Revista de Ciencias Tecnológicas (RECIT). Volumen 3 (1): 10-22

Revista de Ciencias Tecnológicas (RECIT). Universidad Autónoma de Baja California ISSN 2594-1925

Volumen 6 (3): e144. Julio-Septiembre, 2023. https://doi.org/10.37636/recit.v6n3e144

ISSN 2594-1925

Research article

Effects of wind speed and temperature on economics

and environmental impact assessment of different

solar PV systems in Malaysia

Efectos de la velocidad del viento y la temperatura en la

economía y la evaluación del impacto ambiental de diferentes

sistemas solares fotovoltaicos en Malasia

Tijani Alhassan Salami , Ariffin Salbiah

School of Mechanical Engineering, College of Engineering, Universiti Teknologi MARA, 40450 Shah Alam,

Selangor, Malaysia

Corresponding author: Tijani Alhassan Salami, School of Mechanical Engineering, College of Engineering,

Universiti Teknologi MARA, 40450 Shah Alam, Selangor, Malaysia. E-mail: alhassanuitm@gmail.com. ORCID:

0000-0002-0954-718X

Received: July 19, 2021 Acepted: July 27, 2023 Published: August 5, 2023

Abstract. This study aims to analyse the effect of temperature and wind speed on the performance of different

types of photovoltaic (PV) systems at a different state in Malaysia and how it affects the economics and

environmental impact assessment in the present year of 2018 as well as future years in 2030 and 2040. Three types

of grid-connected solar PV modules namely Mono-Crystalline, Poly-crystalline, and Thin Film were selected to be

implemented in different cities of Shah Alam, Chuping, Alor Setar, Ipoh and Kota Kinabalu. A mathematical model

was adopted to estimate the performance characteristics of the solar PV modules. Based on the data in the present

year, the highest power output produced by the Mc-Si module for Alor Setar city is given by 33.40 MWh/year while

the lowest amount of power output provided by this PV panel is about 28.18 MWh/year in Shah Alam. Furthermore,

an area of 144 m2 for the Mono-Crystalline PV module can satisfy the total energy requirement by the resident as

it was the most profitable to be implemented compared to Poly-crystalline and Thin Film. The findings of this study

can serve as important information on the economic viability of installing PV systems in the selected cities in

Malaysia.

Keywords: Temperature; Wind speed; Solar radiation; PV performance.

Resumen.- Este estudio tiene como objetivo analizar el efecto de la temperatura y la velocidad del viento en el

rendimiento de diferentes tipos de sistemas fotovoltaicos (PV) en un estado diferente de Malasia y cómo afecta la

evaluación del impacto económico y ambiental en el presente año de 2018, así como en el futuro. años en 2030 y

2040. Se seleccionaron tres tipos de módulos fotovoltaicos solares conectados a la red, a saber, monocristalinos,

policristalinos y de película delgada, para implementarlos en diferentes ciudades de Shah Alam, Chuping, Alor

Setar, Ipoh y Kota Kinabalu. Se adoptó un modelo matemático para estimar las características de rendimiento de

los módulos fotovoltaicos solares. Según los datos del año en curso, la producción de energía más alta producida

por el módulo Mc-Si para la ciudad de Alor Setar es de 33,40 MWh/año, mientras que la producción de energía

más baja proporcionada por este panel fotovoltaico es de aproximadamente 28,18 MWh/año en Shah Alam.

Además, un área de 144 m2 para el módulo fotovoltaico monocristalino puede satisfacer el requerimiento total de

energía del residente, ya que fue el más rentable de implementar en comparación con el policristalino y la película

delgada. Los hallazgos de este estudio pueden servir como información importante sobre la viabilidad económica

de instalar sistemas fotovoltaicos en las ciudades seleccionadas de Malasia.

Palabras clave: Temperatura; Velocidad del viento; Radiación solar; Rendimiento fotovoltaico.

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1. Introduction

Over the last decades, there has been a

significant increase in the demand for fossil

fuels for energy production to meet the

energy requirement for industrial and

domestic applications. The continuous

exploration and ever-growing demand for

these fossil fuels have led to the emission of

toxic materials such as carbon dioxide into

the atmosphere. Consequently, this has led

to global warming [1], [2].

A growing body of literature recognises the

threat posed by the depletion of fossil fuel

such as natural gas, coal, and oil. These

fuels also contribute significantly to global

carbon dioxide and climate change [3], [4].

An obvious solution to curb the escalation

of the ongoing depletion of global fossil fuel

and environmental pollution is to promote

the adoption of sustainable and renewable

energy technologies; this concern has

attracted extensive attention. Renewable

energy can be produced from natural

resources such as solar, wind, biomass and

geothermal [5]. Among these renewable

energy technologies, solar energy is the

fastest-growing technology in Malaysia [3].

The potential application areas of solar

energy are photovoltaic (PV) technology for

electrical power production and solar

thermal energy for thermal energy

production [6], [7]. Solar PV consists of a

semiconducting material such as silicon

which directly converts solar irradiance into

electrical energy [8]. Solar PV offers a

promising technology with several benefits

such as pollution-free and easy installation

it is therefore expected to contribute

significantly to global future sustainable

energy development [9]. It is now well

established from a variety of studies that,

climate change has a considerable effect on

renewable energy resources, for example in

the case of solar energy, wind speed, and

ambient temperature are the most important

parameters of the climate that need

considerable attention [10, 11].

