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by Sainu Franco, V.R.Mandla and Nikhil.P.G School of Mechanical and Building Sciences (SMBS),

14th Annual International Conference and Exhibition on Geospatial Information Technology and Applications. Estimation of Power Generation Potential of Bright Roof- Areas and Photovoltaic Sizing in Hyderabad City using Geospatial technology. by Sainu Franco, V.R.Mandla and Nikhil.P.G

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by Sainu Franco, V.R.Mandla and Nikhil.P.G School of Mechanical and Building Sciences (SMBS),

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  1. 14th Annual International Conference and Exhibition on Geospatial Information Technology and Applications Estimation of Power Generation Potential of Bright Roof- Areas and Photovoltaic Sizing in Hyderabad City using Geospatial technology by Sainu Franco, V.R.Mandla and Nikhil.P.G School of Mechanical and Building Sciences (SMBS), VIT University, Vellore, TamilNadu, India.

  2. Introduction • The harbinger of economic growth and industrial development of any country is power generation. • This causes GHG emissions and depletion of fossil fuels. • Solar electricity has the potential to offset these negative impacts. 14th Annual International Conference and Exhibition on Geospatial Information Technology and Applications

  3. Objective • The calculation of roof area suitable for solar applications is done by analyzing available geospatial technology. • This study also develops an algorithm to estimate the total PV system components, using analytical methods. • The details of the power plant capacity required for 1 MW is also discussed. • The proposed results help the design engineers to fix the system and space requirements. 14th Annual International Conference and Exhibition on Geospatial Information Technology and Applications

  4. I.I. Data sources • In order to identify and calculate the bright roof top areas the visible, near infrared (VNIR) and thermal bands of Terra/ASTER level 1B acquired with a spatial resolution of 15 m was analyzed. 14th Annual International Conference and Exhibition on Geospatial Information Technology and Applications

  5. I.2 ASTER characteristics • The ASTER instrument acquires surface data in the visible to near- infrared (three bands at 15m per pixel), short-wave infrared (six bands at 30m per pixel) and thermal infrared (five bands at 90m per pixel) wavelength regions of the electromagnetic spectrum 14th Annual International Conference and Exhibition on Geospatial Information Technology and Applications

  6. I. 3. Study Area 14th Annual International Conference and Exhibition on Geospatial Information Technology and Applications

  7. I. 3. Study Area • Hyderabad, is the capital of Andhra Pradesh, India. It is one of the largest metropolitan city of India . • Hyderabad is situated on Deccan plateau, located in North West of Andhra Pradesh. Situated on 17° 22' 31" North latitude and 78° 28' 27" East longitude it has an average elevation of about 536 metres above sea level (1,607 ft). 14th Annual International Conference and Exhibition on Geospatial Information Technology and Applications

  8. II. Classification Accuracy Assessment: Supervised and Unsupervised classification Supervised classification techniques include Parallelepiped, Minimum Distance, Mahalanobis Distance, Maximum Likelihood, Spectral Angle Mapper (SAM) Unsupervised classification includes ISO-Data and K-Means techniques. 14th Annual International Conference and Exhibition on Geospatial Information Technology and Applications

  9. II. Post Classification: • Post classification tools classify rule images to calculate class statistics and confusion matrices to apply majority and minority analysis in classifying images 14th Annual International Conference and Exhibition on Geospatial Information Technology and Applications

  10. Fig: Classification accuracy using various classifiers Fig: Kappa coefficients values for various classifiers Classification accuracy using various classifiers III. 2. Classification Accuracy (Source: Sainu & Ravibabu, 2012, IJEE) 14th Annual International Conference and Exhibition on Geospatial Information Technology and Applications

  11. Fig: Classification image of study area using SVM Classified Image 14th Annual International Conference and Exhibition on Geospatial Information Technology and Applications

  12. Fig: Shows bright roof area extraction using Google earth Scale 1: 65m Bright Roof Area Extraction 14th Annual International Conference and Exhibition on Geospatial Information Technology and Applications

  13. 14th Annual International Conference and Exhibition on Geospatial Information Technology and Applications

  14. DC Load AC Load Photovoltaic System Flowchart Solar Radiation Battery Bank PV Module Inverter 14th Annual International Conference and Exhibition on Geospatial Information Technology and Applications

