International Journal of Computation and Applied Sciences IJOCAAS Vol. 7, Issue 2, OCTOBER 2019

476

Abstract— Photovoltaic modules are the most widely used around

the world as a substitute for fossil fuels in producing clean and

environmentally friendly solar electricity. In this study, the

performance of a photovoltaic power plant established at Asmaa

Bint Al-Hareth School in Sohar, Oman, was evaluated. This

station can generate a power of 150 kW. The results of the study

showed that the system losses fluctuate from low to high values,

for example: the average daily reference return is between 4.6-7.15

(h / d), and the daily yield from 3.05-5.07 (h / d), and the system

return was 11.74- 20.54 (h / d). As for the performance of the

constant current, it ranged from 64% to 74%, and also in relation

to the power factor, whose value ranged from 11.74% to 20.5%.

The study showed that the performance of the studied station was

seasonal in the sense of changing performance due to changing

climate conditions, as the productivity of the station depends on

the intensity of the solar radiation and the period of sunshine. The

study proved that the environment conditions of the Sultanate of

Oman is suitable for operating grid connected photovoltaic power

stations, which is a successful option for producing electricity on

the national and personal levels.

Index Terms— Oman; Sohar; grid-connected; payback

period; yield; climatic conditions

I. INTRODUCTION

Economic growth and a significant increase in the

population have increased the demand for electricity all

over the world. Global energy demand for the period from

1973 to 2015 has increased from 6101 million MToe (million

tons of oil equivalents) to 13,647 million MToe; the

participation rate of fossil fuels was 82% [1]. The excessive

burning of fossil fuels for energy production has created serious

environmental and economic problems such as air pollution and

climate change [2]. The trend towards renewable energy

sources such as solar energy can be considered the most promising to reduce greenhouse gas emissions [3]. Several

important applications have been studied for the exploitation of

heat-producing or electricity-generating solar energy [4].

Energy experts predict that if the world continues to move

towards renewable energies, solar energy will occupy 27% of

global energy supply by 2050 [5]. Here, it is important to know

that the current energy supply of solar energy is less than 1% of

the global energy supply [6].

Solar-based applications are diverse, and they are thermal or

electrical applications. For thermal applications, for example,

solar water heater [7], solar air heater [8], Trombe wall [9],

gradient salt pond [10], and solar distillation can be counted [11, 12]. The production of electricity can be done using

Ali Al-Maani is with Faculty of Engineering, Sohar University, Sohar,

Oman. (Ali.IbrahimAlMaeini@Majanco.nama.om)

thermal heat through concentrated power plants and solar

chimney [13, 14] or directly using photovoltaic cells [15].

Photovoltaic (PV) cells are the most promising applications of

solar energy due to many positive properties such as ease of

installation; low maintenance cost, excellent development

potential, and does not emit greenhouse gases or noise during

normal operation [16]. The production prices of these cells have

been increasingly reduced with a qualitative increase in their

electrical efficiency [17], resulting in an accelerated trend

towards the installation and use of photovoltaics around the world [18]. 98-gigawatt photovoltaic (PV) plants were installed

in different parts of the world in 2017, twice as much as in 2015,

bringing the total capacity produced globally to more than 400

GW [19].

The solar power station has a specialized system to monitor all

parts of the station and has a central unit of measurement, which

uses sensors and software in the monitoring system to obtain

data such as the production of electricity from the plant daily,

monthly, and annually. The measurments unit monitors all

changes to system standards and records system failures,

including a meteorological monitoring section, etc. [20, 21]. PV grid-connected electricity systems can be divided into two

types; the first is the integrated PV system (BiPV) and the

second is the PV generation system (DGPV) distribution

system [22]. BiPV systems supply electricity to a certain

amount and if there is an excess, it is pumped into the grid [23].

The second type, DGPV systems, generates electricity and

pumps it into the grid without feeding any local load. Grid-

connected PV systems can consist of a single saw PV array or

several rows of photovoltaic cells, and can be enhanced with

another power source such as wind turbines, diesel generators

or storage units (batteries) [24]. Hybrid systems are used in

conditions where there is a frequent lack of power supply, to ensure compensation for under-load [25].

The grid-connected PV systems can be classified into two types

depending on the use of batteries as storage to systems with

battery storage or systems without this storage. In integrated

photovoltaic (BiPV) systems, surplus electricity is sold to the

grid, but if the electricity supplied from the PV plant is not able

to compensate, the shortage of electricity supplied in the grid

will be compensated [26].

Because of the importance of photovoltaic power plants

connected to the grid in the provision of renewable electricity

environmentally friendly and reduce pollution and dependence on fossil fuels, many researchers have conducted valuable

studies in this field, the following paragraphs show some of

these efforts:

Ref. [27] conducted a review to demonstrate the importance of

grid-connected PV systems. The study focused particularly on

Evaluation of a 150 kW grid-connected PV

station constructed in Sohar –Oman Ali Al-Maani*, Mohamed Al-Maani, Kareem Al-Maani

T

International Journal of Computation and Applied Sciences IJOCAAS Vol. 7, Issue 2, OCTOBER 2019

477

conversion efficiency and tension compatibility. The study

showed that the conversion efficiency in the reflectors usually

exceeds 90% with the outlook for total compatibility does not

exceed 5%. The study also highlighted the most important

problems that researchers should address, such as over-scaling

in the PV generator for inverters. In Turkey, Ref. [28] evaluated the economics of a grid-connected photovoltaic power system

and also connected to a battery storage system. After analyzing

the weather data, the researchers used two different scaling

methods. In the first method, they studied volume when the

electricity generated and demand were equal annually. In the

second method, the researchers hypothesized that this equality

occurs in the month of peak demand. The results of the study

showed that the cost of electricity generated from photovoltaic

power stations connected to the grid will be higher per kilowatt-

hour with a limit of 3 to 4 times higher than electricity generated

at fossil fuel stations. The reason for these high costs, as the

researchers explained, is due to the high taxes imposed by the Turkish government with no government subsidies for PV

electricity.