In the new global economy, PV installation

has become a central issue to meet the

global energy demand and reduce emissions

caused by traditional energy resources such

as coal and natural gas [10], [11]. Therefore,

the issue of PV installation and application,

especially for domestic and industrial

applications, has received considerable

critical attention in Malaysia [12], [13]. For

example, the Government of Malaysia has

projected that by the year 2050, 11.5GW of

renewable energy capacity be installed [14].

Recently, researchers have shown an

increased interest in increasing the capacity

of PV installation, for example, the

International Energy Agency (IEA)

estimated to produce 11% of global

electricity demand through photovoltaic

(PV) by the year 2050 and this is expected

to reduce 2.3 Gt of global CO2 emission of

per year [15]. Ambient temperature has

been instrumental in our understanding of

photovoltaic module performance, and its

efficiency reduces when the ambient

temperature increases [16]. Existing

research recognises the critical role played

by ambient temperature in influencing the

performance of photovoltaic modules.

According to [16], Thin Film photovoltaic

modules are better option in hot climates

[17]. Recently investigators have examined

the effects of ambient temperature on

photovoltaic modules under Karabuk

(Turkey) climatic conditions, they conclude

that ambient temperature plays an essential

role in the performance of photovoltaic

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modules [18]. Generally, the solar

photovoltaic modules are manufactured at

standard test conditions (STC) (i.e. 1000

W/m², Air Mass 1.5 and module operating

temperature 25°C), however ambient

temperature and wind speed at a specific

location affect the performance of the

module, especially if its application is for

domestic purpose, hence the photovoltaic

module's performance changes concerning

the actual location and prevailing ambient

conditions to which they are subjected [19]–

[21]. Other literature also concluded that

increase in wind speed results in cooling the

PV through convection heat loss to the

ambient and this would increase the PV

module efficiency [22].

Since the government of Malaysia has

planned to increase the capacity of PV

energy production up to about 11% of the

country's total energy demand, it is

important to understand the performance of

PV modules at different ambient

temperatures and wind speeds of the

country. However, even though previous

research related to the performance of PV

module efficiency and economic analysis

for specific locations have been carried out,

a lot more cities have not yet been covered,

especially for domestic applications.

Therefore, this study aims to fill this gap by

investigating the effect of ambient

temperature and wind speed on the

economic and electrical efficiency

performance of different PV modules in

specific cities in Malaysia.

2. Methodology

2.1 Subsection title Proposed residential

house, load consumption and load

profile

Fig. 1 shows the proposed design of the

residential house with a grid connection PV

system and its respective predicted load.

The system comprises PV panels, DC/AC

inverter, Fuse boards, loads, and the PV

meter. As the solar radiation falls on the PV

panels, DC current is produced. The DC

current can, however, be converted into AC

current by means of an inverter which is

used to match AC requirements in

residential appliances. Any excess electrical

power that is produced can be sent to

Tenaga Nasional Berhad (TNB) grid.

Figure 1. Proposed design of residential house with

a grid-connected PV system.

All the estimated load and power

consumption by the residential house were

obtained based on the selected cities of this

study, namely, Shah Alam, Chuping, Alor

Setar, Ipoh and Kota Kinabalu. The detailed

geographical location of the chosen cities is

shown in Table 1.

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Table 1. Parameters for the selected cities

From the data collected, the total energy

consumed by the resident per day is 27.432

kWh (refer to Table 2) while 822.96 kWh

energy consumed monthly by the resident.

Fig. 2 shows the hourly energy load profile

of a residential house. It can be observed

that the maximum hourly power

consumption is 3.725 kW, which requires

the PV system to produce at least

89.4kWh/day (3.725 kW  24 hours) of

energy in order to support the power

consumed by the load. Thus, the PV system

should yield at least 32.631 MWh/year

(89.4 kWh365 days). Therefore, base on

the preliminary study, 23 kWp of PV

capacity system has been chosen based on

the size of the PV panel available in the

market that is expected to produce annual

energy of 36.364 MWh/year.

Figure 2. The hourly energy load profile

Table 2. Predicted load and power consumption

No.

Equipment

Quantity

Power rating (W)

Time usage (hour)

Energy (Wh)

Ceiling Fan

975

Television

150

1200

Air Conditioner

3500

17500

Washing Machine

500

Refrigerators

150

3600

Rice Cooker

627

Electric kettle

480

Fluorescent Lamp

100

1400

Laptop

150

10.

Electric Iron

1000

Average total daily power consumption

27432

Selected Cities

Latitude

(N)

Longitude

(E)

Altitude

(m a.s.l)

Time Zone

(UTC)

Shah Alam

3.0733

101.5185

Chuping

6.4985

100.2580

105

Alor Setar

6.1248

100.3678

Ipoh

4.5975

101.0901

195

Kota Kinabalu

5.9804

116.0735

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3. Model equations and simulation

Most previous studies have shown that solar

cells' performance varies with temperature

changes [23]. Therefore, to determine the

performance of all the three (3) types of PV

module in this study

(Monocrystalline/Polycrystalline /Thin

film), the cell temperature was estimated

using the NOCT-Standard formula as

shown below [24], [25].

( )

TT NOCT

ac 

−

+= 800

(1)

Where Tc is the PV cell temperature, Ta is

the ambient temperature, TNOCT is Nominal

Operating Cell Temperature. The solar

radiation, I(t) is measured at 1000W/m2

while the irradiance is fixed at 800W/m2.

