Energy for Sustainable Development 43 (2018) 130–138
Contents lists available at ScienceDirect
Energy for Sustainable Development
Performance evaluation of a rooftop solar photovoltaic power plant in
Northern India
Satish Kumar Yadav ⁎, Usha Bajpai
Center of Excellence in Renewable Energy Education and Research, University of Lucknow (New Campus), Lucknow 226021, India
a r t i c l e
i n f o
Article history:
Received 21 January 2018
Accepted 22 January 2018
Available online xxxx
Keywords:
Performance analysis
Cell temperature
Energy yield
a b s t r a c t
The rapid growth of electricity demand due to the increase in population has put the burden on the power
stations of India to enhance their generation. With the serious drop in prices of solar photovoltaic (SPV) generated electricity and rising tariffs on conventional electricity have drawn attention to generate electricity through
the solar photovoltaic plant. Therefore, it is important to assess accurately and precisely the annual and monthly
yield of SPV plant to help in designing and installation of new plants. Performance analysis of a 5 kWp roof-top
photovoltaic plant has carried out, and the effect of temperature analyzed. The annual average daily reference
yield, array yield, and final yield found 5.23 kWh/kWp/day, 4.51 kWh/kWp/day and 3.99 kWh/kWp/day respectively. The annual average daily array efficiency, inverter efficiency and system efficiency found to be 11.34%,
88.38%, and 10.02% respectively. The annual average daily performance ratio and capacity utilization factor measured 76.97% and 16.39%. The annual energy yield of the plant recorded 7175.4 kWh. Results show that energy
loss is maximum during May when the temperature is highest. The performance of the plant compared with
PV plants installed all over in India and found comparable.
© 2018 International Energy Initiative. Published by Elsevier Inc. All rights reserved.
Introduction
In the 21st century, energy security is the primary goal of India. It is
impossible to achieve this goal with conventional energy resources. The
scarcity of conventional energy sources and environmental problems
associated with them has emphasized to use renewable energy sources
to fulfill the energy needs. Renewable energy sources will play a vital
role in the nation's target to be energy secured. The solar photovoltaic
energy systems can play a significant role to meet the present energy
demand and contribute to the sustainable development. In the Indian
context, solar photovoltaic conversion technology is preferred over
other renewable energy technologies due to availability and intensity
of solar radiation. India receives 4–7 kWh/m2 per day with an annual
radiation ranging from 1200 to 2300 kWh per square meter. It has an
average of 250–300 clear sunny days and 2300–3200 h of sunshine
per year (Kapoor, Pandey, Jain, & Nandan, 2014). Therefore, SPV systems
provide the opportunity for individual as well as industrialist to generate the electricity through solar energy.
The Government of India has taken several initiatives to the development of the solar sector in which JNNSM is the milestone. The
Jawaharlal Nehru National Solar Mission (JNNSM) under the brand
‘Solar India’ was launched in 2010 with the aim of achieving grid parity
by the year 2022. It proposed at the deployment of 20,000 MW of grid⁎ Corresponding author.
E-mail address: satishy975@gmail.com (S.K. Yadav).
connected and 2000 MW of off-grid solar power during the three
phases (first phase up to 2012–13, second phase from 2013 to 2017
and the third phase from 2017 to 2022) of its operative period
(JNNSM, 2008). The Central Government of India has increased the target of the JNNSM to 100 GW to be obtained through grid-connected
projects, off-grid projects and solar parks of 2022 (PIB, 2015). Therefore,
many stand-alone and grid-connected solar photovoltaic systems have
been installed and being installed rapidly to meet the target all over
India. It is necessary to assess all performance parameters of installed
PV plant precisely for the choice of technology, project development
and viability of a new project for a location.
The main problem of the PV system is to capture sunlight efficiently
and convert it into electricity. When solar photovoltaic module operates
into the real environment, its output characteristics vary compared to
standard test conditions (1000 W/m2 irradiance, 1.5 AM and 25 °C
temperature). The output power of a SPV module is affected by local climatic parameters (temperature, wind, humidity, dust deposition, etc.)
and geographical factors (latitude, longitude, etc.). Essentially, the performance of plant is affected by the temperature. The efficiency of SPV
modules reduces with the increase of ambient temperature. The International Energy Agency PVPS-Task 2 group has analyzed the performance
of 18 selected grid-connected PV systems of different mountings (free
standing, roof-mounted and integrated PV facades) from the different
geographic site in five countries. To see the temperature effect on the
systems, the group has used annual datasets of hourly data 17 out of
18 systems. Datasets showed an annual temperature loss ranging from
https://doi.org/10.1016/j.esd.2018.01.006
0973-0826/© 2018 International Energy Initiative. Published by Elsevier Inc. All rights reserved.
S.K. Yadav, U. Bajpai / Energy for Sustainable Development 43 (2018) 130–138
1.2 to 10.3%. The annual average daytime temperature for all the PV
systems is between 2 and 21 °C. A well-cooled PV array can have a
temperature rise of about 25 K at 1000 W/m2 and a temperature loss of
less than 4% (Nordmann & Clavadetscher, 2003).
