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Prof. R. S. Hosmath
Assistant Professor
Dept. of Mechanical Engg.
B.V.B College of Engg. and Tech.,
Hubballi
Dr. H. Naganagouda
Director,
National Training Centre for Solar Technology,
Karnataka Power Corporation Limited,
Bangalore
Presented by
SHAHBAZ MAKANDAR A
(2BV13MES11)
M.Tech.
Energy Systems Engineering
Project Title
Studies on Grid connected 3MW Solar PV Power Plant
Karnataka Power Corporation Ltd.
Under the Guidance of
K.L.E. Society’s
B. V. Bhoomaraddi College of Engg. & Technology
Vidyanagar, Hubli 580031
(NBAACCREDITED & AUTONOMOUS INSTITUTION WITH ISO 9001-2008 CERTIFICATION)
Contents
Introduction
Statement of the Problem
Objectives
Literature Review
Site details of the SPV plant
Simulation studies of SPV power plant
Results and Discussions
Conclusions
Scope for Future work
References Energy Systems Engineering 2
Introduction
Details of PV Systems
 Major components of PV systems
 Fabrication of PV cells and Working Principle
 PV Power Generation
 Grid-connected without storage
Energy Systems Engineering 3
Fig 1. Major PV system Components (KPCL record)
Energy Systems Engineering 4
Fig 2. Solar Cells Working Principle (KPCL record)
Energy Systems Engineering 5
Fig 3. Grid-connected PV System (KPCL record)
Energy Systems Engineering 6
Statement Problem
• Energy
• SPV system
• Government Policy
Energy Systems Engineering 7
Objectives
 To simulate the climatological parameters like solar insolation, wind
speed and atmospheric temperature on “METEONORM” open-source
platform.
 To simulate the detailed operation of a solar PV based plant on
“PVSYST” platform to analyze component level performance along
with overall plant operation
 To simulate site parameters for installation of SPV system using
“HELIOSCOPE” tool.
 Experimental observation of the system behavior of the 3MW SPV
power plant through “SCADA” based system to investigate its
performance characteristics.
 To compare the Simulation and Experimental data to draw feasibility
factors for future upgradation of existing SPV power plant
Energy Systems Engineering 8
Literature Review
 Performance Evaluation of SPV Plant
 Solar Insolation availability
 SPV system Simulation Software
 SPV Technology
Energy Systems Engineering 9
Site details of the SPV Plant
Basic information of Solar PV Plant
Site details
Experimental procedure for Performance Study
Energy Systems Engineering 10
Fig 4. Block Diagram of the PV Plant [18]Energy Systems Engineering 11
Height above sea level 882m
Ambient Air
Temperature
Maximum: 40oC
Minimum: 18oC
Relative Humidity
Maximum: 99.1% (during
monsoon)
Minimum: 18.3%
Rainfall Annual average: 1549 mm
Period: 4 months
Table 1: Technical data of Solar PV [18]
Energy Systems Engineering 12
Place of Installation
Near Yalesandra Village, Kolar, Karnataka,
India
Latitude & Longitude of the place 120 53’ & 780 09’
Allotted Land Area 15 acres (10.3 acres effectively used)
Nominal Capacity of the PV Plant 3 MW
Date of Commission 27th December 2009
Owner
Karnataka Power Corporation Limited
(KPCL)
Installed by (Contractor) Titan Energy Systems Ltd. , Secunderabad
Modules Titan S6-60 series
SCADA for diagnosing and
monitoring
Yes
PCU (Inverters) 250 kW (12 Nos)
HT Transformer and switchgear for