Once the PV cell temperature is obtained, it

can be used to determine the efficiency of

the solar PV modules [27, 28].

( )

 

refcrefrefc TT −−=



(2)

All the parameters of ref, βref and Tref are

provided by the PV manufacturer [24].

Equation (3) can be used to determine the

wind speed, where vw= 1 m/s is the local

wind speed close to the module while vf is

the wind speed measured 10 meters above

the ground [24].

5.068.0 −= fw vv

(3)

The nominal power of the PV panel has

been set at 23 kWp as available in the

market. Other parameters that were used for

the simulation are shown in Table 3.

Table 3. Constant parameter required

No.

Parameters

Value

Nominal power

23kWp

Module type

Standard

PV panel Technology

Monocrystalline/Po

lycrystalline/Thin

film

Mounting Disposition

Facade or tilt roof

Ventilation property

Ventilated

Tilt Angle

30˚

Azimuth Angle

0˚

3.1 Economics and Environmental Impact

Assessment

3.1.1 Economics models

Based on this case study, the economic

profitability of the PV systems can be

calculated by using three key indicators

namely, Payback Period (PP), Net Present

Value (NPV) and Life Cycle Cost (LCC).

i. Payback period

The payback period is the number of years

it takes for the energy-cost saving to recover

the initial investment costs of a system [26].

periodperflowinCash

investmentCapital

PeriodPayback =

(4)

ii. Net Present Value (NPV)

Net present value is the difference between

the present value of cash flows into and

from a project [29, 30]. Thus, the higher the

amount of NPV obtained, the greater is the

financial advantages.

( ) ( ) ( )

SNPV +

+−= 1

.....

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( )

=+

+−= N

S11

(5)

From the equation, Q is the net cash flow, S

is the cost of the PV system and N is the life

cycle of the PV panel that is estimated to be

21 years [27].

iii. Life Cycle Cost (LCC) Analysis

Life Cycle Cost (LCC) is an analysis used

to determine the cost involved in the project

that includes the cost of maintaining,

operating, owning and the project disposing

of cost.

LCC=CPV+Cinv+Cins+CO&M (6)

Where CPV represents cost of PV modules,

Cinv is the inverter cost, Cins is the

installation cost, and the CO&M is the

operating and maintaining cost. Annualised

LCC analysis of the PV systems can be

calculated by the equation (7) below.

























−













−

LCCALCC N

(7)

Where i represents inflation rate, N is PV

lifetime that is 21 years, and d indicates the

discount rate. Lastly, equation (8) can be

used to determine the actual cost invested by

the owner to produce 1kWh of energy.

Unit electrical cost =

LOAD

ALCC

365

(8)

3.1.2 Environmental Model

Estimating environmental impacts

assessment of energy technologies in the

early design stage is critical [26] to address

global warming issues. United Nations

report that CO2 intensity of electricity

generation needs to drop by 80%, by 2050

[32-34]. The result from the environmental

impact assessment of PV systems can be

used to establish a comparison on how

much deployment of PV modules can save

the amount of GHG emission and predict

the potential for all cities in the future.

Table 4 shows the GHG emission factors

used in this stud

Table 4. The GHG emission factors

GHG gases product from coal power plants

Emission Factors (kg/kWh)

CO2

0.97

SO2

0.00124

NOx

0.00259

Ash

0.068

4. Results and Discussion

4.1 Solar radiation data for temperature

Fig. 3 shows the effect of solar radiation on

ambient temperature for the five selected

cities. The simulation was conducted to

forecast the solar radiation for all the cities

in the present year (2018) and the future

year of 2030 and 2040 [35, 36]. Based on

Fig. 3, it can be said that high global

radiation leads to high ambient temperature.

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The amount of global radiation received by

the PV panel in 2018, 2030 and 2040 is

relatively the same with only a slight

difference. As the year keep increasing, the

ambient temperature also increases with

increases in global radiation. The city that

gained the highest global radiation is

Chuping as shown in Fig. 3(b). In the

present year and year 2030, Chuping

acquired about 180W/m2 of global radiation

monthly with ambient temperatures of

29.5C and 29.7C, respectively). In 2040,

an ambient temperature of 29.8C that

corresponds to global radiation of 181W/m2

is expected. It can also be observed from

Fig. 3(a) that Shah Alam obtained the

lowest amount of monthly global radiation

of 117W/m2 in the present year and future

year of 2030 and 2040, this corresponds to a

progressive increase in ambient temperature

from 26.8C (2018) to 27C (2030) and to

28.2C (2040) respectively.

Figure 3. Global radiation versus ambient temperature.

(a): Shah Alam

(b): Chuping

(c): Alor Setar

(d): Ipoh

(e): Kota Kinabalu

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4.2 Solar radiation data for wind speed

Figure 4 shows the forecasted data for global

radiation that is expected to be received by the PV

panel at various wind speeds. The forecasted data of

global radiation for the present year, the year 2030

and the year

2040 for all five (5) cities were obtained through

simulation. It can be observed from Figure 4 that

there is a fluctuation in the amount of global

radiation acquired as the wind speed increases for all

the cities. Among all the selected cities, however,

Chuping is the city that received the highest amount

of global radiation of 180W/m2 in the present year

and year 2030, while in the year 2040, the amount of

global radiation increased slightly to 181W/m2 at the

same wind speed of 1.7 m/s. Besides, Shah Alam also

recorded the lowest monthly global radiation of only

117W/m2 at 2.6 m/s wind speed for all the present

year and future years of 2030 and 2040 as shown in

Fig. 4(a). Therefore, it can be concluded that the

higher wind speed received corresponds to the least

amount of global radiation.