In Spain, Ref. [29] evaluated a grid-connected photoelectric

power system (GCPV) producing 2 kW. The results of the study

showed that the average demand for electricity in the station

area is 7.4 kWh, and this plant has achieved 4.1% to 8% of the

average monthly demand for electricity. In the United Arab

Emirates (Oman's formal neighbor), Ref. [30] designed and

evaluated the performance of the GCPV system under the

conditions of this hot weather country for a whole year. The

study showed the effect of the accumulation of dust on the performance of the system as it caused a significant decrease in

the productive capacity. The researchers considered dust to be

a major concern for the implementation of PV systems in desert

areas. The researchers also showed the effect of high

temperature air and relative humidity, which caused a loss in

producing capacity of up to 27%.

In Daegu Metropolitan, Ref. [31] conducted a practical

evaluation of the performance of two types of GCPV systems.

The study focused on the effect of several weather factors such

as atmospheric temperature, the intensity of horizontal

radiation, and the tilt angle of the photovoltaic cells on the

efficiency of the two plants. The study results showed that the annual electrical efficiency of both plants reached 10.8%. Most

costs (80%) are also caused by PV and inverter cells.

In Kuwait, Ref. [32] assessed the performance of GCPV and its

association with electrical load and weather data. The practical

study showed that GCPV systems caused a lower electricity

load at peak demand; the effect of the PV plant in reducing the

peak monthly demand was evident.

Many researchers have designed and evaluated the performance

of several photovoltaic production systems implemented in the

Sultanate of Oman. Ref. [33] studied the possibility of

predicting the intensity of solar radiation for 17 different locations in Oman. These sites are Ramees, Khasab, Mina

Qaboos, Primi, Rusayl, Seeb, Sur, Masirah, Fahud, Marmul,

Yaloni, Kirun Sh'ayti, Majis, Thumrait, Suwaiq, and Mini

Raysut. The results of the study showed that the average solar

energy in these sites is about 5.597 kWh/m2/day. The

researchers found that the cost of electricity produced by the

photoelectric in the conditions of the studied cities is about $

0.21/kWh.

Ref. [34] used prepared data for 25 sites in the Sultanate to

study the economic feasibility of the establishment of

photovoltaic electricity systems there. The researchers

hypothesized the establishment of 5 MWp PV plants and

studied the economic feasibility of such systems using

RETscreen softwere. The simulation results showed that the cost of electricity produced from these systems ranges from

0.21 to 0.304 USD/kWh. Ref. [104] used the HOMER program

to simulate the use of a hybrid system consisting of a PV station

with a wind field and a diesel generator to be used in Oman's

environmental conditions. The results indicated that diesel

generators could be replaced by the proposed system and that

the economic returns of such hybrid systems depend directly on

the potential of energy sources such as wind and solar energy

as these resources are unequal in Oman. Ref. [35] also used the

HOMER program to determine the optimal size of renewable

energy systems that would be able to meet the demand for

electricity in remote locations of Oman (Hajar, Bani and Hamid in northern Oman, Masirah Island and Muthurah area in

southern Oman). The cost of electricity produced by the

proposed systems ranged from 0.206 to 0.361 USD/kWh. Table

2-1 lists the most updated article in this field.

The present work aims to study and evaluate the performance

of a 150-kW grid-connected PV system in Omani climate

conditions. The success of these systems will open the way to

build many other stations which will reflect positively on the

Omani environment and health.

II. EXPERIMENTAL SETUP

A) The status of electric power in Oman

In the Sultanate of Oman, the demand for electricity increased

from 2773 MW in 2007 to 5691 MW in 2014, which is twice

the electricity demand, and it is expected to increase the annual

growth rate of electricity demand to reach 17.8%. Rising

population growth and the rapid industrial renaissance in the

Sultanate caused an increase in peak demand for electricity.

With this continuing escalation in demand, a shortage of

electricity supply is expected in the coming years. Figure 4 shows the rising demand for electricity in the Sultanate [36].

Electricity in Oman is produced entirely using natural gas

(fossil fuels). The Sultanate produces natural gas locally. The

total natural gas produced in 2009 amounted to 1,097,661

million cubic feet and 92% of this gas was consumed locally in

electricity production. This consumption of this material, which

can be used in exporting and bringing foreign currencies to the

country, means a waste of national wealth. Hence the need to

conduct in-depth studies on the utilization of a number of

renewable energy types in the Sultanate of Oman and how to

encourage foreign investments in this field. Figure 5 shows the energy demand in Oman for 2006 and 2007 by sector.

The Sultanate has undertaken several projects to provide solar

energy to some of the Sultanate's schools in cooperation with

Shell Co. The aim of these projects is to provide clean and

environmentally friendly electrical energy for use in schools, in

addition to developing work in the renewable electricity sector

and training Omani cadres to provide a local technical base that

contributes to the development of this sector in the future [37].