evacuation
1.25 MVA for each MW
Table 2: General description of Yalesandra PV Plant [18]
Energy Systems Engineering 13
Two type of S6 - 60 series
modules are used
225 Wp & 240 Wp
Total number of modules 13,368 [10,152 - 225 Wp;3216 – 240 Wp]
Solar Cell material Mono-Crystalline Silicon
1 Array 24 Modules
No. of Arrays per Inverter(250
kW)
45-46 (Total 557 Arrays with 12 Inverters)
Arrays per MW
1st MW installation– 181
2nd & 3rd MW installations – 188
Total installed Solar Cells area 5.4 acre
Inclination of Modules 15o with horizontal
Table 3: Technical data of Solar PV [18]
Energy Systems Engineering 14
Type S6-60 series
Maximum Power, Pmp (W) 225 240
Maximum Power Voltage
(Vmp)
28.63 V 28.63 V
Maximum Power Current
(Imp)
7.93 A 8.12A
Open Circuit Voltage (Voc) 37.50 V 37.62V
Short Circuit Current (Isc) 8.52 A 8.55A
Module dimensions (mm) 1657 x 987 x 42
No., type and arrangement
of cells
60, Mono-Crystalline, 6 x 10
Matrix
Cell Size (mm) 156 x 156
NOCT, °C 45
Weight (Kg) 19
Glass Type and Thickness
3.2mm Thick, Low iron,
Tempered
Table 4: Module Specifications [18]
Fig 5. High efficiency PV module [24]
Energy Systems Engineering
Type
6 x 4 Module Array
(24 modules per Structure)
Material Mild Steel
Overall dimensions (mm) 6780x 6030
Coating Galvanized
Wind rating 160 km per hour
Tilt angle 15°
Foundation PCC
Fixing type Nut Bolts
Table 5: Array mounting structure at the plant [18]
Energy Systems Engineering 16
Fig 6: Typical SCADA System [19]
Energy Systems Engineering 17
Fig 7: Block Diagram of SPV Plant (KPCL record)
Energy Systems Engineering 18
Experimental Performance study
Key performance indicators
 Performance Ratio
 Radiation at the Site
 Array Conversion Efficiency
 Inverter Efficiency
 Energy Generated
Energy Systems Engineering 19
𝑷𝑹 =
𝐴𝑐𝑡𝑢𝑎𝑙 𝑟𝑒𝑎𝑑𝑖𝑛𝑔 𝑜𝑓 𝑝𝑙𝑎𝑛𝑡 𝑜𝑢𝑡𝑝𝑢𝑡 𝑖𝑛 𝑘𝑊ℎ 𝑝. 𝑚
𝐶𝑎𝑙𝑐𝑢𝑙𝑎𝑡𝑒𝑑, 𝑛𝑜𝑚𝑖𝑛𝑎𝑙 𝑝𝑙𝑎𝑛𝑡 𝑜𝑢𝑡𝑝𝑢𝑡 𝑖𝑛 𝑘𝑊ℎ 𝑝. 𝑚
𝑨𝑪𝑬 =
𝐷𝑎𝑦 𝑠𝑢𝑚 𝑔𝑒𝑛𝑒𝑟𝑎𝑡𝑖𝑜𝑛 𝑜𝑓 𝑖𝑛𝑣𝑒𝑟𝑡𝑒𝑟 𝑖𝑛 𝑊𝑎𝑡𝑡 𝐻𝑟
𝑑𝑎𝑦 𝑠𝑢𝑚 𝑖𝑟𝑟𝑎𝑑𝑖𝑎𝑛𝑐𝑒 𝑖𝑛
𝑘𝑊ℎ
𝑚2 ×
𝐶𝑒𝑙𝑙 𝑎𝑟𝑒𝑎
12
𝑖𝑛 𝑚2
𝑷𝑪𝑼 𝑬𝒇𝒇𝒊𝒄𝒊𝒆𝒏𝒄𝒚 =
(𝐶𝑢𝑚𝑢𝑙𝑎𝑡𝑖𝑣𝑒 𝑜𝑢𝑡𝑝𝑢𝑡 𝑖𝑛 𝑘𝑊ℎ)
(𝐶𝑢𝑚𝑢𝑙𝑎𝑡𝑖𝑣𝑒 𝑖𝑛𝑝𝑢𝑡 𝑖𝑛 𝑘𝑊ℎ)
× 100
𝑪𝒐𝒎𝒑𝒂𝒓𝒆 𝑮𝒓𝒊𝒅 𝑻𝒓𝒂𝒏𝒔𝒅 𝒆𝒏𝒆𝒓𝒈𝒚 𝒘𝒊𝒕𝒉 𝑬𝒙𝒑 & 𝑨𝒄𝒕 𝑮𝒆𝒏 𝒆𝒏𝒆𝒓𝒈𝒚
=
𝐷𝑎𝑦 𝑠𝑢𝑚 𝑖𝑟𝑟𝑎𝑑𝑖𝑎𝑡𝑖𝑜𝑛 𝑖𝑛
𝑊ℎ
𝑚2
𝑅𝑒𝑓𝑒𝑟𝑒𝑛𝑐𝑒 𝑖𝑟𝑟𝑎𝑑𝑖𝑎𝑡𝑖𝑜𝑛 𝑖𝑛
𝑊ℎ
𝑚2
× 𝐶𝑎𝑝𝑎𝑐𝑖𝑡𝑦 𝑜𝑓 𝑡ℎ𝑒 𝑝𝑙𝑎𝑛𝑡
FormulaeUsed
Energy Systems Engineering 20
𝐺𝐿
=
𝐷𝑖𝑓𝑓𝑒𝑟𝑒𝑛𝑐𝑒 𝑖𝑛 𝑖𝑟𝑟𝑎𝑑𝑖𝑎𝑡𝑖𝑜𝑛 𝑎𝑡 𝑔𝑟𝑖𝑑 𝑙𝑜𝑠𝑠 𝑡𝑖𝑚𝑒 𝑖𝑛
𝑊ℎ
𝑚2
𝑅𝑒𝑓𝑒𝑟𝑒𝑛𝑐𝑒 𝑖𝑟𝑟𝑎𝑑𝑖𝑎𝑡𝑖𝑜𝑛 𝑖𝑛
𝑊
𝑚2
× 𝑐𝑎𝑝𝑎𝑐𝑖𝑡𝑦 𝑜𝑓 𝑡ℎ𝑒 𝑝𝑙𝑎𝑛𝑡 𝑤𝑖𝑡ℎ 𝑙𝑜𝑠𝑠𝑒𝑠 𝑖𝑛 𝑘𝑊
MPE= 𝑖=0
𝑛
(𝐻𝑖,𝑚−𝐻𝑖,𝑐)/(𝐻𝑖,𝑚) ×100
𝑁
RMSE= 𝑖=0
𝑛
(𝐻𝑖,𝑐−𝐻𝑖,𝑚)2
𝑁
𝟏
𝟐
MBE= 𝑖=0
𝑛
(𝐻𝑖,𝑐−𝐻𝑖,𝑚)
𝑁
FormulaeUsed
Energy Systems Engineering 21
Simulation Studies of SPV power plant
METEONORM
PVSYST
HELIOSCOPE
Energy Systems Engineering 22
Fig 8: METEONORM simulation result of SPV plant [23]
Energy Systems Engineering
23
Fig 9: PVSYST simulation result of SPV plant [22]
Energy Systems Engineering 24
Fig. 10 : Helioscope simulation result of SPV plant [21]
Energy Systems Engineering
25
Results and Discussions
Fig 11. Month-wise Performance Ratio
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
PerformanceRatio(PR)
Duration, month
Energy Systems Engineering 26
0
2
4
6
8
10
12
14
16
18
1 5 9 13 17 21 25 29
July June August September
Duration, Day
Efficiency%
Fig 12. Array Conversion Efficiency for Rainy Season
Energy Systems Engineering 27
Fig 13. Array Conversion Efficiency for Winter Season
0
2
4