(a): Shah Alam

(b): Chuping

(c): Alor Setar

(d): Ipoh

(e): Kota Kinabalu

Figure 4. Global radiation versus wind speed

4.3 Effect of temperature on the PV

performance

Figure 5. PV module temperature versus ambient

temperature

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Figure 5 shows that, there is direct correlation

between the ambient temperature and the PV module

temperature, as the ambient temperature increases,

the PV module temperature also increases. The thin

film module obtained the highest module

temperature compared to polycrystalline and mono-

crystalline modules. The efficiency of the PV

module has been estimated using equation (2). It is

shown that, as the module temperature increases, it

results in a decrease in PV module efficiency (Refer

to Fig. 6). The monocrystalline PV panel produced

the highest efficiency compared to the other two (2)

types. For example, at PV module temperature of 48

C, the efficiency of monocrystalline, polycrystalline

and thin film modules are 18.60%, 13.19% and

8.29% respectively.

Figure 6. PV efficiency versus module temperature.

4.4 System simulation result

The performance of each PV module,

namely, Monocrystalline Silicon (Mc-Si),

Polycrystalline Silicone (PC-Si) and Thin

Film technologies, was determined to

identify which one is suitable to be installed

at the rooftop by residents based on the

cities selected. Each of the PV modules

produces different efficiency and power

output with respect to the global radiation

received at the location of the cities. As

shown in Fig.7, it can be clearly seen that

the mono-crystalline silicon PV panel

produces the highest power output for each

of the five selected cities throughout the

year 2018. Based on the data in the present

year, the highest power output produced by

the Mc-Si module for Alor Setar city is

given by 33.40 MWh/year while the lowest

amount of power output provided by this PV

panel is about 28.18 MWh/year in Shah

Alam. For Pc-Si module, the highest power

output for Alor Setar city is 31.52

MWh/year and the lowest power output of

26.68 MWh/year was recorded for Shah

Alam, whereas the highest power output for

thin-film module is 17.71 MWh/year which

corresponds to Chuping city, however, Shah

Alam still produced the least power output

with only 1.25 MWh/year.

Figure 7. Annual PV Panels output of each sites for

present year.

The forecasted data for the year 2030 and

2040 can be seen in Fig. 8 and Fig. 9

respectively. Both years indicate that

Chuping has the potential to produce the

highest PV power output for the Mc-Si, Pc-

Si and Thin Film PV module while Shah

Alam provided the least amount of power

output throughout the year. From the

present year until 2040, all of the output

power for the three types of PV systems

continued to increase in all of the cities

except for Ipoh and Kota Kinabalu. The

annual power output for Mc-Si panel in Ipoh

decreased slightly by about 0.04 MWh/year,

which is from 30.72 MWh/year in 2018 to

30.68 MWh/year in 2030 before it rises

back to 30.79 MWh/year with an increase in

power output of 0.11 MWh/year in 2040.

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Lastly, for Kota Kinabalu, the Pc-Si module

shows an increase of 0.07 MWh/year from

2018 to 2030 before it decreases to 0.11

MWh/year in 2040 whereas the thin film

panel shows a rapid increase from 1.44

MWh/year in the present year to 17.31

MWh/year in 2030 before it slightly

decrease to 17.25 MWh/year in 2040. To

recapitulate, the mono-crystalline silicon

system is the most efficient PV panel as it

produced the highest PV power output

compared to the other PV system. Thus,

Chuping proved to be the best location to

install the PV panel as it received the highest

amount of solar radiation throughout the

present year and in the future also. It can be

concluded that an increase in solar radiation

will increase the PV power output and thus

results in a better performance.

Figure 8. Annual PV Panels output of each sites for

the year 2030.

Figure 9. Annual PV Panels output of each site for

the year 2040.

4.5 Economics impact Assessment result

4.5.1 Payback Period (PP)

Figure 10. Payback period of the selected cities

The payback period is the number of years

the energy-cost saving takes to recover the

initial investment costs of a system [26].

This payback period has been determined

using equation (4). The initial investment

cost for the monocrystalline is Malaysian

Ringit (RM), RM 193,750.00, and RM

190,952.80 for polycrystalline while the

cost for thin-film is RM 180,430.00. The

shortest time taken to regain the initial cost

is about 5 years for monocrystalline panels

in the city of Chuping and Alor Setar as

shown in Fig. 10 above. Both cities

provide the highest amount of PV power

output and thus the time required to pay

back the investment cost will be shorter.

Plus, the thin-film panel results in the

longest time taken to obtain the initial

investment cost for all five cities. Based on

the graph, it takes 11 years to get back the

installation cost for Shah Alam city as it

proves that the PV power output of thin-

film module provides the least amount

compared to monocrystalline and

polycrystalline silicon modules. The

payback calculation for the present year

and for 2030 and 2040 results in almost the

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same amount with relatively small

changes which does not significantly

affect the payback time and thus only the

present year data is shown in Fig.10 above.

Through this payback calculation, the

residents can predict the time taken to

regain their investment cost and choose the

suitable PV module to be implemented at

their location whether it is beneficial or not

for them to invest.

