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Ground measured data vs meteo data sets:57 locations in India_01.01.2020

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Gensol collected Actual Global Tilted Irradiation (AGTI) of 57 sites from operational projects spread across in India. It was then correlated with Expected Global Tilted Irradiation (EGTI) from the following meteo-databases namely:

1) Meteonorm-7.2
2) SolarGIS,
3) NASA (National Aeronautics and Space Administration),
4) NREL (National Renewable Energy Laboratory)

In our report, we find most representative meteo-data set for each site.

Published in: Business

Ground measured data vs meteo data sets:57 locations in India_01.01.2020

  1. 1. 1 Comparing one-year data of 57 on-ground sites Pyranometers with four most popular meteo-data sets Correlation of Meteo-Data Sets with ground measured data CONSULTING Gensol Engineering Limited 31st December 2019
  2. 2. 2 A. Introduction B. Key Takeaways for Stakeholders C. About Meteo-Databases D. Understanding Correlation coefficient D. Methodology E. Analysis & Results Index
  3. 3. 3 Gensol has carried out an exercise to correlate the Actual Global Tilted Irradiation (AGTI) (based on pyranometer) received with respect to expected GTI (EGTI) from various Meteo-databases. Gensol has collected AGTI databases of 57 sites of data from operational sites spread across in India A) Introduction The market of solar PV energy has grown in vast ways and is quite advanced. The radiation of solar PV energy plays a very important role in the development of any solar project. Solar energy generation is reliant on solar radiation of a particular location. Good solar radiation (direct & diffused) results in the higher generation and improved financial returns. Thereby, current industry relies completely on meteo- databases in the country to predict solar radiation namely; ▪ Meteonorm-7.2 ▪ SolarGIS, ▪ NASA (National Aeronautics and Space Administration), ▪ NREL (National Renewable Energy Laboratory), ▪ Actual data measured from Pyranometer (located at respective sites) Meteo-databases are categorized in two ways: ground-based (terrestrial) & satellite-based. All the databases have different uncertainties, resolution and deviation % when compared with actual data. Solar radiation varies location to location depending on latitude & longitude, azimuth angle, weather conditions etc.
  4. 4. 4 ❑ Significance of Correlation Co-efficient - Statistical measure that calculates the strength of the relationship between Actual Global Tilted Irradiation (AGTI) w.r.t. to Expected Global Tilt Irradiation (EGTI) for month on month as well as annual data. B) Key Takeaways for Stakeholders Note: *SolarGIS dataset - 33 On ground sites NREL, Meteonorm, NASA - 57 On ground sites Co-efficient Factor Range Category SolarGIS Meteonorm NASA NREL 0.8-0.9 High 58% 58% 53% 58% 0.9-1.0 Extreme 27% 21% 16% 26% Weightage of Sites in % Standard Deviation Range Category SolarGIS Meteonorm NASA NREL <2.5% Low 39% 35% 16% 0% >2.5 to <5% Medium 6% 28% 32% 7% Weightage of Sites in % ❑ Significance of Standard Deviation- Statistical measure that calculates the amount of variation between annual AGTI and EGTI for various meteo-dataset for different site
  5. 5. 5 ❑ Meteo-Database Correlation Relativeness – NREL, Meteonorm & SolarGIS* are having maximum sites (58% of total sites) with high correlation, which represents equal correlation factor for mentioned databases. B) Key Takeaways for Stakeholders Correlation Coefficient Range Relation 0.0 - 0.6 Low 0.6- 0.8 Medium 0.8 -0.9 High 0.9 - 1.0 Extreme SolarGIS Meteonorm NASA NREL Low 0% 0% 4% 0% Medium 15% 21% 28% 16% High 58% 58% 53% 58% Extreme 27% 21% 16% 26% 0% 0% 4% 0%15% 21% 28% 16% 58% 58% 53% 58% 27% 21% 16% 26% 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% SitesinPercentage(%) Meteo-Database Annual Solar Radiation Correlation – Sites in % Meteo-database with extreme & high correlation coefficient is recommended. Note: *SolarGIS dataset - 33 On ground sites NREL, Meteonorm, NASA - 57 On ground sites