6
8
10
12
14
16
1 5 9 13 17 21 25 29
October November December January
Efficiency%
Duration, Day
Energy Systems Engineering 28
Fig 14. Array Conversion Efficiency for Summer Season
0
2
4
6
8
10
12
14
16
1 5 9 13 17 21 25 29
February March April MAY
Duration, Day
Efficiency%
Energy Systems Engineering 29
0
20000
40000
60000
80000
100000
120000
140000
160000
180000
200000
Duration, Month
TotalIrradianceWh/𝒎^𝟐
Fig 14. Month wise Total IrradiationEnergy Systems Engineering 30
94
95
96
97
98
99
100
1 5 9 13 17 21 25 29
April March February May
Duration, Day
Efficiency%
Fig 15. Daily basis PCU Efficiency for Summer SeasonEnergy Systems Engineering 31
94
95
96
97
98
99
100
1 5 9 13 17 21 25 29
June July August September
Duration, Day
Efficiency%
Fig 16.Daily basis PCU Efficiency for Rainy SeasonEnergy Systems Engineering 32
0
5
10
15
20
25
30
35
40
45
50
0
500
1000
1500
2000
2500
06:00 08:10 10:30 12:50 15:10 17:30
July August September Avg Module Temperature
Duration, Time
EnergygenerationinkWh
ModuleTemperature(°C)
Fig 17. Monthly average Power, Module Temperature Vs Time in Rainy SeasonEnergy Systems Engineering 33
0
2000
4000
6000
8000
10000
12000
14000
16000
18000 Expected Energy in kWh Generation in kWh Transported in kWh
Duration, Months
EnergyinkWh
Fig 18. Expected, Generated and transmitted energyEnergy Systems Engineering 34
0
5000
10000
15000
20000
25000
30000
Duration, Months
EnergyinkWh
Fig 19. Month-wise grid Transmitted Energy (Energy Meter Reading)Energy Systems Engineering 35
0
1000
2000
3000
4000
5000
6000
0
2000
4000
6000
8000
10000
12000
14000
1 5 9 13 17 21 25 29
Mono-crystalline Gen in kWh Poly-crystalline Gen in kWh
Solar radiation W/(sq.m)
SolarRadiationW/(sq.m)
EnergyGenerationinkWh
Duration, Days
Fig 20. Comparison of Mono and Poly-Crystalline panel of total energy GenerationEnergy Systems Engineering 36
100
120
140
160
180
200
220
240
1 2 3 4 5 6 7 8 9 10 11 12
Calculated Value Measured Value
Duration, Month
HourlySumIrradiance(W/m²perhr)
Fig 21. Comparison of Calculated and Measured values of Hourly Sum Irradiance (2014-15)Energy Systems Engineering 37
200
250
300
350
400
450
500
1 2 3 4 5 6 7 8 9 10 11 12
Calculated Value Measured Value
Duration, Months
GenerationinKWh
Fig 22. Comparison of Calculated and Measured values of Generation (2014-15)Energy Systems Engineering 38
0.5
1
1.5
2
2.5
3
3.5
4
4.5
1 2 3 4 5 6 7 8 9 10 11 12
Calculated Value Measured Value
Duration, Months.
WindSpeedinm/s
Fig 23. Comparison of Calculated and Measured values of Wind Speed (2014-15)Energy Systems Engineering 39
10
15
20
25
30
35
1 2 3 4 5 6 7 8 9 10 11 12
Duration, Months
AirTemperature(°C)
Fig 24. Comparison of Calculated and Measured values of Air Temperature (2014-15)Energy Systems Engineering 40
Conclusions
The following conclusions are reported based on simulation and experimental studies,
• The experimental observation of the 3MW SPV plant during Mar 2014 to Feb 2015
indicated performance ratio to have varied between 58% to 87%.
• The Array conversion efficiency of the PV panel was observed to be varying between 9%
to 15% depending upon climatic conditions at the site.
• The PCU efficiency was observed to be close to 96% but lower than the rated value of
98% as per the manufacturer specifications.