Table 3. Net Present Value (NPV) for all of the selected cities.

Site

Year

Monocrystalline

Polycrystalline

Thin Film

Shah Alam

present

RM 141,177.83

RM1 26,113.30

RM 31,432.52

2030

RM 143,419.58

RM 128,228.14

RM 440.81

2040

RM 143,990.01

RM 128,767.17

RM 79.96

Chuping

present

RM 200,551.42

RM 182,312.98

RM 30,060.34

2030

RM 202,744.77

RM 184,400.24

RM 31,235.48

2040

RM 203,172.60

RM 184,793.89

RM 31,457.89

Alor Setar

present

RM 201,953.31

RM 183,645.82

RM 4,393.87

2030

RM 201,261.69

RM 182,994.10

RM 30,442.54

2040

RM 202,288.40

RM 183,961.05

RM 30,987.30

Ipoh

present

RM 171,352.31

RM 154,676.31

RM 18,012.99

2030

RM 170,828.97

RM 154,181.52

RM 14,195.13

2040

RM 172,155.22

RM 155,442.19

RM 14,905.31

Kota Kinabalu

present

RM 190,615.92

RM 172,913.13

RM 9,442.25

2030

RM 191,549.99

RM 173,803.05

RM 25,258.75

2040

RM 190,195.21

RM 172,519.57

RM 24,535.65

On the other hand, the thin film module

was not preferred and therefore not

suitable to be invested into by the resident

since the NPV results shown are very

small which indicated that this PV module

produced a very low value of the cash flow

for 21 years. Thus, from this analysis, it

can be said that the forecasted data for the

three (3) PV systems is expected to

increase in the year 2030 and 2040 except

that for Ipoh and Kota Kinabalu where

there is a slightly increase and decrease

trend.

4.5.2 Net Present Value (NPV)

The Net Present Value (NPV) results for

the cash flow were estimated using Excel

and the calculation was done using

equation (5). Cash flow takes into account

the total amount of incomings and

outgoings cash of the operating activities

of an organisation. Table 3 below shows

the NPV for the three (3) types of PV

systems used in this study, the NPV is used

to determine the profitability of the three

(3) PV systems at each of the selected

cities. Based on the tabulated data shown,

the monocrystalline PV panel gives the

highest amount of NPV for all five (5)

selected cities. Thus, monocrystalline is

the best PV module to be installed

especially at Chuping, this is because the

higher the amount of NPV obtained the

higher the profit margin which eventually

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translates into a greater financial benefit

for the residents.

4.5.3 Life Cycle Cost Analysis (LCCA)

Life Cycle Cost (LCC) is an analysis that

is used in order to determine the cost

involved in the project which includes cost

of maintaining, operating, owning and the

project disposing cost. By using equation

(6) and the related parameter needed, the

life cycle cost (LCC) for all three (3) types

of PV systems were obtained as tabulated

in Table 4. The highest life cycle cost

(LCC) is the Monocrystalline PV Panel

with RM 193,750.00, followed by the

Polycrystalline PV panel which is RM

190,952.80 whereas the LCC for Thin

Film PV Panel is RM 180,430.00. Next, to

find the annualised LCC (ALCC) value,

equation (7) was used. The ALCC for

Monocrystalline PV Panel is RM

15,335.08 while for Polycrystalline PV

Panel is RM 15,113.68 and for Thin Film

PV Panel is RM 14,280.81. Lastly,

equation (8) is the formula that was used

to calculate the unit cost of electricity for

1kWh. From this calculation, the actual

cost invested by the owner to produce 1

kWh of energy can be estimated. Based on

the result of the analysis, the actual cost for

producing 1 kWh of electricity for

Monocrystalline is RM 1.00 and

Polycrystalline is RM 0.99 while for Thin-

film is RM0.93. Even though the Thin

Film PV Panel provides a higher profit

margin, however, it is still not

recommended for the residents to

implement the thin-film module because

of its higher NPV value.

Table 4. The cost involved in the Life Cycle Cost Analysis (LCCA).

Parameters

Mc-Si

Pc-Si

Thin Film

Cost

Cost for

23 kWp

(RM)

Cost

Cost for

23 kWp

(RM)

Cost

Cost for

23 kWp

(RM)

PV Panel

RM 13.90

/Wp

166,800

RM 13.90 /Wp

164,280

RM13.90 /Wp

154,800

Installation

10% PV cost

16,680

10% PV cost

16,428

10% PV cost

15,480

Inverter

RM 3.91 /W

8602

RM 3.91 /W

8602

RM 3.91 /W

8602

Operation &

maintenance

cost

1% PV Cost

1668

1% PV Cost

1642.80

1% PV Cost

1548

TOTAL

RM 193 750

RM 190 952.80

RM 180 430

4.6 Environmental Impact Assessment

Result

The environmental impact assessment is

very important for the owner to consider in

the investment of PV systems to make a

comparison on the amount of GHG

emission that can be saved with the

deployment of solar PV and to predict the

potential for all the cities in the future. The

analysis shown in Fig. 12 shows that Alor

Setar city has the potential to save a

considerable amount of GHG emission per

year followed by Chuping, Kota Kinabalu,

and Ipoh while Shah Alam saves the least

amount. It can be seen that the

Monocrystalline is the best PV panel to be

chosen by the residents as it can save the

highest amount of GHG emission compared

to the other PV types.