  6. 6. 6 ❑ Meteo-Database Standard Deviation - Meteonorm & SolarGIS* are having maximum sites with lowest standard deviation. B) Key Takeaways for Stakeholders Standard Deviation Relation <2.5% Low >2.5 to <5% Medium >5% to <7.5% High >7.5% Extreme SolarGIS Meteonorm NASA NREL Low 39% 35% 16% 0% Medium 6% 28% 32% 7% High 18% 23% 23% 21% Extreme 36% 14% 30% 72% 39% 35% 16% 0%6% 28% 32% 7% 18% 23% 23% 21% 36% 14% 30% 72% 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% SitesinPercentage Meteo-Database Annual Solar Radiation Deviation- Sites in % Meteo-database with low & medium standard deviation is recommended. Note: *SolarGIS dataset - 33 On ground sites NREL, Meteonorm, NASA - 57 On ground sites
  7. 7. 7 Actual Global Tilted Irradiation(AGTI) • Actual site radiation data of past one year (April 2018 – March 2019) for 57 locations (as seen on map) is collected on 15 minute interval for comparative analysis. • Pyranometer at sites are placed according to the actual orientation of Plane of Array (PoA) of each project. • Pyranometer used at sites are either of First Class, second class or Secondary Standard with region-wise accuracy of bubble level ranging between 0.1° to 0.2° and is properly calibrated as per ISO standards and OEM guidelines • Where actual radiation data was not available for certain time period, AGTI values have been corrected considering near average values across the particular time period.
  8. 8. 8 Expected Global Tilted Irradiation(EGTI) • For each project, PVSyst simulation has been run considering actual tilt angle of the PV arrays installed at sites and • Four PV Syst considering a different meteo data set have been run for each site and resultant global tilted irradiation (EGTI) has been taken for each case. • Since month on month GHI to GTI gain is following similar trend for all sites and meteo-databases considered, analysis carried on EGTI or Meteo Data based GHI will not impact the results significantly • P50 & P75 EGTI values have been considered for evaluating correlation1. [1] https://www.fourmilab.ch/rpkp/experiments/analysis/zCalc.html -5.00% 0.00% 5.00% 10.00% 15.00% 20.00% 25.00% 30.00% JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC Gainin% Month-Wise Expected GHI VS Expected GTI Gain (%) SolarGIS Deviation% Meteonorm Deviation % NASA Deviation % NREL Deviation %
  9. 9. 9 C) About Meteo-Databases Data Source Satellite-Based Satellite & Ground-Based Satellite-Based Satellite & Ground Based No. of Meteo- Stations - 8350 - 1454 Time Period - Since 1999 to 2018 depending on the satellite data coverage - 1981-1990 & 1991-2010 for solar irradiation on a global scale 1983-2005 2000-2014 Temporal Resolution2 (Time Step) - Original 10/15/30 minutes depending on the satellite region - 1 minute and hourly modelled data 3-hourly -Monthly and annual average daily total 30/60 minutes interval It is essential to consider appropriate solar radiation database in order to evaluate performance of any solar photovoltaic power plants in India. In India, Meteonorm & SolarGIS databases are considered as bankable and acceptable in the market considering defined uncertainties The energy generation from a Solar Power Plant (SPP) is dependent on the solar radiation incident on earth’s surface which further depends on many factors like the length of atmospheric path, dust concentration, moisture content, scattering effect, etc. There are many trusted databases which factor in the same.
  10. 10. 10 B) About Meteo-Databases Data Spatial Resolution3 (Solar radiation) 0.25km x 0.25km 8km X 8 km 111km X 111km 10kmX10km ( SUNY Model ) 4kmX4km Uncertainty in Global Horizontal Irradiation (GHI) ±4.0% 2% to 10% 6.86% to 11.29% -20.00% to +5% Uncertainty in Direct Normal Irradiance (DNI) ±8.0% 3.5% to 20% (-4.06%) to 7.4% (-30.00%) to +8% Bankability in Country High High Medium Low [2] Temporal resolution =Revisit time of a satellite between two successive image acquisitions between the same area. [3] Spatial resolution = Refers to the number of pixels utilized in construction of the image.
