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Petter Pilesjö

Prefekt

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A Multi-Objective Optimization Approach for Solar Farm Site Selection: Case Study in Maputo, Mozambique

Författare

  • Tome Eduardo Sicuaio
  • Pengxiang Zhao
  • Petter Pilesjö
  • Andrey Shindyapin
  • Ali Mansourian

Summary, in English

Solar energy is an important source of clean energy to combat climate change issues that motivate the establishment of solar farms. Establishing solar farms has been considered a proper alternative for energy production in countries like Mozambique, which need reliable and clean sources of energy for sustainable development. However, selecting proper sites for creating solar farms is a function of various economic, environmental, and technical criteria, which are usually conflicting with each other. This makes solar farm site selection a complex spatial problem that requires adapting proper techniques to solve it. In this study, we proposed a multi-objective optimization (MOO) approach for site selection of solar farms in Mozambique, by optimizing six objective functions using an improved NSGA-II (Non-dominated Sorting Genetic Algorithm II) algorithm. The MOO model is demonstrated by implementing a case study in KaMavota district, Maputo city, Mozambique. The improved NSGA-II algorithm displays a better performance in comparison to standard NSGA-II. The study also demonstrated how decision-makers can select optimum solutions, based on their preferences, despite trade-offs existing between all objective functions, which support the decision-making.

Avdelning/ar

  • Institutionen för naturgeografi och ekosystemvetenskap
  • Centrum för geografiska informationssystem (GIS-centrum)
  • BECC: Biodiversity and Ecosystem services in a Changing Climate
  • MECW: The Middle East in the Contemporary World
  • LU profilområde: Naturbaserade framtidslösningar

Publiceringsår

2024-08

Språk

Engelska

Publikation/Tidskrift/Serie

Sustainability

Volym

16

Avvikelse

17

Dokumenttyp

Artikel i tidskrift

Förlag

MDPI AG

Ämne

  • Earth and Related Environmental Sciences

Nyckelord

  • Geospatial Artificial Intelligence (GeoAI)
  • Multi-Objective Optimization (MOO)
  • Solar Farm
  • site selection
  • NSGA-II optimization algorithm

Aktiv

Published

ISBN/ISSN/Övrigt

  • ISSN: 2071-1050