Another study performed in Italy, the campus of the University of
Salento to know the effect of climatic parameters on the performance on installed PV system in a particular geographical area. A
960 kWp photovoltaic system divided into two subfields with different tilt angle (3–15°) and different nominal powers (353.3 kWp and
606.6 kWp). The values of performance parameters like final yield,
reference yield, PV system efficiency, performance ratio (PR) and
cell temperature losses were analyzed. The study concluded that
the PV system efficiency varies between the highest value of 17% in
spring to the lowest value of 15% in summer, and the PR rises at the
maximum point of 86.5% in March to the minimum point of 79% in
June. The cell temperature losses were reported to a minimum of
3.5% in October to a maximum of 8% in June (Congedo, Paolo,
Malvoni, & De Giorgi, 2013).
Vasisht, Srinivasan, and Ramasesha (2016) calculated the effect of
temperature variation on the performance of a 20 kWp grid-connected
SPV plant for different seasons throughout the year. In summer, as
module temperature rises above 45 °C module efficiency reduces by
0.08% per degree rise in temperature. In monsoon, for module temperature rises 35 °C, module efficiency reduces by 0.04% per degree rise in
temperature. In post-monsoon module's efficiency reduces by 0.06%
per degree rise temperature when module temperature increases than
38 °C. However, in winters, module temperature is 55 °C but the
minimum drop in efficiency recorded due to the cool breeze and low
ambient temperatures.
In this present study, the performance of a 5 kWp rooftop gridconnected solar power plant is evaluated based on normalised parameters like reference yield, array yield, final yield, PV module efficiency,
inverter efficiency, system efficiency, performance ratio and capacity factor using monitored data for the year 2015. Calculated results give a detailed information of system performance and provide a source for the
techno-economic development of a new project. The effect of
temperature on the performance of the plant is also observed in
different seasons throughout the year. Here, the present study reveals
the annual behavior of PV system with concerning operating temperature. The performance of plant is also compared to the other plants
installed all over India.
131
The SPV system specification
The experimental analysis conducted in the Centre of Excellence
in Renewable Energy Education and Research located at the New
Campus of the University of Lucknow. It situated on 26.30 and
27.10 North latitude and 80.30 and 81.13 East longitude. Lucknow's
weather can be broadly divided into four seasons winter (Dec–
Feb), summer (Mar–June), monsoon (July–Sep) and post-monsoon
seasons (Oct–Nov). To reduce the consumption of conventional electricity and fulfill the demand through clean electricity, state nodal
agency UPNEDA (Uttar Pradesh New and Renewable Energy Development Agency) has installed a SPV plant to the University of Lucknow, which is a 5 kWp solar photovoltaic power plant on the
building roof of the Centre of Excellence in Renewable Energy Education and Research (Fig. 1). The funding of the project has been from
the Ministry of New and Renewable Energy, Government of India.
All generated electricity fed into the centre's load. The plant has
grid connection to fulfill the energy demand in the absence of solar
radiation and supply electricity to the load during the excess requirement of electricity in some special occasions.
The solar photovoltaic power plant consists an array of 20 solar
photovoltaic modules manufactured by Sova Power Limited-SS250P. PV
array covers an area of 38.4 m2 with 1.92 m2 single module area. Each
module comprises 72 polycrystalline silicon series connected solar cells
with area 202.8 cm2. The modules are oriented toward the south direction
at the tilt angle of 26.5° (latitude of Lucknow) to receive the maximum
solar radiation. Array consist four series connected modules form a string
and these strings arranged in parallel, which attached to a junction box.
The output of junction box connected to MPPT based inverter also called
Power Conditioning Unit (PCU), which converts DC to AC to match load
demand. It provides uninterrupted power to the load using solar and
grid input in same order of priority. The PCU had 90.0% rated efficiency
with 5 kVA maximum AC power. PCU consists latest Digital signal processor (DSP) based pure sine wave inverter, which provides continuous pure
sine wave power to the load (Fig. 2).
Data logging
A weather data logging station installed near the plant, which
records solar radiation, temperature, relative humidity, wind speed
and direction, rainfall, atmospheric pressure, and soil moisture data
Fig. 1. Satellite view of location of 5 kWp rooftop SPV array.
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S.K. Yadav, U. Bajpai / Energy for Sustainable Development 43 (2018) 130–138
for each five-minute interval. Solar PCU monitoring interface records
the output data of PV array voltage, current, power and inverters output
parameters like Voltage, current and power for each five-minute and
store in the computer. The back surface temperature of the module
has measured with the help of thermocouple based Type-K (NiCrNiAl) sensor. The probe measures the temperature at every fiveminute interval (with allowable error ± 3%) and stores it into micro
SD memory card.
which allows to comparing the similar PV systems in a particular geographic location (Ayompe et al., 2011).
YF ¼
EAC
Po
Unit of final yield is kWh/kWp/d (or h/d).
Reference yield (YR)
System performance indices
The performance of solar PV systems can be different according to
their different configurations and locations. The performance of PV
systems can readily compare by evaluating their performance indices like array yield, final yield, reference yield, capture loss, performance ratio, and system efficiencies etc. These indices provide
primary information about the performance of the PV system that
the system is working properly or not. After calculating these indices,
we can compare the performance of same PV systems under various
operating conditions (IEC 61724, 1998, Ayompe, Duffy, McCormack,
& Conlon, 2011).