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Revista de Ciencias Tecnológicas (RECIT). Volumen 6 (3): e144

(a): Shah Alam

(b): Chuping

(c): Alor Setar

(d): Ipoh

(e): Kota Kinabalu

Figure 11. Total avoided amount of GHG emission

for all selected cities

Fig. 11(c) confirms that, in relation to the

present year and by using Monocrystalline

PV panel, Alor Setar City can save up to

about 34.69 tonne (34689.81 kg) of GHG

followed by Polycrystalline PV panel which

can also save up to 32.84tonne (32839.65

kg) of GHG while the Thin Film can save

15.43 tonne (15432.42 kg) of GHG. The

forecasted data for the future year 2030,

showed that there is a slight decrease in the

amount of GHG emission that can be saved

by the Mc-Si module which is about 0.061

tonne (60.63 kg) from 34.69 tonne to 34.63

tonne. However, the Pc-Si module showed

a rapid decrease of about 14.18 tonne

(14180.47 kg) from 32.84 tonne (32839.65

kg) to 18.66 tonne (18659.18 kg) GHG

emission while the thin-film module

resulted in an increasing amount of GHG

emission that can save about 3.054tonne

(3053.98 kg) from 18486.4 kg in 2018 to

15432.42 kg in 2030. In the year 2040, both

Alor Setar and Chuping cities are predicted

to save the highest amount of GHG

emissions for all three types of PV panels.

The Mc-Si, Pc-Si and thin-film panels each

can save up to about 34.72 tonne (34719.19

kg) 32.87 tonne (32867.28 kg)

and18.53tonne (18534.16 kg) GHG

emission respectively. The city with the

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Revista de Ciencias Tecnológicas (RECIT). Volumen 6 (3): e144

least amount of avoidable GHG emissions

per year is Shah Alam as shown in Figure 9

(a). In the present year of 2018, all three (3)

types of PV panels for Shah Alam save the

least amount of GHG emission compared to

the other cities. However, the amount of

GHG emission that can be avoided by each

of the PV Panels keeps increasing from the

present year to 2030 until 2040. This

showed that, as the year increases, the

amount of GHG emission saved by all the

PV panels in Shah Alam will also increase.

At last, it can be said that the site of Chuping

and Alor Setar is the best location compared

to the other cities as they can avoid the

highest level of GHG emission in the

present year and also in the future year.

5. Conclusion and Recommendation

Throughout this study, the effect of

temperature and wind speed on the

performance of the three (3) types of PV

panels has been analysed. It shows that an

increase in temperature decreases the

efficiency of the PV module. The increase

in PV panel temperature was due to high

solar radiation that leads to high ambient

temperature with low wind speed. This

paper also has simulated the economics and

environmental impact assessment for all

three (3) types of PV systems at the five (5)

selected cities in Malaysia. Based on the

research, it was found that Monocrystalline

silicon PV panel is suitable to be invested in

by the residents especially as it provides the

best result for all the selected cities

compared to the other PV panels. Although

the initial investment cost for a

Monocrystalline module is a bit higher,

however, it proves to produce the highest

annual PV power output and the time taken

to regain the initial cost also is the shortest

compared to the other two (2) systems.

Furthermore, the Monocrystalline PV

module only required an area of 144 m2 to

satisfy the total energy requirement by the

resident compared to 153 m2 area needed by

the Polycrystalline panel while Thin Film

PV panel required about 166 m2 area.

Of all of the five (5) selected cities, Chuping

has been the city with the highest potential

to install the PV system whether in the

present year or even in the future year since

the city received the highest amount of

global radiation, and it gives the best result

in terms of environmental and economic

impact assessments. As a recommendation,

many environmental factors affect the

performance of solar PV panels apart from

temperature and wind speed. Thus, the

study related to other factors such as

humidity and dust deposition effects should

be considered in more detail so that the solar

PV panel can provide the highest efficiency.

Also, many approaches such as

mathematical, statistical modelling and

experimental can be used for the analysis.

Acknowledgements

There was no financial support for this

work, though the Authors are grateful to

Faculty of Mechanical Engineering,

Universiti Teknologi Mara for providing

facilities to carry out the research.

6. Authorship acknowledgements

Tijani Alhassan Salami: Original Idea;

conceptualization; Methodology; Review

first draft; Review and editing; Project

administration; Review final draft. Ariffin

Salbiah: Investigation; simulation;

Analysis of data; Writing first draft; Review

final draft.

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Revista de Ciencias Tecnológicas (RECIT). Volumen 6 (3): e144

References

[1] T. Fujisaki, "Evaluation of Green Paradox: Case

Study of Japan," Evergreen, vol. 5, no. 4, pp. 26-31,

2018, https://doi.org/10.5109/2174855

[2] K. Marzia, M. F. Hasan, T. Miyazaki, B. B. Saha,

and S. Koyama, "Key factors of solar energy

progress in Bangladesh until 2017," Evergreen, vol.

5, no. 2, pp. 78-85, 2018,

https://doi.org/10.5109/1936220

[3] A. M. K. See, K. Mehranzamir, S. Rezania, N.

Rahimi, H. N. Afrouzi, and A. Hassan, “Techno-

economic analysis of an off-grid hybrid system for a

remote island in Malaysia: Malawali island, Sabah,”

Renew. Sustain. Energy Transit., vol. 2, no.

