et al, 2006)

Malaysia 10.11 95.15 0.77

(Farhoodnes

et al, 2015)

North

Algeria

7-10 87-96

0.62-

0.82

(Cherfa et al,

2015)

South

Algeria

11-15 92-94

0.44-

0.88

Present

system

4 CONCLUSION

The first PV plant connected to the grid based on

polycrystalline modules, installed in the Algerian Sahara,

has been investigated during the period of May 2016 to

May 2017, all energy generated was fed into the low

voltage net work supply to the URAER building. During

this period are measured and analyzed daily and monthly

parameters of system, thanks to real time climatic and

performance measurements for all 5 minutes. The average

annual Daily energy of 9.89kWh is injected on the grid.

The annual daily average horizontal fixed slope

irradiation is (5.6215kWh/m²), and the annual daily

average sun tracking is (9.227kWh/m²). The energy

produced by system fixed on sun tracking structure is

higher than one fixed on horizontal fixed slope structure

by 64%.

PR is therefore an estimate of all the losses that

distinguishes the real system without theoretical loss

system. We find that this PVSGC system gives very

satisfactory results compared to PV systems installed all

around the world. The average yearly value of Pr is 80%,

for the installed system.

ACKNOWLEDGMENT

This project was financially supported by the Directorate

General for Scientific Research and Technological

Development - Algerian Ministry of Higher Education and

Scientific Research.

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Performance Analysis of PV System on Real Time Sun Tracking Structure for Grid Connection in Southern Algeria

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ANNEXES :

Table 1 Module Performance under standard test

conditions (STC): SW150

Maximum power Pmax 150W

Open circuit voltage Uoc 22.5V

Maximum power

point voltage

Umpp 18.3V

Short circuit current Isc 8.81A

Maximum power

point current

Impp 8.27A

Table 2 Inverter Fronius IG15 :

Specifications Input:

IG15 :

Recommended connection power 1300 – 2000 Wp

MPP voltage range 150 – 400 V

Max input voltage at (STC) 500V

Max input current 10.75 A

Output characteristics:

IG15 :

Rated output power 1.3kW

Max output power 1.5kW

Rated network voltage 230V +10 / -15%

Nominal output current 5.7A

Rated frequency 50 +/- 0.2 Hz

Distortion < 3%

Power factor 1

maximum efficiency 94.2 %

Euro yield 91.4 %

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