YR ¼
HT
Go
Unit of reference yield is kWh/kWp/d (or h/d).
Performance ratio (PR)
Array yield (YA)
It is the energy output from a PV array (EA, DC) over the installed
array's rated output power (Po). It represents the number of hours per
day that the array would need to operate at its rated output power to
contribute the same daily array energy to the system as was monitored
(IEC 61724, 1998).
YA ¼
The reference yield is the total in-plane irradiance HT divided by the
PV's reference irradiance Go. It represents an equal number of hours at
the reference irradiance. If G0 equals 1 kW/m2, then reference yield is
the number of peak sunhours or the solar radiation in units of kWh/m2
(Marion et al., 2005).
EA;DC
Po
Unit of array yield is kWh/kWp/d (or h/d).
The performance ratio is the ratio of the final yield and the reference
yield. The PR is a dimensionless quantity that represents the total losses
in the system when converting from rated DC power to output AC
power. PR values are useful for determining if the system is operating
as expected and for identifying the occurrence of problems due to
inverter operation (faults/failures, maximum power tracking), trip of
the circuit-breaker, solder-bond failures in module junction boxes,
diode failures, inoperative trackers, snow, soiling, shading, degradation
of PV system, or other failures (Marion et al., 2005).
PRð%Þ ¼
YF
YR
Final yield (YF)
It is the daily, monthly or annually net energy output (EAC) of the
entire PV plant, which supplied by the array per kW of installed PV
array (Po) at standard test conditions (STC) of 1000 W/m2 solar
irradiance and 25 °C cell temperature. This is a characteristic parameter,
The higher PR value suggests that the plant working near the rated
power whereas lower indicates production losses due to technical or
design problem. Normally PR value varies within the range of 0.6 to
0.8 due to the variable weather conditions (Sharma and Goel, 2017).
In cool climates, it can exceed even 0.9 (Dierauf et al., 2013).
Fig. 2. Schematic block diagram of the SPV plant.
S.K. Yadav, U. Bajpai / Energy for Sustainable Development 43 (2018) 130–138
Capacity utilization factor (CUF)
61724, 1998).
It is the ratio of the real amount of generated energy by the PV
plant for 24 h per day for a year, to the maximum possible output energy from it for a year under the rated power. Capacity utilization
factor usually expressed in percentage (Kymakis, Kalykakis, &
Papazoglou, 2009).
ηA ð%Þ ¼
CUFð%Þ ¼
YF
EAC
¼
100
24 365 P0 24 365
CUF is a site dependent parameter. It varies according to the solar
radiation received and the number of clear sunny days experienced by
the PV plant's site. It affected significantly according to the type of
module used (Vasisht et al., 2016).
EA
100
Aa HT
where
EA Total generated DC energy per day (kWh)
Aa Overall array area (m2)
HT In-plane irradiance per day (kWh/m2).
Inverter efficiency (ηinv)
It formulated as the ratio of AC power generated by the inverter
(PAC) to the DC power (PDC) generated by the PV array system. The instantaneous inverter efficiency given by (IEC 61724, 1998).
ηinv ð%Þ ¼
Various losses
An SPV power plant generates less energy compare to rated energy
due to variable climatic conditions and losses in Balance of System
(BOS) Components. Using measured data different losses have been
calculated.
Array capture losses (LC)
Array capture losses occur due to array operation, which can represent
as (Kymakis et al., 2009):
LC ¼ YR −YA ðkWh=kWp=d or h=dÞ
These are two types:
A. Thermal capture loss (LCT): Thermal capture loss occurs when PV
module operates beyond 25 °C. Thermal capture loss is the difference between reference yield and temperature corrected referenced
yield (Padmavathi & Daniel, 2013).
YCT ¼ YR −YR corr:
ðkWh=kWp=d or h=dÞ
YR corr. is temperature corrected reference yield which is given by:
YR corr: ¼ YR ½1−λðTm −25Þ ðkWh=kWp=d or h=dÞ
where λ is temperature coefficient of power In %/°C.
B. Miscellaneous capture loss (LCM): These losses occur due to wiring
and cables losses, losses due to diodes, shading, mismatched losses
between modules and strings, soiling and maximum power point
tracking losses.
LCM ¼ LC −LCT
ðkWh=kWp=d or h=dÞ
133
PAC
100
PDC
System efficiency (ηsys)
It defined as the ratio of output total AC energy to the total input
energy (Ayompe et al., 2011).
ηsys ð%Þ ¼
EAC
100
Aa HT
EAC Total generated AC energy per day (kWh)
Aa Overall array area (m2)
HT In-plane irradiance per day per day (kWh/m2).
It can also represent as (Kumar & Sudhakar, 2015):
ηsys ð%Þ ¼ ηA ηinv
where
ηA Array efficiency
ηinv Inverter efficiency
Results and discussion
Performance of PV systems affected by the climatic parameters
mostly by temperature. Cell temperature plays a crucial role in output
energy of SPV system. The temperature of a module varies according
to other parameters like solar irradiance, ambient temperature, wind
velocity, rain, and humidity. Effect of these parameters on the cell
temperature of the module has analyzed based on the recorded data
of data logger.
