SPAN: An open-source plugin for photovoltaic potential estimation of individual roof segments using point cloud data

Abstract

Decentralized solar PhotoVoltaic (PV) is one of the most promising energy sources for cities and individuals pursuing energy self-sufficiency. Especially, the already available rooftop surfaces are a major contributor to push for rooftop mounted PV systems. However, accurate PV potential estimation of individual buildings is still a challenging task since many parameters must be considered such as meteorological factors, panel technology, geographical location, available roof surface area, surface azimuth and tilt angle. In this study, we created an efficient approach that can be used for roof surface's PV potential estimation based on point cloud data and capable of processing various scales from single building to city scale. In the proposed approach, each roof surface's features were utilized for PV potential estimation by employing the PVGIS database. PV potential estimation was carried out on daily, monthly, and annual periods to provide a better estimation. Also, we developed a flexible and easy to use open-source plugin based on the QGIS software for rooftop mounted PV potential estimation capable of estimating every roof surface's PV potential. The method was tested on 80 buildings selected from ROOFN3D dataset. The proposed approach achieved an overall accuracy of 84% and an F1 score of 0.92.