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Identification of optimal wind, solar and hybrid wind-solar farming sites using fuzzy logic modelling

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  • Dhunny, A.Z.
  • Doorga, J.R.S.
  • Allam, Z.
  • Lollchund, M.R.
  • Boojhawon, R.

Abstract

In this paper, an analytical framework is developed using fuzzy logic to evaluate optimal sites for wind, solar and hybrid wind-solar farms; using criterial components for energy optimization through climatological, topographic and human factors. The model is applied through a case study to the island of Mauritius which bears a highly complex topography. Through this computation, fuzzy constraints including wind and solar power, site elevation, settlement areas, and proximity to grid lines are all fitted to different fuzzy membership sets and the individual satisfaction degrees of each were calculated and aggregated into overall satisfaction degrees. Decision maps of highly suitable regions for hybrid wind-solar farming were then highlighted revealing two potential sites on the island for hybrid wind-solar farming; revealing a total generation potential of energy per year of 161.58 GWh at Le Morne and 281.28 GWh at La Laura-Malenga. The findings of this study aim to guide energy and urban planners to better identify optimum sites for wind, solar and hybrid wind-solar farm construction whilst making optimal use of land resources to achieve both sustainable dimensions and energy economic resilience.

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  • Dhunny, A.Z. & Doorga, J.R.S. & Allam, Z. & Lollchund, M.R. & Boojhawon, R., 2019. "Identification of optimal wind, solar and hybrid wind-solar farming sites using fuzzy logic modelling," Energy, Elsevier, vol. 188(C).
  • Handle: RePEc:eee:energy:v:188:y:2019:i:c:s0360544219317517
    DOI: 10.1016/j.energy.2019.116056
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