Analysis of weather data
Effect of plane of array irradiance on cell temperature
System losses (L S ). System losses cover all the losses of energy,
which occur during the conversion of the array generated DC energy into usable AC energy. These losses caused by inverter, conduction and losses of passive circuit elements (Kumar & Sudhakar,
2015).
LS ¼ YA −Y F
ðkWh=kWp=d or h=dÞ
Efficiencies
Array efficiency (ηA)
It defined by the ratio of output energy to input energy. Actually, it
represents the energy conversion efficiency of the PV array (IEC
Logged data provides the information about the annual variation of
the climatic parameters. Solar radiation is the main parameter to
generate the power, but it increases cell temperature as well. Solar
radiation directly affects the cell temperature (Tc). When solar irradiance strikes over the solar cell, some portion of it reflected, transmitted
and absorbed. Only a small fraction of absorbed radiation converted into
electricity, except it's all low and high energy radiation take part to raise
the cell temperature. In May, the maximum monthly average daily solar
insolation recorded 7.33 kWh/m2/d, while in December the lowest
recorded solar insolation was 3.16 kWh/m2/d. Maximum monthly
average daily cell temperature of 51.81 °C recorded during May when
the solar irradiance of the month was maximum, and minimum
monthly average daily cell temperature of 24.46 °C recorded in January
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S.K. Yadav, U. Bajpai / Energy for Sustainable Development 43 (2018) 130–138
55.00
55.00
R² = 0.9331
50.00
Cell temperature (oC)
Cell Temperature (oC)
50.00
45.00
40.00
35.00
30.00
25.00
20.00
2.50
45.00
y = -0.4515x + 68.399
40.00
35.00
30.00
25.00
3.50
4.50
5.50
6.50
7.50
20.00
30.0
8.50
Plane of array irradiacnce (kWh/m2/d)
40.0
50.0
60.0
70.0
80.0
90.0
Humidity (%)
Fig. 3. Annual variation of plane of array irradiance and cell temperature.
Fig. 5. Annual variation of cell temperature and humidity.
when the solar irradiance of the month was the minimum. The average
hourly cell temperature increases linearly with the increase of solar
radiation and shows a strong correlation (R2 = 0.9331) with solar
irradiance Fig. 3.
(−0.4515) shows that cell temperature decreases linearly by increasing
the humidity.
Effect of ambient temperature on cell temperature
Good wind speed keeps the module cool and prevents the loss of the
output power. Monthly average daily wind speed recorded 2.5 m/s in
June and the minimum wind speed 0.6 m/s in November month at
system's site. Installed SPV system is an open rack mounted system
that is at the height of 12 m from earth surface. The system has enough
air gap between the roof and fixed modules which is better for module
heat transfer than any other PV system like.
BIPV (Building Integrated Photovoltaic) system, as it can transfer
heat from both surfaces to the ambient (Kurnik, Jankovec, Brecl, &
Topic, 2011). Fig. 6 shows the relation between the wind velocity and
the difference between cell temperature and ambient temperature
(Tc-Ta). Negative correlation (−0.3465) coefficient shows that as the
wind velocity increases, the temperature of the module decreases
linearly. As monthly average daily wind speed increases from 1.5 m/s
to 2.5 m/s during May and June, an average decrement of 3° has seen
in the (Tc-Ta).
Like solar radiation, Cell temperature also keeps a linear relationship
to the ambient temperature (Ta). As the ambient temperature rises, the
cell temperature rises as well. Sandwich structure of solar module creates the greenhouse effect, which plays a supporting role in the rise of
cell temperature. The annual average monthly ambient temperature
varied between 13.23 °C to 37.84 °C. The minimum ambient temperature measured in January and maximum ambient temperature in May.
According to the ambient temperature, maximum cell temperature
also recorded in the May and minimum in January. The correlation
coefficient (R2 = 0.98) shows the close linear relation between ambient
temperature and the cell temperature. Fig. 4 suggest that as the ambient
temperature increases the cell temperature increases linearly.
Effect of humidity on cell temperature
In January maximum monthly average daily relative humidity of
82.5%, recorded and minimum monthly average daily humidity was
41.84% in May. The highest value of TC recorded in the summer when
Humidity was the lowest and minimum value of TC recorded in winter
when average humidity was maximum. Due to high humidity water
droplets stick on the back surface of the module, which helps to keep
it cool by transfer the module's heat through evaporation. Fig. 5 shows
that the increase of humidity the value of Tc falls. Negative coefficient
Effect of wind speed on cell temperature
Effect of rain on cell temperature
Rain influences the temperature of solar cell indirectly. It works as a
cleaning agent, which cleans the deposited dust of the PV modules. A
Dusty module gets more temperature than the clean module
(Rouholamini, Pourgharibshahi, Fadaeinedjad, & Abdolzadeh, 2014).