  11. 11. 11 C) Understanding Correlation Coefficient • The correlation coefficient is a statistical measure that calculates the strength of the relationship between the relative movements of two variables or array. • The Correlation Coefficient4 is calculated according to the following formula: S.No Correlation Coefficient Relativity 1 -1.00 to 0.00 No relation 2 0.00 to 0.60 Low Correlation 3 0.60 to 0.80 Medium Correlation 3 0.80 to 0.90 High Correlation 4 0.90 to 1.00 Extreme Correlation [4] The_Correlation_Between_Renewable_Generation_and_Electricity_Demand_A_Case_Study_of_Portugal, March 2016 • Where ‘x’ & ‘y’ are two arrays of variables to be correlated and ‘n’ represents number of variables to be correlated. The mentioned formula can be written simply using standard excel function as follows: • The coefficient ranges from −1 to 1, where the latter indicates a positive linear correlation between the variables y and x, i.e., both variables present the same behavior (y increases as x increases), and −1 implies a negative linear correlation. • The value of 0 indicates no linear correlation between the variables. The ranges have been categorized as below: • It should be noted that the correlation coefficient is different from standard deviation. In statistics, the standard deviation is a measure of the amount of variation or dispersion of a set of values.= 𝐶𝑂𝑅𝑅𝐸𝐿(𝐴1: 𝐴15, 𝐵1: 𝐵15)
  12. 12. 12 D) Methodology North Zone East Zone South Zone West Zone Correlation Evaluation Correlation coefficient is calculated for the following two cases: CASE 1 - Month-wise AGTI values are correlated with month- wise EGTI P50 values. CASE 2 - Annual AGTI values are correlated with annual EGTI P50 & P75 values. Unavailability of SolarGIS files for some of the sites. Limitations
  13. 13. 13 E) Analysis & Results (North, West & East Zone) (Case-1) ❑ EGTI Vs AGTI Correlation Coefficient Estimation: It has been observed that average correlation factor of NREL is marginally highest followed by Meteonorm & SolarGIS. Note :1) The SolarGIS correlation factor is not included for the sites where data is not available. 0.50 0.55 0.60 0.65 0.70 0.75 0.80 0.85 0.90 0.95 1.00 Mansa Mansa FirozepurFirozepurFirozepur Jalaun Jalaun North West Delhi Mirzapur EGTI (P50) & AGTI Data Correlation Cofficient- North Zone Actual Meteonorm NREL SolarGIS NASA Punjab Uttar Pradesh 0.50 0.55 0.60 0.65 0.70 0.75 0.80 0.85 0.90 0.95 1.00 Jodhpur Jodhpur Jodhpur Jodhpur Patan Patan Gaya EGTI (P50) & AGTI Data Correlation Cofficient- West & East Zone Actual Meteonorm NREL SolarGIS NASA Rajasthan Gujarat Bihar
  14. 14. 14 E) Analysis & Results (South Zone)(Case-1) ❑ EGTI Vs AGTI Correlation Coefficient Estimation: It has been observed that average correlation factor of NREL is marginally higher followed by Meteonorm & SolarGIS. 0.60 0.65 0.70 0.75 0.80 0.85 0.90 0.95 1.00 EGTI (P50) & AGTI Data Correlation Coefficient- South Zone Actual Meteonorm NREL SolarGIS NASA Karnataka TelanganaAndhra Pradesh Note :1) The SolarGIS correlation factor is not included for the sites where data is not available.
