Ali Mansourian
Professor
A Multi-Objective Optimization Approach for Solar Farm Site Selection: Case Study in Maputo, Mozambique
Author
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.
Department/s
- Dept of Physical Geography and Ecosystem Science
- Centre for Geographical Information Systems (GIS Centre)
- BECC: Biodiversity and Ecosystem services in a Changing Climate
Publishing year
2024-08
Language
English
Publication/Series
Sustainability
Volume
16
Issue
17
Document type
Journal article
Publisher
MDPI AG
Topic
- Earth and Related Environmental Sciences
Keywords
- Geospatial Artificial Intelligence (GeoAI)
- Multi-Objective Optimization (MOO)
- Solar Farm
- site selection
- NSGA-II optimization algorithm
Status
Published
ISBN/ISSN/Other
- ISSN: 2071-1050