optimal site selection of solar power plant stations using gis-anp and genetic optimization algorithm in markazi province, iran

The demand for non-renewable energy sources in power generation is crucial for residential and commercial uses, significantly impacting national development. however, with the depletion of fossil fuels, there is a shift towards renewable energy sources such as solar, water, and wind, which have seen a surge in use over recent decades. in iran, despite abundant fossil fuel resources, solar energy is vital due to the country's favorable geographic conditions for solar exploitation. this study applies the analytic network process (anp) and genetic algorithm (ga) to identify optimal locations for solar power plant stations in markazi province, iran. key morphological factors considered include slope, elevation, and solar radiation. the research identified the northwest and northern parts of markazi province as the most suitable for solar photovoltaic systems, primarily due to their simpler topography. using a genetic algorithm, which outperformed the anp, it was found that about 24,000 km² in these areas are apt for solar power facilities, categorized into highly suitable (2,429.312 km²), moderately suitable (16,818.49 km²), and suitable (5,029.007 km²). saveh showed the highest potential, while ashtian, khondab, and shazand had the least. these findings provide crucial insights for stakeholders looking to develop solar energy projects in markazi province.