City - Scale Spatial Data Infrastructure for Solar Photovoltaic Energy Generation Assessment

  • Authors

    • R Gowri Shankar Rao
    • N K. Rayaguru
    • N G.Renganathan
    • Sunil Kumar Thakur
    2018-09-01
    https://doi.org/10.14419/ijet.v7i3.34.18705
  • Solar PV, GIS software, Infrastructure, Urban planning, S./’ patial data infrastructure(SDI)
  • Spatial data plays an vital  role in decision-making for development of smart cities.  As it is very evident that  the development of   smart and sustainable city  mainly depends on its physical infrastructure such as intelligent transportation, smart energy, smart metering etc., This paper  provides an analysis  which aims  using the  spatial data infrastructure  tools  for estimation of  the  region  based  solar PV potential  generation  for a specific urban region . This analysis would afford a great insight in deciding a city scaled potential energy production and planning,  an estimate of the geographical PV potentials for solar power generation is adopted.  The total PV potential is evaluated for  a specific defined area and compared with the local electricity demand. The outcomes comprise of an initial valuation of the town's solar potential that can be used to upkeep organization decisions regarding reserves in solar systems.  Successful implementation of SDI  finally depends on the political governance and  their framing policies.

  • References

    1. [1] KatrinaAdam,VictoriaHoolohan,JamesGooding,ThomasKnowland,CatherineS.E.Bale, Alison S.Tomlin, Methodologies for city-scale assessment of renewable energy generation potential to inform strategic energy infrastructure investment, Cities ,Volume 54, May 2016, Pp. 45-56.

      [2] Thomas Held, PVMAPS: Software tools and data for the estimation of solar radiation and photovoltaic module performance over large geographical areas, Solar Energy Volume 142, 15 January 2017, Pages 171-181.

      [3] Yan-wei Sun a , Angela Hof b , Run Wang a,n , Jian Liu a , Yan-jie Lin a , De-wei Yang,GIS-based approach for potential analysis of solar PV generation at the regional scale: A case study of Fujian Province, Energy Policy 58 (2013) ,pp.248–259.

      [4] Sergio Castellanos , Deborah A Sunte, and Daniel M Kammen,, Rooftop solar photovoltaic potential in cities: how scalable are assessment approaches?, Environ. Res. Lett. 12 (2017) 125005.

      [5] ElieserTarigan , Djuwari,LasmanPurba,Assessment of PV Power Generation for Household in Surabaya Using SolarGIS–pvPlanner Simulation, Energy Procedia , Volume 47, 2014, Pages 85-93.

      [6] Zulkiflee Abd Latif1, Nurul Ain Mohd Zaki12, Siti Aekbal Salleh, GIS-based Estimation of Rooftop Solar Photovoltaic Potential using LiDAR, IEEE 8th International Colloquium on Signal Processing and its Applications , 2012.

      [7] Zulkiflee Abd Latif1, Nurul Ain Mohd Zaki12, Siti Aekbal Salleh, GIS-based Estimation of Rooftop Solar Photovoltaic Potential using LiDAR, IEEE 8th International Colloquium on Signal Processing and its Applications , 2012.

      [8] GIS for Renewable Energy,ArcNews magazine, ESRI, 2008

      [9] Steven Jige Quana*, Qi Lia, Godfried Augenbroea, Jason Browna, Perry Pei-Ju Yanga A GIS-based Energy Balance Modeling System for Urban Solar Buildings, Energy Procedia 75 ( 2015 ) 2946 – 2952.

      [10] Sabo Mahmoud Lurwan, Mohammed Oludare Idrees, Goma Bedawi Ahmed, Usman Salihu Lay and Norman Mariun, GIS-Based Optimal Site Selection for Installation of Large- Scale Smart Grid-Connected Photovoltaic (PV) Power Plants in Selangor, Malaysia, American Journal of Applied Sciences 2017, 14 (1), 174-183.

      [11] Angelamaria Massimo,,Marco Dell’Isola , Andrea Frattolillo and Giorgio Ficco, Development of a Geographical Information System (GIS) for the Integration of Solar Energy in the Energy Planning of a Wide Area,Sustainability 2014, 6, 5730- 5744.

      [12] Solargis. info/pvplanner; 2013. Available from http://www.solargis.info/pvplanner

      [13] http://solarelectricityhandbook.com/solar-angle-calculator.html

      [14] Marcel S, Tomáš C. SolarGIS: New web-based service offering solar radiation data and PV simulation tools for Europe, North Africa and Middle East. Eurosun; 2012.

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  • How to Cite

    Gowri Shankar Rao, R., K. Rayaguru, N., G.Renganathan, N., & Kumar Thakur, S. (2018). City - Scale Spatial Data Infrastructure for Solar Photovoltaic Energy Generation Assessment. International Journal of Engineering & Technology, 7(3.34), 4-7. https://doi.org/10.14419/ijet.v7i3.34.18705