15.0
14.0
y = -0.3465x + 13.059
55.00
13.0
R² = 0.9803
50.00
(Tc-Ta) (oC)
Cell Temperature (oC)
60.00
45.00
40.00
35.00
12.0
11.0
10.0
30.00
9.0
25.00
20.00
10.00
8.0
15.00
20.00
25.00
30.00
35.00
Ambient Temperature (oC)
Fig. 4. Annual variation of ambient temperature and cell temperature.
40.00
0.5
1.0
1.5
2.0
2.5
Wind velocity (m/s)
Fig. 6. Annual variation of Wind velocity and (Tc-Ta).
3.0
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S.K. Yadav, U. Bajpai / Energy for Sustainable Development 43 (2018) 130–138
Rain
∆Tcnd Conduction temperature drop. In the calculation, the value of
∆Tcnd is taken 3, because the array is open rack mounted (Dierauf
et al., 2013).
200
60.00
160
140
40.00
120
100
30.00
80
20.00
Rain (mm)
Cell temperature (oC)
180
50.00
60
40
10.00
20
0
0.00
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
Month
Fig. 7. Annual variation of rain and (Tc-Ta).
Maximum rain recorded in July is 179.1 mm and minimum rain of 0.5
mm recorded in November. Fig. 7 shows that average cell temperature
falls about 6 °C in July from the previous month when the maximum
rain recorded. In August a decrement of 4 °C in cell temperature
recorded with 175.8 mm rain.
Effect of temperature on the performance of SPV power plant
Photovoltaic conversion process directly affected by the operating
temperature of the solar cell. The solar cell temperature rises fast
comparatively to the ambient temperature. Solar radiation has a wide
range of the spectrum, which does not fully convert into electric energy
by the solar cell. A solar cell converts only that radiation which is equal
to its bandgap (∆Eg) excess radiation absorbed by the solar cell as heat.
The output characteristics of solar cell vary according to the variation of
the cell temperature.
Efficiency of array
The solar cell is a semiconductor device. As its temperature rises, the
bandgap of semiconductor contracts and the Open circuit voltage (Voc)
of the solar cell decreases while short-circuit current (Isc) of it increases
on increasing the temperature, due to easy reach of charge carriers from
the valence band to the conduction band. That is why the solar cell has
negative temperature coefficient for the open circuit voltage whereas
positive temperature coefficient for the short-circuit current (Shenck,
2010). Therefore, temperature essentially affects the Voc of the solar
cell. Voc reduces linearly with increase of cell temperature, hence the
efficiency of module drops (Skoplaki & Palyvos, 2009). The effect of
temperature on the PV module's electrical efficiency can be obtained
by using Evans and Florschuetz (1977) temperature corrected PV
efficiency equation:
ηc ¼ ηTref ½1 þ βref ðTc −Tref Þ
ð9Þ
ηTref is the module electrical efficiency at the reference temperature.
Tref is reference temperature. βref is the temperature coefficient of the
power. The PV manufacturer normally gives the quantity ηTref and βref.
ηc is temperature derated efficiency of the module and Tc is cell temperature and calculated as follows:
Tc ¼ Tm þ
GPOA
∆T
GSTC
Tm Measured module back surface temperature (°C)
GPOA Plane of array irradiance (W/m2).
GSTC Reference irradiance at STC; constant at 1000 (W/m2)
Mostly, the array efficiency of SPV plant affected by the temperature
in summer due to long exposure of solar irradiance, modules temperature becomes higher than other seasons. Module output power reduces
per degree rise in temperature above 25 °C, according to its temperature
coefficient of power. In the summer, with a decrease of 15.37%, the
array's efficiency was measured 11.00%. In May, a maximum decrement
of 17.90% in the array's efficiency noted with an average monthly cell
temperature 51.81 °C. During the monsoon period, an average reduction in the efficiency of the array found 14.21%. Due to oceanic air and
raining in monsoon, ambient temperature falls resultant the temperature of the array falls as compared to summer and improves the array's
efficiency. In the monsoon, 11.15% of array's efficiency measured. About
12.28% drop of the efficiency of array observed during post-monsoon
period. Lowest reduction in the array's efficiency of 8.26% measured
during the winter. Highest array's efficiency of 12.08% observed in
January due to the lowest ambient temperature. In winter, average
efficiency of the array measured of 11.93% when the average temperature of the cell was 27.98 °C. The annual efficiency of the array observed
11.34% with a drop of 12.79%. Array efficiency of the present system was
greater than most of the installed systems across the world as 6.08% for
Shivgangai (Sundaram & Babu, 2015), 9.54% for Turkey (Eke &
Demircan, 2013), 11.02% for Thailand (Chimtavee & Ketjoy, 2012),
8.9% for Spain (Drif et al., 2007), 10.11% for Malaysia (Farhoodnea,
Azaz, Khatib, & Elmenreich, 2015).
Inverter efficiency
The performance of SPV power plant also depends on the efficiency
of the inverter. Hence, it is important to know the impact of the temperature on the efficiency of the inverter. Some studies reported that high
temperature put a negative impact on the efficiency of the inverter
(Rouholamini et al., 2014). The annual average monthly value of
inverter's efficiency recorded 88.38%. A drop of 1.7% recorded of inverter
efficiency from its rated efficiency during the year. The maximum of
3.92% reduction in the efficiency recorded in the month of May. In
summer, 2.49% and 1.33% drop recorded in the monsoon. The minimum
reduction of 0.78% recorded in the winter. Best inverter efficiency
observed in February due to low ambient temperature and good solar
radiation, which was 89.53%. Minimum inverter efficiency of 86.28%
recorded in May when the temperature was maximum. A reduction of
2.08% in inverter's efficiency recorded in the post-monsoon period.