The project began in several Omani schools by Shell company

in 2016, and the installation of photovoltaic power stations

International Journal of Computation and Applied Sciences IJOCAAS Vol. 7, Issue 2, OCTOBER 2019

478

connected to the network was completed in several schools.

These include the Sultan Qaboos School in Buraimi, Khawla

Bint Al-Hakim School in Salalah, Umm Al-Fadl School in Al-

Banana Pool in Nizwa, and Al-Asma'a Bint Al-Harith School

for Girls and Kaaba Bin Barsha School for Boys in South Al

Batinah Governorate. Work is underway to set up such stations in 22 schools across the Sultanate, with an average of two in

each governorate. These stations aim to reduce the load on the

central grid and save 30% of the annual electricity consumption

in these schools. This project is the first pilot experience in this

field for the application of photovoltaic systems connected to

the grid and this experience has the full support of all official

authorities. The project also includes the organization of

training courses to prepare a staff capable of handling the

maintenance and installation of such stations by Shell Co.

The photovoltaic power plant in Asmaa Bint Al Hareth School

- Sohar started on August 9, 2018. The plant has a capacity of

151.2 kW. In this study, we will monitor and evaluate the operation of this 150 kW grid-connected photovoltaic system.

In this chapter we will show the methodology of monitoring and

evaluation for the system and devices used in the

measurements, which lasted for one year. The work carried out

focused on the impact of different weather conditions on the

performance of the system and the success of such systems to

work in the weather and environmental conditions of the

Sultanate of Oman in general and the city of Sohar in particular.

B) System description

In this study, the performance evaluation of the PV system

connected to the grid established at Asma Bint Al Hareth School in Sohar will be monitored. The system has generated

power of 150 kW grid-connected photovoltaic system supplies

DC power that is converted by aid of invertor to AC current.

The school is located at Latitude 24.32° N and Longitude

56.75° E. The system can be descriped as group of modules

with an area of 428 m² while the Cell area is 382 m². This station

designed to generate (151.20 kWp). Type: Photovoltaic systems

connected to public electricity network (on‐grid). Fig. 1 & 2

represents pohotos of the studied station. At this station, the

designers used Monocrystalline silicon (Si-mono) solar cells

and paved in two sets of 18 modules, of which they were serialized and six of them in parallel. The modules plane

orientation tilt angle is 5° causes a shading on the car garage by

a width of 5.00 m and the length of the system is 76 m. The

station modules area is 428 m2 and the cell area is 382 m2. The

designer used 216 modules to generate 150 kW of electricity.

C) The status of electric power in Oman

In the Sultanate of Oman, the demand for electricity increased

from 2773 MW in 2007 to 5691 MW in 2014, which is twice

the electricity demand, and it is expected to increase the annual

growth rate of electricity demand to reach 17.8%. Rising

population growth and the rapid industrial renaissance in the Sultanate caused an increase in peak demand for electricity.

With this continuing escalation in demand, a shortage of

electricity supply is expected in the coming years. Figure 4

shows the rising demand for electricity in the Sultanate [36].

Electricity in Oman is produced entirely using natural gas

(fossil fuels). The Sultanate produces natural gas locally. The

total natural gas produced in 2009 amounted to 1,097,661

million cubic feet and 92% of this gas was consumed locally in

electricity production. This consumption of this material, which

can be used in exporting and bringing foreign currencies to the

country, means a waste of national wealth. Hence the need to

conduct in-depth studies on the utilization of a number of

renewable energy types in the Sultanate of Oman and how to

encourage foreign investments in this field. Figure 5 shows the

energy demand in Oman for 2006 and 2007 by sector. The Sultanate has undertaken several projects to provide solar

energy to some of the Sultanate's schools in cooperation with

Shell Co. The aim of these projects is to provide clean and

environmentally friendly electrical energy for use in schools, in

addition to developing work in the renewable electricity sector

and training Omani cadres to provide a local technical base that

contributes to the development of this sector in the future [37].

The project began in several Omani schools by Shell company

in 2016, and the installation of photovoltaic power stations

connected to the network was completed in several schools.

These include the Sultan Qaboos School in Buraimi, Khawla

Bint Al-Hakim School in Salalah, Umm Al-Fadl School in Al-Banana Pool in Nizwa, and Al-Asma'a Bint Al-Harith School

for Girls and Kaaba Bin Barsha School for Boys in South Al

Batinah Governorate. Work is underway to set up such stations

in 22 schools across the Sultanate, with an average of two in

each governorate. These stations aim to reduce the load on the

central grid and save 30% of the annual electricity consumption

in these schools. This project is the first pilot experience in this

field for the application of photovoltaic systems connected to

the grid and this experience has the full support of all official

authorities. The project also includes the organization of

training courses to prepare a staff capable of handling the maintenance and installation of such stations by Shell Co.

The photovoltaic power plant in Asmaa Bint Al Hareth School

- Sohar started on August 9, 2018. The plant has a capacity of

151.2 kW. In this study, we will monitor and evaluate the

operation of this 150 kW grid-connected photovoltaic system.

In this chapter we will show the methodology of monitoring and

evaluation for the system and devices used in the

measurements, which lasted for one year. The work carried out

focused on the impact of different weather conditions on the

performance of the system and the success of such systems to

work in the weather and environmental conditions of the

Sultanate of Oman in general and the city of Sohar in particular. D) System description

In this study, the performance evaluation of the PV system

connected to the grid established at Asma Bint Al Hareth

School in Sohar will be monitored. The system has generated

power of 150 kW grid-connected photovoltaic system supplies

DC power that is converted by aid of invertor to AC current.