September 2021, p. 100040, 2022,

https://doi.org/10.1016/j.rset.2022.100040

[4] A. Dajuma, S. Yahaya, S. Touré, A. Diedhiou,

and R. Adamou, "Sensitivity of Solar Photovoltaic

Panel Efficiency to Weather and Dust over West

Africa : Comparative Experimental Study between

Niamey ( Niger ) and Abidjan ( Côte d ' Ivoire )," pp.

123-147, 2016,

https://doi.org/10.4236/cweee.2016.54012

[5] M. B. Ali, S. A. A. Kazmi, S. N. Khan, and M. F.

Abbas, "Techno-economic assessment and

optimization framework with energy storage for

hybrid energy resources in base transceiver stations-

based infrastructure across various climatic regions

at a country scale," J. Energy Storage, vol. 72, no.

July, 2023,

https://doi.org/10.1016/j.est.2023.108036

[6] E. Foster, M. Contestabile, J. Blazquez, B.

Manzano, M. Workman, and N. Shah, "The

unstudied barriers to widespread renewable energy

deployment: Fossil fuel price responses," Energy

Policy, vol. 103, no. November 2016, pp. 258-264,

2017, https://doi.org/10.1016/j.enpol.2016.12.050

[7] A. Al Shehri, B. Parrott, P. Carrasco, H. Al Saiari,

and I. Taie, "Accelerated testbed for studying the

wear , optical and electrical characteristics of dry

cleaned PV solar panels," Sol. Energy, vol. 146, pp.

8-19, 2017,

https://doi.org/10.1016/j.solener.2017.02.014

[8] E. Kabir, P. Kumar, S. Kumar, A. A. Adelodun,

and K. Kim, "Solar energy : Potential and future

prospects," vol. 82, no. October 2017, pp. 894-900,

2018, https://doi.org/10.1016/j.rser.2017.09.094

[9] S. Basnet, K. Deschinkel, L. Le Moyne, and M.

Cécile Péra, "A review on recent standalone and grid

integrated hybrid renewable energy systems: System

optimization and energy management strategies,"

Renew. Energy Focus, vol. 46, pp. 103-125, 2023,

https://doi.org/10.1016/j.ref.2023.06.001

[10] A. Bianchini, A. Guzzini, M. Pellegrini, and C.

Saccani, "Photovoltaic/thermal (PV/T) solar system:

Experimental measurements, performance analysis

and economic assessment," Renew. Energy, vol.

111, pp. 543-555, 2017,

https://doi.org/10.1016/j.renene.2017.04.051

[11] D. Burnett, E. Barbour, and G. P. Harrison, "The

UK solar energy resource and the impact of climate

change," Renew. Energy, vol. 71, pp. 333-343, 2014,

https://doi.org/10.1016/j.renene.2014.05.034

[12] L. M. Aguiar, B. Pereira, P. Lauret, F. Díaz, and

M. David, "Combining solar irradiance

measurements, satellite-derived data and a numerical

weather prediction model to improve intra-day solar

forecasting," Renew. Energy, vol. 97, pp. 599-610,

2016, https://doi.org/10.1016/j.renene.2016.06.018

[13] O. O. Ajayi, O. D. Ohijeagbon, C. E. Nwadialo,

and O. Olasope, "New model to estimate daily global

solar radiation over Nigeria," Sustain. Energy

Technol. Assessments, vol. 5, pp. 28-36, 2014,

https://doi.org/10.1016/j.seta.2013.11.001

[14] A. Naderipour et al., "Comparative evaluation

of hybrid photovoltaic, wind, tidal and fuel cell clean

system design for different regions with remote

application considering cost," J. Clean. Prod., vol.

283, 2021,

https://doi.org/10.1016/j.jclepro.2020.124207

[15] A. Naderipour et al., "Effect of COVID-19 virus

on reducing GHG emission and increasing energy

generated by renewable energy sources: A brief

study in Malaysian context," Environ. Technol.

Innov., vol. 20, 2020,

https://doi.org/10.1016/j.eti.2020.101151

[16] S. Mekhilef, A. Safari, W. E. S. Mustaffa, R.

Saidur, R. Omar, and M. A. A. Younis, "Solar energy

16 ISSN: 2594-1925

Revista de Ciencias Tecnológicas (RECIT). Volumen 6 (3): e144

in Malaysia : Current state and prospects," Renew.

Sustain. Energy Rev., vol. 16, no. 1, pp. 386-396,

2012, https://doi.org/10.1016/j.rser.2011.08.003

[17] F. Touati et al., "Long-term performance

analysis and power prediction of PV technology in

the State of Qatar," Renew. Energy, vol. 113, pp.

952-965, 2017,

https://doi.org/10.1016/j.renene.2017.06.078

[18] P. K. Dash and N. C. Gupta, "Effect of

Temperature on Power Output from Different

Commercially available Photovoltaic Modules," J.

Eng. Res. Appl. www.ijera.com, vol. 5, no. 1, pp.

148-151, 2015.

https://api.semanticscholar.org/CorpusID:61287555

[19] M. Bilal, F. Ahmad, and M. Rizwan, "Techno-

economic assessment of grid and renewable powered

electric vehicle charging stations in India using a

modified metaheuristic technique," Energy Convers.