  15. 15. 15 E) Analysis & Results (Case -2) ❑ EGTI Vs AGTI Plotting: The trend plotted by AGTI is almost similar to NREL followed by Meteonorm (showing high correlation). Whereas, at the same time, we can observe that the standard deviation is highest for NREL. Districts in North Zone 1800.00 1850.00 1900.00 1950.00 2000.00 2050.00 2100.00 2150.00 2200.00 Mansa Mansa Firozepur Firozepur Firozepur Jalaun Jalaun NorthW-Delhi Mirzapur GlobalTiltedRadiation(kwh/m2/annum) Annual EGTI (P50 &P75) Vs AGTI Actual SolarGIS P50 SolarGIS P75 Meteonorm P50 Meteonorm P75 NASA P50 NASA P75 NREL P50 NREL P75 Punjab Uttar Pradesh
  16. 16. 16 E) Analysis & Results (Case - 2) 1850.00 1900.00 1950.00 2000.00 2050.00 2100.00 2150.00 2200.00 2250.00 2300.00 2350.00 2400.00 2450.00 2500.00 Kalaburagi Bagalkot Bijapur Bijapur Bijapur Tumkur Tumkur Bidar Raichur Gulbarga Bidar Bijapur Anantapur Nagarkurnool Rangareddi Jagtial Warangal Nirmal Kamareddy Prakasam Chittoor Adilabad sangareddy Medchal Adilabad Karimnagar Guntur sangareddy Jangaon Nizamaba Nalgonda Sircilla Bhuvanagiri Peddapalli Medak Nellore Peddapalli Sircilla Jangaon Jagithyal Nizamabad GlobalTiltedRadiation(kwh/m2/annum) Annual EGTI (P50 &P75) Vs AGTI Actual SolarGIS P50 SolarGIS P75 Meteonorm P50 Meteonorm P75 NASA P50 NASA P75 NREL P50 NREL P75 Karnataka Andhra Pradesh Telangana Districts in South Zone Note :1) The SolarGIS correlation factor is not included for the sites where data is not available. 2) Average correlation coefficient is considered for sites only where SolarGIS data is available for consistency.
  17. 17. 17 E) Analysis & Results (Case - 2) Districts in West Zone & East Zone Note : 1) The SolarGIS correlation factor is not included for the sites where data is not available. 2) Average correlation coefficient is considered for sites only where SolarGIS data is available for consistency. 1850.00 1900.00 1950.00 2000.00 2050.00 2100.00 2150.00 2200.00 2250.00 2300.00 2350.00 2400.00 Jodhpur Jodhpur Jodhpur Jodhpur Patan Patan Gaya GlobalTiltedRadiation(kwh/m2/annum EGTI (P50 & P75) Vs AGTI Actual SolarGIS P50 SolarGIS P75 Meteonorm P50 Meteonorm P75 NASA P50 NASA P75 NREL P50 NREL P75 Rajasthan Gujarat Bihar
  18. 18. 18 Annexure Zone State Sr. No. Site Name District Name SolarGIS Meteonorm NASA NREL North Punjab 1 Mansa-1 Mansa 0.00 0.76 0.69 0.88 2 Mansa-2 Mansa 0.00 0.82 0.68 0.90 3 Mansa-3 Firozepur 0.00 0.83 0.59 0.90 4 Usmankhera Firozepur 0.00 0.89 0.67 0.90 5 Daulatpura Firozepur 0.00 0.91 0.62 0.93 Uttar Pradesh 6 Orai-1 Jalaun 0.00 0.75 0.92 0.79 7 Orai-2 Jalaun 0.00 0.78 0.93 0.79 8 Haidarpur North West Delhi 0.00 0.84 0.96 0.88 9 Mirzapur Mirzapur 0.00 0.83 0.85 0.87 Rajasthan 10 Khetusar Jodhpur 0.00 0.64 0.49 0.73 11 Bhadla Jodhpur 0.00 0.84 0.84 0.90 12 Khetusar Jodhpur 0.00 0.67 0.67 0.79 13 Bhadiachuran Ki Jodhpur 0.00 0.80 0.81 0.87 West Gujarat 14 Charanka Patan 0.98 0.98 0.94 0.93 15 Charanka Patan 0.97 0.99 0.94 0.94 Correlation factors between AGTI and EGTI