The school is located at Latitude 24.32° N and Longitude

56.75° E. The system can be descriped as group of modules

with an area of 428 m² while the Cell area is 382 m². This station

designed to generate (151.20 kWp). Type: Photovoltaic systems

connected to public electricity network (on‐grid). Fig. 1 & 2 represents pohotos of the studied station. At this station, the

designers used Monocrystalline silicon (Si-mono) solar cells

and paved in two sets of 18 modules, of which they were

serialized and six of them in parallel. The modules plane

orientation tilt angle is 5° causes a shading on the car garage by

a width of 5.00 m and the length of the system is 76 m. The

station modules area is 428 m2 and the cell area is 382 m2. The

designer used 216 modules to generate 150 kW of electricity.

International Journal of Computation and Applied Sciences IJOCAAS Vol. 7, Issue 2, OCTOBER 2019

479

Fig. 1: Pictures of the Asma Bint Al Hareth School PV station connected to

the grid (Part 1)

Fig. 2: Pictures of the Asma Bint Al Hareth School PV station connected to

the grid (Part 2)

The Asma Bint Al Hareth School GCPV station project is

supplied by many accessories in addition to the PV panels and

inventers. It is very important to control the and monitor the

electrical power outcomes. As this system is grid connected, it

is not supported by batteries for electricity storage. The station

is equipped with weather station to monitor the weather

variables as wind speed, solar irradiance, air temperature, and

relative humidity. It is also equipped with energy meter to monitor the generated electricity. The system specifications are

summarized as in Table 1. Table 1: Asma Bint Al Hareth School PV station project specifications

Item Description Make Quantity

PV Modules

DUOMAX 72-cell,

MonoPERC,

Bifacial, Dual Glass

(345 Wp)

Trina Solar

432

Inverter SUN2000 – 36 KTL

(36 kW) Huawei 4

Monitoring

System

Blue Log X-3000

Meteocontrol

1

Weather Station

WS600-UMB

Lufft

1

Pyranometer

SMP10

Kipp & Zonen

1

Irradiance Cell

with

Temperature

Probe

Si-RS485-TC-T V2 Mencke and

Tegtmeyer 2

Energy Meter 2-Way Meter

(EM3255) Schneider Electric 2

Interface

Protection

Device

VMD460 - NA Bender 1

The photovoltaic modules are the most important part in the

system and it represent the highest cost part of the system.

Table 2 lists the used PV modules specifications

Table 2: The studied stations’ PV module specifications

PV module Monocrystalline 156.75 × 156.75 mm (6

inches)

Model TSM-350DEG14C.07(II)

Manufacturer Trina Solar

Cell orientation 72 cells (6 × 12)

Module dimensions 1985 × 998 × 28 mm

Weight 28.5 kg

Front Glass 2.5 mm (0.10 inches), High Transmission,

AR Coated Heat Strengthened Glass

PV module rated power

(216 modules)

150 kWp

Maximum voltage 39 V

Maximum current 8.85 A

Open circuit voltage 47.4

Short circuit current 9.47

Efficiency 17.4

Temperature rating

NOCT(Nominal

Operating Cell

Temperature)

44°C (±2°C)

Temperature Coefficient

of PMAX - 0.39%/°C

Temperature Coefficient

of VOC - 0.29%/°C

Temperature Coefficient

of ISC 0.05%/°C

Maximum ratings

Operational -40°C ~ +85°C

Temperature Maximum

System Voltage

1500V DC (IEC)

1000V DC (UL)

Max Series Fuse Rating 20A

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WARRANTY

10 year Product Workmanship Warranty 30 year

Linear Power Warranty

The units used in the project are characterized by the following:

1. High power output.

2. It can increase the total energy generated as it can generate

electricity from the front and back sides.

3. The energy generated from the back can reach 25% of the

total electricity generated depending on the inclination of

the solar module.

4. These units have a unique square design of intersections and

installation method works to avoid the formation of

shadows on the units. 5. These units are characterized by low LCOE by:

A- Maximizing limited space and tofu in labor cost

B - the production of electricity more than the same

measurements of the PV module as close to the production

of standard units.

6. The units used in the project can be used in a wide

application such as:

A. They can be used in public utilities installed on land,

agricultural projects, and in distillation and water

purification projects.

B. Can be used in special application such as sound barriers on highways.

C. These units are compatible with major tracking systems

available in international markets.

7. These modules have high resistance to sand, acid, and

alkalis.

Inventer

Inventeros are the most important devices in GCPV systems. It

converts DC current to AC and uses synchronized AC output to grid frequency to ensure the safety of electricity transmission to

and from the grid. This device senses instability in the grid

current and immediately closes the transfer from the network to

the system or vice versa. Hence, the efficiency of the inverter

must be high to be quick reaction and prevent the destruction of

the system. Table 3 lists the used inventer main specifications.

