An interactive GIS-based method to determine feasible roof areas for photovoltaic panels

Abstract

Multiple platforms, software, and tools exist to support homeowners assess the feasibility to install photovoltaic (PV) panels on their homes. However, the current platforms are not very user-friendly and often neglect the shading effect of nearby trees or other obstacles on the efficiency of the PV panels. This study presents a GIS-based method for considering the shading effect to identify suitable roof areas for hosting PV panels. Furthermore, this study estimates potential electricity output for three representative dates based on the suitable rooftop area. Although currently available tools can calculate the shading, these tools require excessive training and knowledge to understand and use. This might deter homeowners from installing rooftop PV systems. The approach in the presented study is user-friendly and interactive. The users can enter their home address on the map and graphically view the best location of PV panels on their roofs. Also, they can easily see whether their rooftop has enough potential to meet their daily electricity need for three representative dates. The case study location is the Capitol East neighborhood in Des Moines, IA. But as the map developed in this project is based on a Python-based model; the strategy can also be transferred to other neighborhoods and other dates. The presented results for this neighborhood showed on June 20th 93.7% of buildings could meet their daily electricity demand. On September 20th, 91% of buildings in the study area have enough potential to produce the daily electricity demand of a residential building. In winter, most buildings will have to rely on electricity from the grid.