• The rated capacity of SPV solar power plant was 3MWp, but the observed peak power
at the location is limited between 2.6-2.7 MW during the observation period.
• The simulation tools used in the reported work that included METEONORM,
HELIOSCOPE and PVSYST provided an efficient Graphical User Interface making it user
friendly.
• The power generation depended on solar irradiance, module temperature and also
some extent on wind flow. Increase in irradiance increased module temperature and
generation.
• Using statistical methods consisting of Mean Bias error, Root mean square error and
Mean percentage error shows result after comparison all values shows positive results
means they overestimated in result.
Energy Systems Engineering 41
Scope for Future Work
• Studies on Earth-tester to measure leakage current and
isolation resistance of generator
• Studies on thermal imaging to detect abnormal heating in
solar modules, DC junction Boxes and Inverters.
• Studies on power quality analyzer or digital wattmeter can
be taken up to measure accurate power at Inverter side.
Energy Systems Engineering 42
References1. Arif Hepbasli, Zeyad Alsuhaibani, A key review on present status and future directions of solar energy
studies and applications in Saudi Arabia, Renewable and Sustainable Energy Reviews 15 (2011) 5021–
5050
2. Mohamed A. Eltawil and Zheng Ming Zhao, Grid-connected PV power systems: Technical and potential
problems - A review, Renewable and Sustainable Energy Reviews 14, (2010), pp. 112-129.
3. Bharathkumar M., ByregowdaH. V., Performance Evaluation of 5MW Grid connected Solar PV Power Plant
Established in Karanataka, International Journal of Innovative Research in Science, Engineering and
Technology (An ISO 3297: 2007 Certified Organization) Vol. 3, Issue 6, June 2014
4. HemakshiBhoye and Gaurang Sharma, An analysis of One MW PV solar power plant design, International
Journal of Advanced Research in Electrical, Electronics and Instrumentation Engineering (An ISO 3297:
2007 Certified Organization)Vol. 3, Issue 1, January 2014
5. Jasmina Radosavljevic, Amelija Dordevic, Defining of the Intensity of Solar Radiation on Horizontal and
Oblique Surfaces on Earth, Series: Working and Living Environmental Protection Vol. 2, 2001, pp. 77 – 86
6. K. S. Sidhu, Non- Conventional Energy Resources, 2005, http://indiacore.com/ bulletin/ kssidhu-non-
conventional-energy-resources.pdf
7. Yang Hong xing, Li Yutong, Potential of building-integrated PV applications, International Journal of Low
Carbon Technologies 2/3,11th August 2015, http://ijlct.oxfordjournals.org/
8. G. Lopez, F.J. Batlles, J. Tovar-Pescador, Selection of input parameters to model direct solar irradiance by
using artificial neural networks, Energy 30 (2005), pp.1675–1684
9. Marco Bindi, Francesco Miglietta, Gaetano zipoli, Different methods for separating diffuse and direct
components of solar radiation and their application in crop growth models, Climate Research, Vol. 2:
9thJuly 2006 , pp. 47-54,
10.Damon Turney, Vasilis Fthenakis, Environmental impacts from the installation and operation of large-scale
solar power plants, Renewable and Sustainable Energy Reviews 15 (2011) 3261– 3270
11. BhubaneswariParida, S. Iniyan, RankoGoic, A review of solar PV technologies, Renewable and
Sustainable Energy Reviews 15 (2011) 1625–1636
12. Stone, Experimental Solar Radiation Data and Statistical Methods, International Energy and
Environmental Foundations, ISSN 2076-2895(print) ISSN 2076-2909 (online), 2010
13. Abdelfettah Barhdadi, Mouncef Bennis, PVGIS approach for assessing the performances of
the firstPV grid-connected power plant in Morocco, Senior Associate of the Abdus Salam ICTP),
2007, abdelbar@fsr.ac.ma
14. P. W. Suckling ,J.E. Hay, Modelling Direct, Diffuse, and Total Solar Radiation for Cloudless Days,
Manuscript received 14 June 1976; in revised form 1 October 19761
15. Jeff Dozier, A Clear-Sky Spectral Solar Radiation Model for Snow-Covered Mountainous
Terrain, Water Resources Research, Vol. 16, no. 4, August 1980, Pages 709-718
16. J. Aristizabal, G. Gordillo, Performance monitoring results of the first grid- connected BIPV
system in Columbia, Prof of Science Direct Renewable Energy 33 (2008) 2475-2484
18. K. Jairaj, Energy scenario in Karnataka, power point presentation, Energy Dept., Govt. of
Karnataka, Divecha Centre for Climate Change, report IISC-DCCC 11 RE, 1 August 2011
(http://www.mnre.gov.in/solar-conclave2010.htm).