  15. Start Read PV module input data Perform calculations for Module sizing Read load data Fix the inverter size Read weather data Print the values of Number of modules End PV Sizing Algorithm 14th Annual International Conference and Exhibition on Geospatial Information Technology and Applications

  16. Nps = (Vdc/Vm) (1) • Npp = (Pc / (W X Nps) (2) • Ahd = (Im X hs X 0.9 X 0.9 X Npp) (3) • Wht = (Ahd X Vdc X Ei) (4) • Nar = (Npp X Isc X 1.3/Ar) (5) • Area of the modules required = 0.64 X Nps X Npp (6) 14th Annual International Conference and Exhibition on Geospatial Information Technology and Applications

  17. Table: Shows Module Inverter parameters and Radiation input

  18. Table : Shows results of module sizing using simulation

  19. Conclusion • The available bright roof area in Hyderabad suffices for meeting 40% of the total power requirement of MCH. • Much higher accuracy can be achieved if technically advanced datasets of LIDAR or photogrammetry are used. • This study would not have been possible without the help of Geospatial data and it has proved to be an invaluable tool in studies of present scale and also at macro level. 14th Annual International Conference and Exhibition on Geospatial Information Technology and Applications

  20. References • APCPDCL (www.apcentralpower.com/ ) accessed on 18-12-2011. • Article on “Power Consumption Spirals”, The Hindu March 05, 2009. • Vinod Kumar Sharma, Antonio Colangelo and Guiseppe Spagna, 1995; Photovoltaic technology: Basic concepts, Sizing of a stand alone photovoltaic system for domestic applications and preliminary economic analysis; Energy Convers. Mgmt, Vol.36, No.3, pp 161-174 • Fragaki.A and Markvart.T, 2008; Stand-alone PV system design: Results using a new sizing approach; Renewable Energy 33:162-167 • Uzunoglu.M, Onar.O.C and Alam.M.S, 2009; Modelling, control and simulation of a PV/FC/UC based hybrid power generation system for stand alone applications; Renewable Energy 34: 509-520 • Rodolfo Dufo- Lopez, Jose.L, Bernal Agustin, Jose.M .Yusta.Loyo, Jose.A.Dominguez • Navarro, Ignacio.J, Ramirez Rosado, Juan Lujano, Ismael Aso, 2011; Multi objective optimization minimizing cost and life cycle emissions of stand-alone PV-wind-diesel systems with battery storage; Applied Energy 88: 4033-4041. • Kaushika.N.D, Nalini.K.Gautam and Kshitiz Kaushik, 2005; Simulation model for sizing of stand alone solar PV system with inter connected array; Solar Energy materials & Solar Cells 85: 499-51 • Sainu Franco, Usha, M., Ravibabu, M.V., Jothimani, P., 2011 ; Accuracy assessment of image classification techniques on aster data for landuse and landcover, Proceedings of 2nd International Conference on Advances in Mechanical, Manufacturing and Building Sciences (ICAMB-2012), 09-11 Jan, 2012, Organized by VIT University, India. 14th Annual International Conference and Exhibition on Geospatial Information Technology and Applications

  21. Acknowledgment Authors would like to thank .. Director, CDMM, VIT University for permitting to utilize GIS lab Dr. Kamal Jain, Professor, Civil Engineering Department, IIT-Roorkee for providing necessary data for this study. Mr. Peter Paul, Head, Survey & Mapping SAP SPATIAL SERVICES Hyderabad for sharing spatial data 14th Annual International Conference and Exhibition on Geospatial Information Technology and Applications

  22. Thank you for your kind attention..!

  23. Nomenclature Nps number of modules in series Vdc system voltage Vm nominal voltage of the module Npp number of modules in parallel W rated wattage of module Pc plant installed capacity in Watts Ahd daily ampere hours generated Im max. current rating of module hs hours of bright sunshine Wht sizing of Charge Controller Ei efficiency of inverter Nar number of sub arrays and regulators Isc short circuit current; Ar current rating of charge controller T8 min temperature at site; G1 Avg of mean monthly global radiation 14th Annual International Conference and Exhibition on Geospatial Information Technology and Applications

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