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Land Suitability Mapping for Large-scale Solar PV Farms in Tunisia Using GIS-Based MCDM Approach

EasyChair Preprint 9797

5 pagesDate: February 28, 2023

Abstract

Due to the complex nature of the data required to locate large-scale solar PV farms, this topic is of paramount importance. Hence, it is crucial to identify the ideal locations. For this reason, this paper's primary objective is to screen and evaluate the best candidate sites for hosting large-scale solar PV facilities throughout the whole of Tunisia. To this end, we conduct a land suitability analysis of the study region using GIS-based MCDM approach.

According to the outcomes, it was revealed that 1.11 percent of the land area, or 1571 km2, was comprised of the most viable options. Tataouine, Gabès, Gafsa, and Kassérine were also found to have the most promising locations for installing solar PV systems. Additionally, it was estimated that the solar power produced would be around 328 TWh per year.

Finally, the accepted model proved to be a powerful instrument for adjusting the chosen criteria to determine the best locations which may aid Tunisia in attaining its energy goals by 2030.Keywords—Solar energy, Multi-criteria Decision Making (MCDM), FAHP, Tunisia

Keyphrases: FAHP, Geographic Information System (GIS), Multi-Criteria Decision Making (MCDM), Tunisia, solar energy

BibTeX entry
BibTeX does not have the right entry for preprints. This is a hack for producing the correct reference:
@booklet{EasyChair:9797,
  author    = {Sassi Rekik and Souheil El Alimi},
  title     = {Land Suitability Mapping for Large-scale Solar PV Farms in Tunisia Using GIS-Based MCDM Approach},
  howpublished = {EasyChair Preprint 9797},
  year      = {EasyChair, 2023}}
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