19. https://en.wikipedia.org/wiki/SCADA
20. http://karnatakapower.com/portfolio/yelesandra-solar-pv-plant-kolar-dist
21. https://helioscope.folsomlabs.com
22. http://files.pvsyst.com/help
23. http://meteonorm.com/images/uploads/downloads/flyer_meteonorm_7.pdf
24. http://www.titan-energy.com/datasheets/TITAN-S6-60-2BB.pdf
Energy Systems Engineering 44
Thank You
Energy Systems Engineering 45

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Study of Large Scale Grid interactive Solar PV power plant

  • 1. Prof. R. S. Hosmath Assistant Professor Dept. of Mechanical Engg. B.V.B College of Engg. and Tech., Hubballi Dr. H. Naganagouda Director, National Training Centre for Solar Technology, Karnataka Power Corporation Limited, Bangalore Presented by SHAHBAZ MAKANDAR A (2BV13MES11) M.Tech. Energy Systems Engineering Project Title Studies on Grid connected 3MW Solar PV Power Plant Karnataka Power Corporation Ltd. Under the Guidance of K.L.E. Society’s B. V. Bhoomaraddi College of Engg. & Technology Vidyanagar, Hubli 580031 (NBAACCREDITED & AUTONOMOUS INSTITUTION WITH ISO 9001-2008 CERTIFICATION)
  • 2. Contents Introduction Statement of the Problem Objectives Literature Review Site details of the SPV plant Simulation studies of SPV power plant Results and Discussions Conclusions Scope for Future work References Energy Systems Engineering 2
  • 3. Introduction Details of PV Systems  Major components of PV systems  Fabrication of PV cells and Working Principle  PV Power Generation  Grid-connected without storage Energy Systems Engineering 3
  • 4. Fig 1. Major PV system Components (KPCL record) Energy Systems Engineering 4
  • 5. Fig 2. Solar Cells Working Principle (KPCL record) Energy Systems Engineering 5
  • 6. Fig 3. Grid-connected PV System (KPCL record) Energy Systems Engineering 6
  • 7. Statement Problem • Energy • SPV system • Government Policy Energy Systems Engineering 7
  • 8. Objectives  To simulate the climatological parameters like solar insolation, wind speed and atmospheric temperature on “METEONORM” open-source platform.  To simulate the detailed operation of a solar PV based plant on “PVSYST” platform to analyze component level performance along with overall plant operation  To simulate site parameters for installation of SPV system using “HELIOSCOPE” tool.  Experimental observation of the system behavior of the 3MW SPV power plant through “SCADA” based system to investigate its performance characteristics.  To compare the Simulation and Experimental data to draw feasibility factors for future upgradation of existing SPV power plant Energy Systems Engineering 8
  • 9. Literature Review  Performance Evaluation of SPV Plant  Solar Insolation availability  SPV system Simulation Software  SPV Technology Energy Systems Engineering 9
  • 10. Site details of the SPV Plant Basic information of Solar PV Plant Site details Experimental procedure for Performance Study Energy Systems Engineering 10
  • 11. Fig 4. Block Diagram of the PV Plant [18]Energy Systems Engineering 11
  • 12. Height above sea level 882m Ambient Air Temperature Maximum: 40oC Minimum: 18oC Relative Humidity Maximum: 99.1% (during monsoon) Minimum: 18.3% Rainfall Annual average: 1549 mm Period: 4 months Table 1: Technical data of Solar PV [18] Energy Systems Engineering 12
  • 13. Place of Installation Near Yalesandra Village, Kolar, Karnataka, India Latitude & Longitude of the place 120 53’ & 780 09’ Allotted Land Area 15 acres (10.3 acres effectively used) Nominal Capacity of the PV Plant 3 MW Date of Commission 27th December 2009 Owner Karnataka Power Corporation Limited (KPCL) Installed by (Contractor) Titan Energy Systems Ltd. , Secunderabad Modules Titan S6-60 series SCADA for diagnosing and monitoring Yes PCU (Inverters) 250 kW (12 Nos) HT Transformer and switchgear for evacuation 1.25 MVA for each MW Table 2: General description of Yalesandra PV Plant [18] Energy Systems Engineering 13