Fig. 8 demonstrates the slope of the trend-line is negative (−0.0452).
Negative value suggests that high temperature put a negative impact
92
Inverter efficiency (%)
Tc
y = -0.0452x + 89.611
90
88
86
84
82
ð10Þ
80
10.00
15.00
20.00
25.00
30.00
35.00
Ambient temperature (oC)
Fig. 8. Variation of inverter efficiency and ambient temperature.
40.00
136
S.K. Yadav, U. Bajpai / Energy for Sustainable Development 43 (2018) 130–138
on the efficiency of the inverter, that means inverter efficiency decreases on increasing the ambient temperature. The efficiency of inverter of present system is maximum than the system installed in
shivgangai for 88.2% (Sundaram & Babu, 2015), 88.1% for Spain (Drif
et al., 2007), 87% for Ireland (Mondol, Yohanis, Smyth, & Norton,
2006), 88.1% for Algeria (Okello, Van Dyk, & Voster, 2015).
System efficiency
Kalan (Sharma and Chandel, 2013). System has also higher value than
plant installed across the world as 2.4 kWh/kWp/day for Ireland
(Ayompe et al., 2011), 3.12 kWh/kWp/day for Singapore (Wittkopf,
Valliappan, Liu, Ang, & Cheng, 2012), 3.84 kWh/kWp/day for Thailand
(Chimtavee & Ketjoy, 2012), 2.4 kWh/kWp/day for Spain (Drif et al.,
2007), 2.07 kWh/kWp/day for Norway (Adaramola & Vågnes, 2015)
and 3.87 kWh/kWp/day for Turkey (Eke & Demircan, 2013).
Performance ratio (PR)
Yields of plant
The yields of grid-connected power plant deduced with the help of
collected data. Fig. 9 shows final yield, array yield and reference yield
of different months. Reference yield varies from 3.16 kWh/kWp/day to
7.33 kWh/kWp/day. Minimum reference yield of 3.16 kWh/kWp/d is
found in December because the sunshine hour lessened in this month
and maximum references yield 7.33 kWh/kWp/day is found in May
because the sunshine hours in this month recorded more than the
other months. Monthly average daily array yield increases from 2.90
kWh/kWp/day to 6.01 kWh/kWp/day. The array yield relies on the availability of solar radiation, meteorological conditions of the site and the
conversion efficiency of the modules, while the final yield depends on
the components of the SPV system, such as the efficiency of the inverter
and charge controller. Minimum monthly average daily final yield was
2.59 kWh/kWp/day, and the maximum average daily final yield was
5.32 kWh/kWp/day in May. Low final yield in January is due to less
solar radiation and higher final yield in May is due to higher solar radiation. The average annual final yield of the system was 3.99 kWh/kWp/
day being a value higher than the most plant installed in India, as for example 3.67 kWh/kWp/day final yield were found of PV plant in Bhubaneswar (Sharma & Goel, 2017), 3.73 kWh/kWp/day for Karnataka
(Padmavathi & Daniel, 2013), 3.32 kWh/kWp/day for Roorkee (Pundir
et al., 2016), 1.45 kWh/kWp/day to 2.84 kWh/kWp/day for khatkar-
Final Yeild
Array Yeild
Solar Photovoltaic system operates comparatively higher temperature than the temperature at STC. Temperature shows a large seasonal
variation in the PR, which can be ±10% (Dierauf et al., 2013). PR of
the plant varies from 72.67% in May to 82.50% in January (Fig. 10). The
maximum loss in PR measured in May when power loss due to temperature was maximum. Average PR in summer was recorded 74.03%. The
value of PR improves and recorded 76.0% in the monsoon due to lower
module temperature and clear sky. In the post-monsoon, the value of PR
recorded 77.11%, which was more than the value monsoon and
summer. In winter, PR value is 81.76% which was highest than the
other seasons. Annual average PR of the plant recorded 76.97% which
is higher than most systems installed in India as for example 63.68%
for Roorkee (Pundir et al., 2016), 74% for Khatkar-Kalan (Sharma and
Chandel, 2013), 72% for Karnataka (Padmavathi & Daniel, 2013), and
close for system in Bhubaneswar with 78% (Sharma & Goel, 2017). PV
system also shows the greater PR value than most of plant installed
across the world like 64.3% in Algeria (Okello et al., 2015), 72% in
Turkey (Eke & Demircan, 2013), 73.45% in Thailand (Chimtavee &
Ketjoy, 2012), 67.36% in Greece (Kymakis et al., 2009), and 62.7%, in
Spain (Drif et al., 2007).