Manag., vol. 284, no. November 2022, 2023,

https://doi.org/10.1016/j.enconman.2023.116995

[20] E. Gedik, "Experimental Investigation of

Module Temperature Effect on Photovoltaic Panels

Efficiency Modül Sıcaklığının Fotovoltaik

Panellerin Verimine Etkisinin Deneysel Olarak

İncelenmesi," J. Polytech., vol. 19, no. 194, pp. 569-

576, 2016,

https://doi.org/10.101610.2339/2016.19.4.

[21] T. Bhattacharya, A. K. Chakraborty, and K. Pal,

"Effects of Ambient Temperature and Wind Speed

on Performance of Monocrystalline Solar

Photovoltaic Module in T .... Effects of Ambient

Temperature and Wind Speed on Performance of

Monocrystalline Solar Photovoltaic Module in

Tripura , India," no. September, 2014,

https://doi.org/10.1155/2014/817078

[22] Albani, A., & Ibrahim, M. Z. (2014). Statistical

Analysis of Wind Power Density Based on the

Weibull and Rayleigh Models of Selected Site in

Malaysia. Pakistan Journal of Statistics and

Operation Research, 9(4), 395-408.

https://doi.org/10.18187/pjsor.v9i4.580

[23] D. D. Milosavljević, T. M. Pavlović, and D. S.

Piršl, "Performance analysis of A grid-connected

solar PV plant in Niš, republic of Serbia," Renew.

Sustain. Energy Rev., vol. 44, pp. 423-435, 2015,

https://doi.org/10.1016/j.rser.2014.12.031

[24] F. Lai, J. Zhou, L. Lu, M. Hasanuzzaman, and

Y. Yuan, "Green building technologies in Southeast

Asia: A review," Sustain. Energy Technol.

Assessments, vol. 55, no. November 2022, 2023,

https://doi.org/10.1016/j.seta.2022.102946

[25] M. Almaktar, H. Abdul Rahman, and M. Y.

Hassan, “Economic Analysis Using Net Present

Value and Payback Period: Case Study of a 9kWp

Grid-Connected PV System at UTM, Johor Bahru

Campus,” Appl. Mech. Mater., vol. 818, no. January,

pp. 119–123, 2016,

doi: 10.4028/www.scientific.net/amm.818.119.

[26] C. Schwingshackl et al., "Wind effect on PV

module temperature: Analysis of different

techniques for an accurate estimation," Energy

Procedia, vol. 40, pp. 77-86, 2013,

https://doi.org/10.1016/j.egypro.2013.08.010

[27] K. K. Matrawy, A. F. Mahrous, and M. S.

Youssef, "Energy management and parametric

optimization of an integrated PV solar house,"

Energy Convers. Manag., vol. 96, pp. 377-383, 2015,

https://doi.org/10.1016/j.enconman.2015.02.088

[28] Y. Tawada, "Introduction of the a-SiC:H/a-Si:H

heterojunction solar cell and update on thin film Si:H

solar modules," Philos. Mag., vol. 89, no. 28-30, pp.

2677-2685, 2009,

https://doi.org/10.1080/14786430902758663

[29] A. Shirazi, R. A. Taylor, G. L. Morrison, and S.

D. White, "A comprehensive , multi-objective

optimization of solar-powered absorption chiller

systems for air-conditioning applications," Energy

Convers. Manag., vol. 132, pp. 281-306, 2017,

https://doi.org/10.1016/j.enconman.2016.11.039

[30] S. Comello and S. Reichelstein, "Cost

competitiveness of residential solar PV : The impact

of net metering," Renew. Sustain. Energy Rev., vol.

75, no. October 2016, pp. 46-57, 2017,

https://doi.org/10.1016/j.rser.2016.10.050

[31] L. Yun, G. Lalchand, G. Mak, and S. Lin,

"Economical , environmental and technical analysis

of building integrated photovoltaic systems in

Malaysia," vol. 36, pp. 2130-2142, 2008,

https://doi.org/10.1016/j.enpol.2008.02.016

17 ISSN: 2594-1925

Revista de Ciencias Tecnológicas (RECIT). Volumen 6 (3): e144

[32] T. Lang, E. Gloerfeld, and B. Girod, "Don ' t just

follow the sun - A global assessment of economic

performance for residential building photovoltaics,"

Renew. Sustain. Energy Rev., vol. 42, pp. 932-951,

2015, https://doi.org/10.1016/j.rser.2014.10.077

[33] M. A. El-Borie, A. A. Abdel-halim, and S. Y.

El-Monier, "North-South asymmetry of the solar

parameters during the different solar cycles," J.

Taibah Univ. Sci., vol. 10, no. 2, pp. 311-316, 2016,

https://doi.org/10.1016/j.jtusci.2016.02.001

[34] M. Neukom, S. Züfle, S. Jenatsch, and B.

Ruhstaller, "Opto-electronic characterization of

third-generation solar cells," Sci. Technol. Adv.

Mater., vol. 19, no. 1, pp. 291-316, 2018,

https://doi.org/10.1080/14686996.2018.1442091

[35] Y. U. López and H. A. Macias, "Methodology

to design and validate a sustainable isolated solar

photovoltaic system," Renew. Energy Power Qual.

J., vol. 1, no. 15, pp. 453-457, 2017,

https://doi.org/10.24084/repqj15.352

[36] A. K. Abu, I. Muslih, and M. A. Barghash, "Life

Cycle Costing of PV Generation System," J. Appl.

Res. Ind. Eng., vol. 4, no. 3, pp. 185-191, 2020,

https://doi.org/10.22105/jarie.2017.54724

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