  • 14. Two type of S6 - 60 series modules are used 225 Wp & 240 Wp Total number of modules 13,368 [10,152 - 225 Wp;3216 – 240 Wp] Solar Cell material Mono-Crystalline Silicon 1 Array 24 Modules No. of Arrays per Inverter(250 kW) 45-46 (Total 557 Arrays with 12 Inverters) Arrays per MW 1st MW installation– 181 2nd & 3rd MW installations – 188 Total installed Solar Cells area 5.4 acre Inclination of Modules 15o with horizontal Table 3: Technical data of Solar PV [18] Energy Systems Engineering 14
  • 15. Type S6-60 series Maximum Power, Pmp (W) 225 240 Maximum Power Voltage (Vmp) 28.63 V 28.63 V Maximum Power Current (Imp) 7.93 A 8.12A Open Circuit Voltage (Voc) 37.50 V 37.62V Short Circuit Current (Isc) 8.52 A 8.55A Module dimensions (mm) 1657 x 987 x 42 No., type and arrangement of cells 60, Mono-Crystalline, 6 x 10 Matrix Cell Size (mm) 156 x 156 NOCT, °C 45 Weight (Kg) 19 Glass Type and Thickness 3.2mm Thick, Low iron, Tempered Table 4: Module Specifications [18] Fig 5. High efficiency PV module [24] Energy Systems Engineering
  • 16. Type 6 x 4 Module Array (24 modules per Structure) Material Mild Steel Overall dimensions (mm) 6780x 6030 Coating Galvanized Wind rating 160 km per hour Tilt angle 15° Foundation PCC Fixing type Nut Bolts Table 5: Array mounting structure at the plant [18] Energy Systems Engineering 16
  • 17. Fig 6: Typical SCADA System [19] Energy Systems Engineering 17
  • 18. Fig 7: Block Diagram of SPV Plant (KPCL record) Energy Systems Engineering 18
  • 19. Experimental Performance study Key performance indicators  Performance Ratio  Radiation at the Site  Array Conversion Efficiency  Inverter Efficiency  Energy Generated Energy Systems Engineering 19
  • 20. 𝑷𝑹 = 𝐴𝑐𝑡𝑢𝑎𝑙 𝑟𝑒𝑎𝑑𝑖𝑛𝑔 𝑜𝑓 𝑝𝑙𝑎𝑛𝑡 𝑜𝑢𝑡𝑝𝑢𝑡 𝑖𝑛 𝑘𝑊ℎ 𝑝. 𝑚 𝐶𝑎𝑙𝑐𝑢𝑙𝑎𝑡𝑒𝑑, 𝑛𝑜𝑚𝑖𝑛𝑎𝑙 𝑝𝑙𝑎𝑛𝑡 𝑜𝑢𝑡𝑝𝑢𝑡 𝑖𝑛 𝑘𝑊ℎ 𝑝. 𝑚 𝑨𝑪𝑬 = 𝐷𝑎𝑦 𝑠𝑢𝑚 𝑔𝑒𝑛𝑒𝑟𝑎𝑡𝑖𝑜𝑛 𝑜𝑓 𝑖𝑛𝑣𝑒𝑟𝑡𝑒𝑟 𝑖𝑛 𝑊𝑎𝑡𝑡 𝐻𝑟 𝑑𝑎𝑦 𝑠𝑢𝑚 𝑖𝑟𝑟𝑎𝑑𝑖𝑎𝑛𝑐𝑒 𝑖𝑛 𝑘𝑊ℎ 𝑚2 × 𝐶𝑒𝑙𝑙 𝑎𝑟𝑒𝑎 12 𝑖𝑛 𝑚2 𝑷𝑪𝑼 𝑬𝒇𝒇𝒊𝒄𝒊𝒆𝒏𝒄𝒚 = (𝐶𝑢𝑚𝑢𝑙𝑎𝑡𝑖𝑣𝑒 𝑜𝑢𝑡𝑝𝑢𝑡 𝑖𝑛 𝑘𝑊ℎ) (𝐶𝑢𝑚𝑢𝑙𝑎𝑡𝑖𝑣𝑒 𝑖𝑛𝑝𝑢𝑡 𝑖𝑛 𝑘𝑊ℎ) × 100 𝑪𝒐𝒎𝒑𝒂𝒓𝒆 𝑮𝒓𝒊𝒅 𝑻𝒓𝒂𝒏𝒔𝒅 𝒆𝒏𝒆𝒓𝒈𝒚 𝒘𝒊𝒕𝒉 𝑬𝒙𝒑 & 𝑨𝒄𝒕 𝑮𝒆𝒏 𝒆𝒏𝒆𝒓𝒈𝒚 = 𝐷𝑎𝑦 𝑠𝑢𝑚 𝑖𝑟𝑟𝑎𝑑𝑖𝑎𝑡𝑖𝑜𝑛 𝑖𝑛 𝑊ℎ 𝑚2 𝑅𝑒𝑓𝑒𝑟𝑒𝑛𝑐𝑒 𝑖𝑟𝑟𝑎𝑑𝑖𝑎𝑡𝑖𝑜𝑛 𝑖𝑛 𝑊ℎ 𝑚2 × 𝐶𝑎𝑝𝑎𝑐𝑖𝑡𝑦 𝑜𝑓 𝑡ℎ𝑒 𝑝𝑙𝑎𝑛𝑡 FormulaeUsed Energy Systems Engineering 20
  • 21. 𝐺𝐿 = 𝐷𝑖𝑓𝑓𝑒𝑟𝑒𝑛𝑐𝑒 𝑖𝑛 𝑖𝑟𝑟𝑎𝑑𝑖𝑎𝑡𝑖𝑜𝑛 𝑎𝑡 𝑔𝑟𝑖𝑑 𝑙𝑜𝑠𝑠 𝑡𝑖𝑚𝑒 𝑖𝑛 𝑊ℎ 𝑚2 𝑅𝑒𝑓𝑒𝑟𝑒𝑛𝑐𝑒 𝑖𝑟𝑟𝑎𝑑𝑖𝑎𝑡𝑖𝑜𝑛 𝑖𝑛 𝑊 𝑚2 × 𝑐𝑎𝑝𝑎𝑐𝑖𝑡𝑦 𝑜𝑓 𝑡ℎ𝑒 𝑝𝑙𝑎𝑛𝑡 𝑤𝑖𝑡ℎ 𝑙𝑜𝑠𝑠𝑒𝑠 𝑖𝑛 𝑘𝑊 MPE= 𝑖=0 𝑛 (𝐻𝑖,𝑚−𝐻𝑖,𝑐)/(𝐻𝑖,𝑚) ×100 𝑁 RMSE= 𝑖=0 𝑛 (𝐻𝑖,𝑐−𝐻𝑖,𝑚)2 𝑁 𝟏 𝟐 MBE= 𝑖=0 𝑛 (𝐻𝑖,𝑐−𝐻𝑖,𝑚) 𝑁 FormulaeUsed Energy Systems Engineering 21
  • 22. Simulation Studies of SPV power plant METEONORM PVSYST HELIOSCOPE Energy Systems Engineering 22
  • 23. Fig 8: METEONORM simulation result of SPV plant [23] Energy Systems Engineering 23
  • 24. Fig 9: PVSYST simulation result of SPV plant [22] Energy Systems Engineering 24
  • 25. Fig. 10 : Helioscope simulation result of SPV plant [21] Energy Systems Engineering 25
  • 26. Results and Discussions Fig 11. Month-wise Performance Ratio 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 PerformanceRatio(PR) Duration, month Energy Systems Engineering 26
  • 27. 0 2 4 6 8 10 12 14 16 18 1 5 9 13 17 21 25 29 July June August September Duration, Day Efficiency% Fig 12. Array Conversion Efficiency for Rainy Season Energy Systems Engineering 27
  • 28. Fig 13. Array Conversion Efficiency for Winter Season 0 2 4 6 8 10 12 14 16 1 5 9 13 17 21 25 29 October November December January Efficiency% Duration, Day Energy Systems Engineering 28
  • 29. Fig 14. Array Conversion Efficiency for Summer Season 0 2 4 6 8 10 12 14 16 1 5 9 13 17 21 25 29 February March April MAY Duration, Day Efficiency% Energy Systems Engineering 29
  • 31. 94 95 96 97 98 99 100 1 5 9 13 17 21 25 29 April March February May Duration, Day Efficiency% Fig 15. Daily basis PCU Efficiency for Summer SeasonEnergy Systems Engineering 31