Capacity utilization factor
A simulation study performs by the Doolla and Banerjee (2010) on
the output of a 1 MW peak power the plant located in different regions
of India. The study reveals that CUF varies according to the solar
irradiance and ambient temperature of the location. In India, Capacity
utilization factor varies from 16% to 20%. It is complex to see the effect
of temperature on the CUF of the plant in real environment. CUF of
the plant varies from 10.44% to 21.47% to the whole year (Fig. 10).
Maximum CUF of 21.47% obtained in May when electricity production
was maximum and minimum CUF of 10.44% obtained in December
when the electricity production was minimum. In summer, CUF of the
plant was 18.57%, and in monsoon, it was recorded 18.28%. The value
of CUF of 15.87% was measured in the post-monsoon period. The
minimum CUF of 11.94% was measured in winter. Annual average CUF
Eac
Reference Yeild
CUF and PR (%)
Yields (kWh/kWp/d)
8.00
7.00
6.00
5.00
4.00
3.00
2.00
1.00
PR
CUF
90
900.0
80
800.0
70
700.0
60
600.0
50
500.0
40
400.0
30
300.0
20
200.0
10
100.0
0
Eac (kWh/mo)
System Efficiency is the product of module efficiency and inverter
efficiency. System efficiency will be maximum when both the efficiencies are maximum. The system efficiency varied from 9.46% in May to
10.74% in January. The minimum value of efficiency recorded in May,
when the module and inverter efficiency was minimum due to the
higher ambient temperature. Maximum efficiency of 10.74% recorded
in the January when module efficiency was maximum. The annual
average monthly system efficiency recorded to be 10.02%, which is
higher than most of the systems installed. In Khatkar-Kalan systems efficiency was 8.3% (Sharma and Chandel, 2013). In Roorkee, Shivgangai,
Spain, Ireland systems efficiency were 8.7% (Pundir, Varshney, & Singh,
2016), 5.08% (Sundaram & Babu, 2015), 7.8% (Drif et al., 2007), 6.0–9.0%
(Mondol et al., 2006) respectively.
0.0
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
0.00
Jan
Feb Mar
Apr May Jun
Jul
Aug
Sep
Oct
Nov Dec
Month
Month
Fig. 9. Yields of the SPV power plant.
Fig. 10. Monthly performance ratio, capacity utilization factor and total generated
electricity of the plant.
137
S.K. Yadav, U. Bajpai / Energy for Sustainable Development 43 (2018) 130–138
Table 1
Comparison of the performance parameters of the plant from other installed plants over India.
Location
Year
PV type
System size
YF (kWh/kWp/d)
Array eff. (%)
Inverter eff. (%)
System eff. (%)
PR (%)
CUF (%)
Reference
Lucknow
Bhubaneswar
Roorkee
Norway
Algeria
Malaysia
Shivgangai
Khatkar-Kalan
Karnataka
Turkey
Thailand
Singapore
Ireland
Greece
Spain
Ireland
2017
2017
2016
2015
2015
2015
2015
2013
2013
2013
2012
2012
2011
2009
2007
2006
p-sib
p-si
p-si
mc-si/p-si
p-si
mc-sia
–
p-si
mc-si
p-si
–
p-si
mc-si
p-si
mc-si
mc-si
5 kWp
11.2 kWp
1816 kWp
2.07 kWp
3.2 kWp
3 kWp
5 MWp
190 kWp
3 MWp
2.73 kWp
11 kWp
142.5 kWp
1.72 kWp
171.36 kWp
200 kWp
13 kWp
3.99
3.67
3.32
2.55
4.9
3.8
4.81
1.45–2.84
3.73
3.87
3.84
3.12
2.4
1.96–5.07
2.4
1.69
11.34
13.42
–
12.7
13.72
10.11
6.08
–
10.1–13.25
9.54
11.2
13.7
14.9
–
8.9
7.5–10.0
88.38
89.83
97
88.8
88.1
95.15
88.2
–
–
–
93
94.8
89.2
–
88.1
87
10.02
12.5
8.7
11.6
–
–
5.08
8.3
–
76.97
78
63.68
83.03
64.3
77.28
85.5–92.3
74
72
72
73.45
81
81.50
67.36
62.7
60–62
16.39
15.27
13.85
10.58
20.41
15.7
–
9.27
15.69
23.2
14
15.7
10.10
15.26
–
–
Present study
Sharma and Goel
Pundir et al.
Adaramola and Vågnes
Okello et al.
Farhoodnea M et al
Sundaram and Babu
Sharma and Chandel
Padmavathi and Daniel
Eke and Demircan
Chimtavee and Ketjoy
Wittkopf et al.
Ayompe et al
Kymakis et al.
Drif et al.
Mondol et al.
a
b
10.41
11.2
13.3
–
7.8
6.0–9.0
mc-si, monocrystalline silicon solar cell.
p-si, polycrystalline solar cell.
registered 16.39%, which is more than most of systems presented in
Table 1 as 15.27% for Bhubaneswar (Sharma & Goel, 2017), 9.27% for
Khatkar-Kalan (Sharma and Chandel, 2013), 15.69% for Karnataka
(Padmavathi & Daniel, 2013) and 13.85% for Roorkee (Pundir et al.,
2016). CUF value of different PV systems installed in Norway,
Malaysia, Thailand, Ireland, Greece are 10.58% (Adaramola & Vågnes,
2015), 15.7% (Farhoodnea et al., 2015), 14% (Chimtavee & Ketjoy,
2012), 10.1% (Ayompe et al., 2011), 15.26% (Kymakis et al., 2009)
respectively, which is less than present system.
