Optimizing urban solar photovoltaic potential: A large group spatial decision-making approach for Tehran

Abstract

Solar energy is a prominent renewable resource that can substitute fossil fuels. Identifying suitable locations for urban photovoltaic systems (UPVS) is a crucial step towards utilizing renewable energy sources. This study employs a large group spatial decision-making support system based on geographic information systems (GIS-LGDM) to create a map highlighting high-potential areas for UPVS in Tehran, Iran. The analysis considers ten effective criteria: photovoltaic power output (PVOUT), sky view factor (SVF), building density, building height, population density, aerosol optical depth (AOD), and distance from infrastructure and facilities (parks, roads, commercial, industrial, and service centers, and airports). The LGDM method determines the necessary weights and addresses uncertainties among the criteria. The final potential map was generated using the weighted linear combination (WLC) method to identify the most suitable locations for UPVS installation. Additionally, the one-at-a-time (OAT) method assessed the sensitivity of the results to criteria weights. Results revealed that PVOUT and population density are the most influential criteria in the UPVS potential assessment for Tehran. According to the GIS-LGDM analysis, 37 % and 10 % of the areas have very high and high potential for UPVS installation, respectively. Sensitivity analysis also showed that changes in the AOD and building density criteria weights have the minimal and maximal effects on the area of high-potential locations, respectively. The findings of this study are applicable to various managerial and planning functions related to solar energy development in urban environments, aiming to promote the rapid adoption of renewable energy.