  • 32. 94 95 96 97 98 99 100 1 5 9 13 17 21 25 29 June July August September Duration, Day Efficiency% Fig 16.Daily basis PCU Efficiency for Rainy SeasonEnergy Systems Engineering 32
  • 33. 0 5 10 15 20 25 30 35 40 45 50 0 500 1000 1500 2000 2500 06:00 08:10 10:30 12:50 15:10 17:30 July August September Avg Module Temperature Duration, Time EnergygenerationinkWh ModuleTemperature(°C) Fig 17. Monthly average Power, Module Temperature Vs Time in Rainy SeasonEnergy Systems Engineering 33
  • 34. 0 2000 4000 6000 8000 10000 12000 14000 16000 18000 Expected Energy in kWh Generation in kWh Transported in kWh Duration, Months EnergyinkWh Fig 18. Expected, Generated and transmitted energyEnergy Systems Engineering 34
  • 35. 0 5000 10000 15000 20000 25000 30000 Duration, Months EnergyinkWh Fig 19. Month-wise grid Transmitted Energy (Energy Meter Reading)Energy Systems Engineering 35
  • 36. 0 1000 2000 3000 4000 5000 6000 0 2000 4000 6000 8000 10000 12000 14000 1 5 9 13 17 21 25 29 Mono-crystalline Gen in kWh Poly-crystalline Gen in kWh Solar radiation W/(sq.m) SolarRadiationW/(sq.m) EnergyGenerationinkWh Duration, Days Fig 20. Comparison of Mono and Poly-Crystalline panel of total energy GenerationEnergy Systems Engineering 36
  • 37. 100 120 140 160 180 200 220 240 1 2 3 4 5 6 7 8 9 10 11 12 Calculated Value Measured Value Duration, Month HourlySumIrradiance(W/m²perhr) Fig 21. Comparison of Calculated and Measured values of Hourly Sum Irradiance (2014-15)Energy Systems Engineering 37
  • 38. 200 250 300 350 400 450 500 1 2 3 4 5 6 7 8 9 10 11 12 Calculated Value Measured Value Duration, Months GenerationinKWh Fig 22. Comparison of Calculated and Measured values of Generation (2014-15)Energy Systems Engineering 38
  • 39. 0.5 1 1.5 2 2.5 3 3.5 4 4.5 1 2 3 4 5 6 7 8 9 10 11 12 Calculated Value Measured Value Duration, Months. WindSpeedinm/s Fig 23. Comparison of Calculated and Measured values of Wind Speed (2014-15)Energy Systems Engineering 39
  • 40. 10 15 20 25 30 35 1 2 3 4 5 6 7 8 9 10 11 12 Duration, Months AirTemperature(°C) Fig 24. Comparison of Calculated and Measured values of Air Temperature (2014-15)Energy Systems Engineering 40
  • 41. Conclusions The following conclusions are reported based on simulation and experimental studies, • The experimental observation of the 3MW SPV plant during Mar 2014 to Feb 2015 indicated performance ratio to have varied between 58% to 87%. • The Array conversion efficiency of the PV panel was observed to be varying between 9% to 15% depending upon climatic conditions at the site. • The PCU efficiency was observed to be close to 96% but lower than the rated value of 98% as per the manufacturer specifications. • The rated capacity of SPV solar power plant was 3MWp, but the observed peak power at the location is limited between 2.6-2.7 MW during the observation period. • The simulation tools used in the reported work that included METEONORM, HELIOSCOPE and PVSYST provided an efficient Graphical User Interface making it user friendly. • The power generation depended on solar irradiance, module temperature and also some extent on wind flow. Increase in irradiance increased module temperature and generation. • Using statistical methods consisting of Mean Bias error, Root mean square error and Mean percentage error shows result after comparison all values shows positive results means they overestimated in result. Energy Systems Engineering 41
  • 42. Scope for Future Work • Studies on Earth-tester to measure leakage current and isolation resistance of generator • Studies on thermal imaging to detect abnormal heating in solar modules, DC junction Boxes and Inverters. • Studies on power quality analyzer or digital wattmeter can be taken up to measure accurate power at Inverter side. Energy Systems Engineering 42
