Research Article Open Access

GIS-Based Optimal Site Selection for Installation of Large-Scale Smart Grid-Connected Photovoltaic (PV) Power Plants in Selangor, Malaysia

Sabo Mahmoud Lurwan1, Mohammed Oludare Idrees2, Goma Bedawi Ahmed2, Usman Salihu Lay2 and Norman Mariun1
  • 1 Centre for Advanced Power and Energy Research (CAPER), Faculty of Engineering, University Putra Malaysia, Malaysia
  • 2 Geospacial Information Science Research Centre (GISRC), University Putra Malaysia, Serdang, Malaysia

Abstract

This study presents a GIS-based model to identify optimal sites to install large-scale smart grid-connected Photovoltaic (PV) power plants. Input datasets include digital elevation model, road networks, grid lines and daily average solar radiation. Using multi-criteria decision-making approach, we set constraining conditions for slope, proximity to the road, proximity to grid lines, solar radiation and land use to optimize the process of selecting suitable sites. Also, we predicted energy generation potential, installation capacity and CO2 emission reduction potential. The result shows that 790.48 km2 (40%) of the study is optimal for large-scale PV installation. Furthermore, a total of 105276.88 GWh/yr annual electricity generation, 59.29 GW installation capacity and yearly CO2 emission reduction of 66324 (kt–CO2/yr) are estimated for Selangor. This study indicates that based on the 2030 national energy demand, about 38.4% of the annual energy demand could be met if 59.29 GW capacity is install in Selangor. Similarly, the study predicts 13.2% annual carbon emission reduction offset from the predicted 2020 CO2 emission.

American Journal of Applied Sciences
Volume 14 No. 1, 2017, 174-183

DOI: https://doi.org/10.3844/ajassp.2017.174.183

Submitted On: 10 October 2015 Published On: 30 January 2017

How to Cite: Lurwan, S. M., Idrees, M. O., Ahmed, G. B., Lay, U. S. & Mariun, N. (2017). 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, 14(1), 174-183. https://doi.org/10.3844/ajassp.2017.174.183

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Keywords

  • Geographic Information System (GIS)
  • Photovoltaic
  • Site Selection
  • Renewable Energy
  • CO2 Emission