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Site Suitability Analysis for Developing Wind Farms in Pakistan: a GIS-based Multi-criteria Modeling Approach.

Author(s)
Ali Jamshed Institute of Spatial and Regional Planning (IREUS), University of Stuttgart, Germany
AsadAli Saleem National Engineering Services Pakistan (NESPAK), Islamabad, Pakistan
Saleem Javed Master Program in Infrastructure Planning, University of Stuttgart, Germany
Maria Riffat Master Program in Infrastructure Planning, University of Stuttgart, Germany
Abstract
With a global scarcity of the fossil fuel resources and the eventual harm made to nature, a need for shifting to the renewable sources of energy has been given immense prominence. Developing countries, like Pakistan, have also been making a mark on this green evolution in their pursuit of enhancing the national grid capacity and reducing the energy deficit being faced by the country. Considering the case of Wind energy, research has shown a clear disparity in the amount of energy currently being tapped and the existing potential. Bearing in mind the substantial amount of resource investment needed to harness wind energy, meticulous planning becomes obligatory when choosing the potential site for a wind farm. Geographic Information Systems (GIS) have proven to be appropriate for this purpose. A multi-criteria approach modeled on the GIS software has been employed to establish the best-suited sites for wind energy development in Pakistan. Analysis indicated that the coastal areas of Sindh, northern parts of the country, the areas close to Bannu, Mardan, Sawabi, Islamabad and Mianwali as well as central-west of the country, including Sadiqabad in Punjab province and areas nearby Bolan Pass in Baluchistan were desirable for wind farm development. The GIS-based model can act as a guide for regional planners and policymakers in the energy sector for shaping future policies on wind energy and develop the optimum wind energy projects.
Publication Details
Page(s) 195-201
Published Journal: Science, Technology and Development, Volume: 37, Issue: 4, Year: 2018

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References
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