Table 3: Inventer used in the studied station specifications

Model SUN2000-36KTL

Manufacture Huawei Technolgies

Operating Voltage 480-850V

Unit Nom. Power 36 kW

Array Soiling Losses Loss Fraction 3.0 %

Wiring Ohmic Loss Loss Fraction 0.5 % for Array (1&2)

Module Mismatch Losses Loss Fraction -0.3 %

Module Quality Loss Loss Fraction 2.0 %

Total voltage drop 2.95%

Maximum efficiency 98.8%

Max. DC Usable Power 40,800 W

Max. Input Voltage 1,100 V

Max. Current per MPPT 22 A

Max. Short Circuit Current

per MPPT

30 A

Min. Operating Voltage /

Start Input Voltage

200 V / 250 V

MPPT Operating Voltage

Range

200 V ~ 1000 V

Max. Number of Inputs 8

Number of MPP Trackers 4

Output

Rated AC Active Power 36,000 W

Max.AC Apparent Power 40,000 VA

Max. AC Active Power

(cosφ=1)

Default 40,000W; 36,000W optional

in settings

Rated Output Voltage 220V / 380V, 230V / 400V, default

3W+N+PE;3W+PE optional in

settings

277V/480V,3W+PE

Rated AC Grid Frequency 50 Hz / 60 Hz

Max. Output

Current(@380V/400V/480V)

60.8 A/57.8A/48.2A

Adjustable Power Factor 0.8 LG ... 0.8 LD

Max. Total Harmonic

Distortion ＜3%

Protection

Input-side Disconnection

Device

Yes

Anti-Islanding Protection Yes

DC Reverse-Polarity

Protection

Yes

PV-array String Fault

Monitoring

Yes

DC Surge Arrester Type II

AC Surge Arrester Type II

Insulation Monitoring Yes

Residual Current Detection Yes

Communication

Display LED Indicators

USB / Bluetooth +APP Yes

RS485 Yes

PLC Yes

Fast Ethernet Optional

General

Dimensions （W×H×D） 930 ×550 ×260 mm

Weight 55 kg

Operation Temperature

Range -25 °C ~ 60 °C

Cooling Natural Convection

Max. Operating Altitude

Without Derating

4,000 m

Relative Humidity 0 ~ 100%

DC Connector Amphenol H4

AC Connector Waterproof PG Terminal + OT

Connector

Protection Rating IP65

Internal Consumption at

Night

< 1 W

Topology Transformerless

The wiring system is an important part of the GCPV system.

The wires exposed to two heating sources, the first is the wire resestance to electricity flow and the second is the solar

radiation and ambient air temperature. Increasing ambient air

temperature and exposing to high solar radiation as in Oman

climates will increase the resistivity of the wire to electricity

flow. As for the wiring used in the system, Table 3-4 lists its

details.

In grid-connected PV systems, the electricity generation system

is only allowed to connect to the public grid after the connection

conditions, which vary from country to country, are met. This

difference is caused by the voltage as the voltage in the country

where the PV system is connected to the network vary

according to such country. The most important conditions for the connection between the generating station and the grid are

that the frequency of the electric current should be within the

specified tolerance ranges. Protection devices are used to

protect the system and the network from many problems

resulting from generation or frequency. The protection devices

organize adjustable measuring channels separately for

International Journal of Computation and Applied Sciences IJOCAAS Vol. 7, Issue 2, OCTOBER 2019

481

protection against low voltage or rise-in-voltage, and protects

from decrease in the frequency or increase the frequency. The

security device must meet the requirements of static and

dynamic network monitoring.

VMD460-NA is used to protect the system and the network and

to moitore the feed power from the PV system to the grid. In grid-connected PV power plant systems, voltage and frequency

monitoring relays such as VMD460-NA should be used to

protect the system and protect the grid from CHPs, wind,

hydropower, and photovoltaic systems that feed energy into the

grid. If the voltage changes to an unacceptable level such as a

high increase or a significant decrease in frequency values, then

the task of VMD460-NA is to disconnect the PV system from

the distributed grid using a coupling switch. This device tracks

and monitors voltage and frequency. This device is connected

and installed directly into the central dashboard. This VMD460

device uses a separate NA connection for the mains supply.

Figure 3-9 represents a photo of the protection VMD460 device.

E) PV plant performance analysis

To analyze the grid connected PV system, the following

equations are used:

1. Array yield (YA)

The result of this equation is an assessment of the performance

of the PV module based on its electricity output. In this

equation, the productivity of the PV array is compared with the

nominal productivity of the electricity generated from the array.

𝑌𝐴 =𝐸𝑃𝑉

𝑃𝑛𝑜𝑚

Where: EPV represnts the electricity generated by the array.,

and Pnom represents the nominal productivity of the array.

2. System yield (YS)

System yield is defined as the ratio of the energy output from

the inverter (EAC) to the nominal energy of the PV array used.

𝑌𝑆 =𝐸𝐴𝐶

𝑃𝑛𝑜𝑚 h/d

3. Reference yield (YR)

The reference yield is defined by the ratio of solar radiation intensity (H) to solar radiation intensity under STC conditions

(G = 1000 W/m2).

𝑌𝑅 =𝐻

𝐺𝑆𝑇𝐶 h/d

4. Corrected reference yield (YCR)

This equation gives a correction to the reference yield due to

the effect of temperature on the working PV module

𝑌𝐶𝑅 = 𝑌𝑅(1 − 𝛾(𝑇𝐶 − 𝑇0)) h/d

Where: γ represents the coefficient of temperature for the

maximal power, TC : the module temperature, T0: the module

temperature in STC conditions (25°C).

5. Thermal energy losses (Etherm)

The equation represents the losses in PV module performance resulted from the temperature effect.

𝐸𝑡ℎ𝑒𝑟𝑚 = 𝐸𝑃𝑉(1 −1

(1−𝛾(𝑇𝐶−𝑇0)) MWh

6. DC performance ratio (PR)

The result of this equation is useful when comparing the

productivity of different PV systems connected to the grid at

different locations. It represents the proportion of useful

electricity generated divided by the energy that is supposed to

be generated in an ideal state without any waste of energy.