  • 43. References1. Arif Hepbasli, Zeyad Alsuhaibani, A key review on present status and future directions of solar energy studies and applications in Saudi Arabia, Renewable and Sustainable Energy Reviews 15 (2011) 5021– 5050 2. Mohamed A. Eltawil and Zheng Ming Zhao, Grid-connected PV power systems: Technical and potential problems - A review, Renewable and Sustainable Energy Reviews 14, (2010), pp. 112-129. 3. Bharathkumar M., ByregowdaH. V., Performance Evaluation of 5MW Grid connected Solar PV Power Plant Established in Karanataka, International Journal of Innovative Research in Science, Engineering and Technology (An ISO 3297: 2007 Certified Organization) Vol. 3, Issue 6, June 2014 4. HemakshiBhoye and Gaurang Sharma, An analysis of One MW PV solar power plant design, International Journal of Advanced Research in Electrical, Electronics and Instrumentation Engineering (An ISO 3297: 2007 Certified Organization)Vol. 3, Issue 1, January 2014 5. Jasmina Radosavljevic, Amelija Dordevic, Defining of the Intensity of Solar Radiation on Horizontal and Oblique Surfaces on Earth, Series: Working and Living Environmental Protection Vol. 2, 2001, pp. 77 – 86 6. K. S. Sidhu, Non- Conventional Energy Resources, 2005, http://indiacore.com/ bulletin/ kssidhu-non- conventional-energy-resources.pdf 7. Yang Hong xing, Li Yutong, Potential of building-integrated PV applications, International Journal of Low Carbon Technologies 2/3,11th August 2015, http://ijlct.oxfordjournals.org/ 8. G. Lopez, F.J. Batlles, J. Tovar-Pescador, Selection of input parameters to model direct solar irradiance by using artificial neural networks, Energy 30 (2005), pp.1675–1684 9. Marco Bindi, Francesco Miglietta, Gaetano zipoli, Different methods for separating diffuse and direct components of solar radiation and their application in crop growth models, Climate Research, Vol. 2: 9thJuly 2006 , pp. 47-54, 10.Damon Turney, Vasilis Fthenakis, Environmental impacts from the installation and operation of large-scale solar power plants, Renewable and Sustainable Energy Reviews 15 (2011) 3261– 3270
  • 44. 11. BhubaneswariParida, S. Iniyan, RankoGoic, A review of solar PV technologies, Renewable and Sustainable Energy Reviews 15 (2011) 1625–1636 12. Stone, Experimental Solar Radiation Data and Statistical Methods, International Energy and Environmental Foundations, ISSN 2076-2895(print) ISSN 2076-2909 (online), 2010 13. Abdelfettah Barhdadi, Mouncef Bennis, PVGIS approach for assessing the performances of the firstPV grid-connected power plant in Morocco, Senior Associate of the Abdus Salam ICTP), 2007, abdelbar@fsr.ac.ma 14. P. W. Suckling ,J.E. Hay, Modelling Direct, Diffuse, and Total Solar Radiation for Cloudless Days, Manuscript received 14 June 1976; in revised form 1 October 19761 15. Jeff Dozier, A Clear-Sky Spectral Solar Radiation Model for Snow-Covered Mountainous Terrain, Water Resources Research, Vol. 16, no. 4, August 1980, Pages 709-718 16. J. Aristizabal, G. Gordillo, Performance monitoring results of the first grid- connected BIPV system in Columbia, Prof of Science Direct Renewable Energy 33 (2008) 2475-2484 18. K. Jairaj, Energy scenario in Karnataka, power point presentation, Energy Dept., Govt. of Karnataka, Divecha Centre for Climate Change, report IISC-DCCC 11 RE, 1 August 2011 (http://www.mnre.gov.in/solar-conclave2010.htm). 19. https://en.wikipedia.org/wiki/SCADA 20. http://karnatakapower.com/portfolio/yelesandra-solar-pv-plant-kolar-dist 21. https://helioscope.folsomlabs.com 22. http://files.pvsyst.com/help 23. http://meteonorm.com/images/uploads/downloads/flyer_meteonorm_7.pdf 24. http://www.titan-energy.com/datasheets/TITAN-S6-60-2BB.pdf Energy Systems Engineering 44
  • 45. Thank You Energy Systems Engineering 45