1.52 kWh/kWp/day in July (Kymakis et al., 2009). Annual average
monthly capture losses due to the temperature (LCT) of 6.34% were
measured. Highest LCT of 11.53% recorded in May due to peak cell temperature. In Karnataka, India, capture losses due to temperature were recorded 8.86% of the reference yield in May (Padmavathi & Daniel,
2013). Annual capture losses, system losses and total losses recorded
12.92%, 11.62% and 24.54% of reference yield respectively. Total estimated
losses of 31.7% calculated in Khatkar-Kalan, India (Sharma and Chandel,
2013). System losses can be reduced by using the more efficient inverter.
Loss calculation
Total energy production
Highest capture losses (LC) of 1.32 kWh/kWp/day recorded in May
when the cell temperature was the highest compared to other seasons
and lowest value of 0.23 kWh/kWp/day was observed in January. Selfshading by modules increases the capture losses due to the decrease of
declination angle of the sun. Concrete dome of the building also
increases the capture losses by putting a partial shade on the array in
winter. System losses (LS) vary from 0.31 kWh/kWp/day in December
to 0.68 kWh/kWp/day in the month of May. Maximum system losses of
0.68 kWh/kWp/day measured in May due to the high capture losses
and low system efficiency. Annually capture losses, system losses and
total losses measured 0.53 kWh/kWp/day, 0.71 kWh/kWp/day and 1.24
kWh/kWp/day (Fig. 11) respectively. Which is similar to system installed
in Bhubaneswar, India, with system losses, capture losses, and total losses
were 0.43 kWh/kWp/day, 0.64 kWh/kWp/day, 1.06 kWh/kWp/day respectively (Sharma & Goel, 2017). In Greece, daily array losses varied
from 0.54 kWh/kWp/day in November to 1.38 kWh/kWp/day in September and the system losses varied from 0.29 kWh/kWp/day in December to
Energy generation directly depends on the sun's intensity and its
availability. In another word, elecricity generation relies on the total radiation falling on the per meter square area of the module and number
of sunshine hours that present in a day. The maximum energy generated in the May, which was 798.70 kWh due to the maximum availability of solar irradiance. The minimum energy generated in the month of
December was 388.40 kWh due to the reduction of solar irradiance. According to the average per day generation, 26.62 kWh/d is the highest in
May. The minimum average daily generation was 12.95 kWh/d in December. Annually average monthly generation registered 19.93 kWh
per month. Total generated energy by the plant is 7175.40 kWh in the
monitored year.
Ls
Lc
Tc
8.00
55.00
7.00
50.00
45.00
6.00
40.00
5.00
35.00
4.00
30.00
25.00
3.00
20.00
2.00
15.00
1.00
10.00
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
Month
Fig. 11. Final yield and different losses of the SPV power plant.
Cell Temperature (oC)
YF , Losses (kWh/kWp/d)
Yf
Environmental benefits of SPV plant
India highly depends on the coal based thermal power plants for electricity generation, which releases huge amount of greenhouse gasses
(GHGs) into atmosphere. In one unit (kWh) electricity generation thermal plant emits an average of 980 g carbon dioxide (CO2) (Sharma &
Tiwari, 2013), 1.24 g sulphur dioxide (SO2), 2.59 g nitrogen oxide
(NOx) and 68 g ash (Agai, Caka, & Komoni, 2011). The SPV plant puts a
positive impact on the environment by reducing the emission of greenhouse gasses and global warming. In the year 2015, it is estimated that
5 kWp PV system prevents about 7031.9 kg CO2, 8.9 kg SO2 and 18.6 kg
NOx to enter into the atmosphere.
Conclusion
A detailed performance analysis of 5 kW rooftop SPV power plant
has been presented based on one year monitored data. The effect of
temperature on the performance of the plant has seen and compared
with other installed plants in India. The annual average reference
yield, array yield and final yield of plant were 5.23 kWh/kW/day, 4.51
138
S.K. Yadav, U. Bajpai / Energy for Sustainable Development 43 (2018) 130–138
kWh/kWp/day and 3.99 kWh/kWp/day respectively. System yield
shows that working of system is quite satisfactory. The average PV
array efficiency, inverter efficiency and system efficiency were found
11.34%, 88.38% and 10.02% respectively. Annual average PR of the
plant is 76.97% and CUF is 16.39%, which is comparable to the other
plant installed in India. The yearly yield of plant is 7175.4 kWh/year
with an average of 24.54% total losses. Capture losses and system losses
are found 12.92% and 11.62% respectively. Capture losses due to rise of
cell temperature calculated 6.34%. System losses can be reduced by
using a more efficient inverter. The plant prevented 7.032 tone of CO2
from entering into the atmosphere throughout the year.
Acknowledgement
The authors are thankful to the Ministry of New and Renewable
Energy (MNRE), Government of India, New Delhi for granting fellowship under the National Renewable Energy Fellowship Programme.
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