𝑃 𝑅 =𝑌𝐴

𝑌𝑅× 100 %

7. Capacity factor (CF)

The result of this equation is the expression of the electrical

energy provided by the generating system. This factor is

defined as the actual ratio of AC generated to the amount of

electricity that PV arrays are supposed to generate if they

operate under optimal conditions.

𝐶𝐹 =𝐸𝐴𝐶

𝑃𝑛𝑜𝑚× 100 %

8. Array capture losses (Lc)

The result of the equation represents all losses occurring during

the operation of the solar panels array, and indicates the time required for the system to provide losses by operating at

nominal power.

𝐿𝑐 = 𝑌𝑅 − 𝑌𝐴 h/d

9. Miscellaneous capture losses

This equation represents all losses of PV modules for a variety

of reasons except losses due to overheating of the unit, such as

losses due to the accumulation of dust, contaminants and dirt on

the surface of the photovoltaic cells. Other losses can be added

such as degradation losses, diodes losses, wire losses, and shading losses.

𝐿𝐶𝑀 = 𝑌𝐶𝑅 − 𝑌𝐴 h/d

10. Thermal capture losses (Ltc)

The equation represents the losses of PV modules resulting

from the operation of these modules at higher degrees of nominal temperature under standard conditions (T0)

𝐿𝑡𝑐 = 𝑌𝑅 − 𝑌𝐶𝑅 h/d

F) Tests procedure

To analyze the performance of a grid-connected photovoltaic

power station such as Khawla Bent Al-Aharith School Station,

International Journal of Computation and Applied Sciences IJOCAAS Vol. 7, Issue 2, OCTOBER 2019

482

performance parameters such as: reference yield, array yield,

system yield, reference yield correction must be calculated and

defined. Thermal power loss can also be classified by

calculating the DC performance ratio (PR), array yield (YA),

system yield (YS) and power factor (CF). The calculation of

different capture loss parameters such as array capture losses (Lc), thermal capture losses (Ltc) and miscellaneous capture

losses (Lcm) is because they provide useful and important

information about the actual operating losses of the station.

III. RESULTS AND DISCUSSIONS

Figure 3 shows the net school electricity demand monthly. The

demand for electricity increases during the hot season

(summer), which starts from the end of March to October, except for the summer vacation. The increase in demand is

caused by air conditioners for the school halls, which are

inevitable to cool the rooms and provide comfort conditions for

teachers, students, and the rest of the school's staff. The demand

decreases during the months of November and January because

the weather in these two months is moderate in the city of Sohar

and does not need air conditioning. In December, it increases in

part because of the need for heating on some hot days.

Fig. 3: The net school electricity demand per month

Fig. 4 shows energy produced by Al-Asma'a Bint Al-Harith

School station per month. The electricity produced ranges from

16240 kW hr. in December to 26650 kW hr. in May. This

fluctuation in station electricity fluctuation referred to the

fluctuation in solar irradiance with seasons changing. Solar irradiance in its maximum value at May with moderate relative

humidity and good wind speed as well as low dusty days, all

these parameters encourage the increase in the station

productivity. As for the reason for its decrease in the winter

months, despite the fact that the temperature is very appropriate

to increase the productivity of the photovoltaic units, because

of the fog and clouds that cause misleading on the photovoltaic

cells and reduce the intensity of the solar radiation reaching

them. It is noted from Al-Asma'a Bint Al-Harith School Station

cannot meet the school's electricity needs during the months of

September and October. As for the rest of the year, it can almost satisfy the school’s demand for electricity, and its production

exceeds the need during the summer holidays (July and

September).

Fig. 4: The energy produced by Al-Asma'a Bint Al-Harith School Station per

month

Figure 5 represents the energy imported from the school per

month for Al-Asma'a Bint Al-Harith School. The school

imports high rate of electricity in September and October while

this rate reduced for minimum values at February, March, June

and July. The demand for electricity increases in hot seasons,

and when the plant’s productivity is not sufficient, the rest of

the is imported from the grid. As for the moderate seasons

where the air conditioners are turned off, the demand for

electricity decreases, and thus the electricity imported from the

network decreases. We notice here that the school station does not need additional costs after its construction except for

inexpensive cleaning works, has greatly reduced the amount of

electricity imported from the network and therefore if you

calculate the difference value in the electricity bill we will find

that the station will pay its costs in a few years.

Fig. 5: Electrical energy imported from the grid to feed Al-Asma'a Bint Al-

Harith School

Figure 6 manifests the electrical energy exported by Al-Asma'a

Bint Al-Harith School PV grid connected station to the national

network. In the days when the demand for electricity increases,

the export of electricity to the network decreases. On the days

when the demand for electricity decreases, more quantities of

the exported PV electricity are exported to the network. Some

people wonder if production is less than demand most of the year, when are the electricity exported. It should be not

forgotten that the production of photoelectric electricity takes

place from sunrise to sunset, while the school operates from

eight in the morning until two in the afternoon, after which there

will be an abundance of production with a decrease in need.

