Performance evaluation of a rooftop solar photovoltaic power plant in ...

Energy for Sustainable Development 43 (2018) 130–138

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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

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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: [email protected] (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.

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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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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.


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


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


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

134


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)


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


Rain

ΔTcnd Conduction temperature drop. In the calculation, the value of ΔTcnd 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

60

Rain (mm)

Cell temperature (oC)

180 50.00

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 (ΔEg) 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 − 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: GPOA Tc ¼ Tm þ ΔT ð10Þ 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

135

y = -0.0452x + 89.611

90 88 86 84 82 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


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.


0.00 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.


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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


Month Fig. 11. Final yield and different losses of the SPV power plant.


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

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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. References Adaramola, M. S., & Vågnes, E. E. T. (2015). Preliminary assessment of a small-scale rooftop PV-grid tied in Norwegian climatic conditions. Energy Conversion and Management, 90, 458–465. Agai, F., Caka, V., & Komoni, V. (2011). Design optimization and simulation of the photovoltaic systems on buildings in southeast Europe. International Journal of Advances in Engineering & Technology, 1, 58–68. Ayompe, L. M., Duffy, A., McCormack, S. J., & Conlon, M. (2011). Measured performance of a 1.72 kW rooftop grid connected photovoltaic system in Ireland. Energy Conversion and Management, 52, 816–825. Chimtavee, A., & Ketjoy, N. (2012). PV generator performance evaluation and load analysis of the PV microgrid system in Thailand. Procedia Engineering, 32, 384–391. Congedo, P. M., Paolo, M., Malvoni, M., & De Giorgi, M. G. (2013). Performance measurements of monocrystalline silicon PV modules in South-eastern Italy. Energy Conversion and Management, 68, 1–10. Dierauf, T., Growitz, A., Kurtz, S., Cruz, J. L. B., Riley, E., & Hansen, C. (2013). Weathercorrected performance ratio. (Technical Report, NREL/TP-5200-57991). Retrieved from National Renewable Energy Laboratory (NREL)https://www.nrel.gov/docs/ fy13osti/57991.pdf, Accessed date: 21 March 2017. Doolla, S., & Banerjee, R. (2010). Diffusion of grid connected PV in India: An analysis of variations incapacity factor. Proceeding of 35th IEEE photovoltaic specialists conference (PVSC); Berlin. Drif, M., Pérez, P. J., Aguilera, J., Almonacid, G., Gomez, P., De la Casa, J., et al. (2007). Univer Project. A grid connected photovoltaic system of at Jaén University. Overview and performance analysis. Solar Energy Materials and Solar Cells, 91, 670–683. Eke, R., & Demircan, H. (2013). Performance analysis of a multi crystalline Si photovoltaic module under Mugla climatic conditions in Turkey. Energy Conversion and Management, 65, 580–586. Evans, D. L., & Florschuetz, L. W. (1977). Cost studies on terrestrial photovoltaic power systems with sunlight concentration. Solar Energy, 19, 255–262. Farhoodnea, M., Azaz, M., Khatib, T., & Elmenreich, W. (2015). Performance evaluation and characterization of a 3-kWp grid-connected photovoltaic system based on tropical field experimental results: New results and comparative study. Renewable and Sustainable Energy Reviews, 42, 1047–1054. IEC (International Electro-technical Commission) standard 61724 (1998). Photovoltaic system performance monitoring-guidelines for measurement, data exchange and analysis. (Accessed 14 March 2017).

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