  19. 19. 19 Zone State Sr. No. Site Name District Name SolarGIS Meteonorm NASA NREL East Bihar 16 Jalsar & Chillam Gaya 0.83 0.82 0.75 0.91 South Karnataka 17 Gulbarga Kalaburagi 0.00 0.87 0.89 0.87 18 Bagalkot Bagalkot 0.00 0.87 0.89 0.86 19 Sindagi Bijapur 0.00 0.89 0.88 0.88 20 Muddebihal Bijapur 0.00 0.78 0.73 0.71 21 Indi Bijapur 0.00 0.91 0.91 0.88 22 Pavagada 1-38 Tumkur 0.87 0.82 0.82 0.84 23 Pavagada 1-37 Tumkur 0.87 0.82 0.82 0.84 24 Chittaguppu Bidar 0.91 0.91 0.91 0.94 25 Raichur Raichur 0.90 0.87 0.86 0.87 26 Farhatabad Gulbarga 0.85 0.88 0.82 0.87 27 Bidar Bidar 0.92 0.94 0.92 0.94 28 Bijapur Bijapur 0.00 0.92 0.92 0.91 Andhra Pradesh 29 Veerabommana Halli Anantapur 0.92 0.88 0.85 0.92 Telangana 30 Veltoor Nagarkurnool 0.00 0.92 0.87 0.84 31 Gingurthy Rangareddi 0.90 0.92 0.90 0.91 32 Mallapur Jagtial 0.91 0.92 0.88 0.87 33 Waddekothapalle Warangal 0.83 0.84 0.78 0.90 34 Bhainsa Nirmal 0.00 0.74 0.76 0.78 Correlation factors between AGTI and EGTI Annexure
  20. 20. 20 Zone State Sr. No. Site Name District Name SolarGIS Meteonorm NASA NREL South Telangana 35 Amun, Kamareddy Kamareddy 0.00 0.90 0.86 0.88 36 Rudra Prakasam 0.00 0.87 0.83 0.88 37 Avaighna Chittoor 0.00 0.85 0.75 0.91 38 Beeravelly Adilabad 0.88 0.69 0.86 0.87 39 Sadashivpet sangareddy 0.85 0.85 0.84 0.89 40 Nagaram Medchal 0.91 0.88 0.90 0.89 41 Beeravelli Adilabad 0.86 0.82 0.87 0.78 42 Vettemula Karimnagar 0.85 0.82 0.89 0.79 43 Achampet Guntur 0.80 0.78 0.79 0.80 44 Gummadidala sangareddy 0.85 0.87 0.82 0.90 45 Ghanpur Jangaon 0.84 0.85 0.81 0.88 46 Renjal Nizamaba 0.84 0.88 0.80 0.89 47 Thukkapur Nalgonda 0.80 0.84 0.83 0.84 48 Sircilla Sircilla 0.91 0.91 0.89 0.92 49 Bhuvanagiri Bhuvanagiri 0.84 0.81 0.79 0.86 50 Kalvasrirampur Peddapalli 0.75 0.82 0.72 0.82 51 Medak Medak 0.91 0.92 0.90 0.95 52 Godhur Nellore 0.89 0.87 0.86 0.89 53 Manthani Peddapalli 0.85 0.88 0.82 0.85 54 Sircilla Sircilla 0.86 0.80 0.85 0.84 55 Jangaon Jangaon 0.80 0.79 0.78 0.86 56 Jagithyal Jagithyal 0.81 0.86 0.76 0.82 57 Padmajiwadi Nizamabad 0.62 0.85 0.83 0.88 Correlation factors between AGTI and EGTI Annexure
  21. 21. 21 Email: solar@gensol.in | Web: www.gensol.in | Phone: +91 79 40068235 | Twitter: gensol_tweets Gensol Engineering Limited Corporate Office A2, 12th Floor Palladium, Opp. to Vodafone House , Corporate Road, Prahladnagar, Ahmedabad, Gujarat. India - 380015

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