0

10000

20000

30000

40000

En

erg

y (

kW

hr)

Month

Net school demand

0

5000

10000

15000

20000

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En

erg

y (

kW

hr)

Month

Energy produced

0

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En

erg

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Energy imported from grid

International Journal of Computation and Applied Sciences IJOCAAS Vol. 7, Issue 2, OCTOBER 2019

483

Fig. 6: The energy exported to grid from Al-Asma'a Bint Al-Harith School PV

station

Figure 7 shows the station self-efficiency, which represents the

produced energy minus imported electricity from the grid

divided by electricity produced. The results reveal high self-

efficiency for the station all over the year but this efficiency

fluctuates from month to another depending on consumed

energy in the school. The final result clarifies that divinity such systems will reduce the load on the network as well as it

supplies it with excess electricity, so it is very suitable to be

distributed on all schools and government buildings in the

Sultanate of Oman.

Fig. 7: Al-Asma'a Bint Al-Harith School PV grid connected station efficiency

Figure 8 reveals the overall energy consumption and exported for the period from Aug 2018 to Aug 2019 for Al-Asma'a Bint

Al-Harith School PV grid connected station. The figure shows

that the net school demand didn’t exceed 31% while the energy

produced was 34%, energy imported from the grid was 16%

while the energy exported to the grid was 19%. These results

declare the success of establishing such station in this school as

it saved money and supported the grid with more electricity.

Fig. 8: Overall energy consumption & Export for the period from Aug 2018 to

Aug 2019 for Al-Asma'a Bint Al-Harith School PV grid connected station

Figure 9 shows the fluctuation between the daily array yield,

the reference yield, and the system yield for each month. The

daily reference yield has a direct relationship commensurate

with the average daily brightness of the sun, so it ranges from

its lowest value of 4.6 hours for January to its highest value of

7.15 hours in October. It is noted from the results included in the curves of the figure that the average daily yield of the array

and the system yield follow the reference yield trend. The

minimum daily average yield for the array (3.05 h/ d) and

average yield for the production system (2.95 h/d) varies in

January. In October, the maximum daily average yield of the

array is (5.07 h/d) and for the production system (4.94 h/d). The

results also show clear differences between the average

throughput of the array and the system throughput for all

months of the year. Such a difference should occur due to the

losses resulted from current conversion in the inverter from DC

to AC.

Fig. 9: Monthly variation of array yield (YA), reference yield (YR) and

system yield (YS) for the studied station

Figure 10 shows the results of the average monthly change of

capture losses, various capture losses, and thermal capture

losses. The array capture losses include all kinds of losses that

may occur in the process of converting sunlight into electricity

via solar cells. These losses range from the lowest in January 1.7 h/d to the maximum in July 2.40 h/d. Various capture losses

have many causes such as shading, wire loss, accumulation of

dust and pollutants, loss of diodes, and the effect of aging on

displays. Losses can be determined, but it is very difficult to

determine the exact nature of them. These losses are lowest in

June (1.55 h/d), to reach their maximum values in July (2.19

h/d). For thermal capture losses they are directly proportional

to the change in module temperature. Therefore, we find that

the highest values of thermal capture loss are in the warm

months of the year. Heat capture losses range from the lowest

value (0.04 h/d) in January to the maximum value (0.3 h/d) in

September.

0

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10000

15000

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25000

En

erg

y (

kW

hr)

Month

Energy exported to grid

0

50

100

150

200

250

300

Eff

icie

ncy (

%)

Month

Self Efficiency2

3

4

5

6

7

8

Yeil

d (

h/d

)

Month

Array Yield

Reference Yield

System Yield

International Journal of Computation and Applied Sciences IJOCAAS Vol. 7, Issue 2, OCTOBER 2019

484

Fig. 10: Monthly variation in array capture losses (Lc), miscellaneous capture

(Lcm) losses and d thermal capture losses (Ltc) for the studied station

Figure 11 shows the average percentage of daily direct current

performance and its monthly change, this average changes with

the change of months, so we find it, for example, in the month of January, it is at the minimum level of 63.59%. The maximum

value of the monthly change in the average daily direct current

performance is 73.56%, which is achieved in June.

Fig. 11: Monthly variation of performance ratio (PR) for the studied station

Figure 12 shows the relationship between the average daily

power factor and the change in months of the year. The lowest

daily average power factor value is 11.74% in January, and the

maximum value in October is 20.54%. The results of the figure

show that the capacity factor is of small values during the winter

season (December, January and February) and increases during

the remaining months of the year (the warmest). From a

comparison of Figures 9 and 10, a relationship between the ratio

of DC performance and the capacity factor for the months of

the year is observed.

Fig. 12: Monthly variation of capacity factor (CF) for the studied station

Table 4 shows a summary of the performance parameters

results of the grid-connected photovoltaic system for the

Asmaa Bint Al-Hareth School in Sohar-Oman.

Table 4: The daily average performance indices of the studied

Sep Oct Nov Dec Jan Feb Mar Apr May Jun Jul Aug

YR (h/d) 6.8 7.1 6.3 5.2 4.5 5.6 7 6.7 6.6 6.5 7.1 6.5

YA (h/d) 4.6 5 4.5 3.5 2.8 3.6 5 4.6 4.5 4.7 4.6 4.15

YS (h/d) 4.5 4.8 4.4 3.5 2.7 3.55 4.7 4.5 4.4 4.6 4.5 4.1

Lc (h/d) 2.15 2 1.6 1.65 1.7 1.89 2.1 2.4 2.3 1.8 2.3 2.4

Lcm (h/d) 2 1.85 1.6 1.7 1.7 2 2.1 1.9 2.15 1.6 2.2 2.12

Ltc (h/d) 0.4 0.28 0.13 0.07 0.05 0.07 0.17 0.24 0.21 0.21 0.22 0.22

PR (%) 67 71 73 67 64 64 71 67 66 74 67 64

CF (%) 19 21 19 15 12 15 20 19 18 20 19 17

Table 5 lists some performance results from literatures for grid

connected PV stations in various countries compared with

recent study results. The comparison between photovoltaic

power plants operating in different regions of the world may be

partly unfair because of their connection to the surrounding

environment [39]. The analysis of the current system was based

on its location in the Omani city of Sohar, which is characterized by a high humidity atmosphere most days of the

year with high temperatures. Also, the wind speed in this region

is from 3 m/s to 5 m/s [40]. The PV module manufacturing

technique, the system connections style and the array

arrangement play an important role in the system's

performance. The following parameters are the most

influencing the performance of any solar cell system:

performance ratio, (PR), array return (YA), and system return

(YS) [41]. In Table 5 the comparison is made on the basis of

these parameters for different regions. The current study results

listed in the table came close to the results of a station study in

Greece [42], despite the fact that the both sites have a mixed

climate. The two existing stations in Trieste (Italy) and Dublin

(Ireland) [43, 44] were in cold weather compared to the current

study, and despite this, the yields of the two systems mentioned

were lower than the readings recorded in the current study. While it appears from the table that the stations in References

[45, 46] were established in arid environments produced higher

yields than the current study. Here we must show that the

sunshine period in Oman is the highest, as it falls within the

solar belt. The solar radiation intensity of Oman is very high for

the above reason, which causes losses due to the high

temperature of the PV unit. We should also mention that there

are losses that occur as a result of the accumulation of dust,

which causes deterioration in the productivity of solar panels.

0

0.5

1

1.5

2

2.5

3C

ap

ture L

oss

es

(h/d

)

Month

Lc

Lcm

Ltc

58

60

62

64

66

68

70

72

74

PR

(%

)

Month

0

5

10

15

20

25

Cap

acit

y F

acto

r (

%)

Month

International Journal of Computation and Applied Sciences IJOCAAS Vol. 7, Issue 2, OCTOBER 2019

485

Table 5: Comparison of performances parameters of PV grid connected systems installed in various countries and the recent study

Ref. [41] Ref. [42] Ref. [43] Ref. [44] Ref. [45] Ref. [46] Recent study

Location Trieste-

Italy

Abu-Dhabi-

UAE

Kuwait Ireland Greece Mauritania Sohar-Oman

Climate conditions Humid

subtropical

Arid Humid

subtropical

Oceanic

(marine)

Temperate

Mediterranean

Arid Humid

subtropical

PV technology HIT Polycrystalline

Si

CIGS Monocrystalline

Si

Polycrystalline

Si

a-Si n la-S Monocrystalline

Si

Station Capacity (kWp) 17.94 36 85.05 1.72 171.36 954.72 150

PR (min/mean/max) % 82/898/95 - 70/-/85 79.3/81.5/84.4 57/67/73 63.6/68/74 63/68/73

YS (min/mean/max) (h/d) - 4.5/-/5.6 -/4.5/- 1.31/-/3.42 1.95/-/5.7 2.95/4.27/4.94 2.8/4.17/4.9

YA (min/mean/max) (h/d) 1.4/3.84/5.5 - - 1.44/-/3.42 - 3.05/4.39/5.07 2.9/4.2/5

IV. CONCLUSSIONS

Solar cells are a good alternative to using fossil fuels to produce

electricity. This technology has spread globally and become

popular in use. Connecting photovoltaic power stations to the

network means taking advantage of two basic things: producing

clean electricity, taking the need from it, and sending the

surplus to the network. In times when PV production decreases as a result of partial shading due to dust storms, clouds or fog,

the grid can be used to supply the school's electricity needs.

The performance of a grid-connected photoelectric power

station installed at Asmaa Bint Al-Hareth School in Sohar city

of Oman was analyzed in this project. During the study, weather

and system performance variables were monitored and

recorded. Monitoring results were analyzed, and these results

were compared with the results of other studies with other

similar systems established in different places in the world.

The analysis that we did in this study was done using

performance indicators such as: Average daily reference yield, daily yield, system yield, DC performance ratio, power factor,

capture losses, various capture losses and thermal losses

capture. The analysis of the results showed that the losses

fluctuate from the lowest value to the highest. For example, the

average daily reference yield was between 4.6-7.15 (h/d), the

daily yield from 3.05-5.07 (h/d), and the system yield was

11.74-20.54 (h/d). The DC performance ratio was ranged from

64% to 74% while the capacity factor has reached 11.74% to

20.5%.

The group of capture losses ranged from 1.55 to 2.19 (h/d), and

the capture losses for the system were 0.04-0.3 (h/d). the

analyzes of the results show that the PV power plant has a kind of seasonal performance, and here we mean the performance

conditions to change from month to month according to the

seasonal environmental conditions. It was also observed that the

productivity of the plant depends on the period of sunshine. In

the spring months, the plant gives values for the average daily

energy production, followed by the summer and autumn

months. In the winter, values of average daily energy

production are at their lowest due to the partial shading

resulting from clouds and fog. It has been proven in the current

study that such systems depend mainly on their performance on

the environmental conditions of the area in which they were established, the period of sunshine, and the size of the

photovoltaic power grid connected station. The study has

proven that such systems are suitable for operation in Omani

climates and it is a successful choice for electricity production

on the national and personal levels.

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