Swedish scientists developed a three-step method that integrates techniques used for the automatic extraction of buildings along with their underlying roof faces, as well as the identification of utilizable rooftop areas for solar arrays. The novel methodology is claimed to avoid overestimating actual potential of buildings for PV deployment.
Scientists in Sweden have created a spatially detailed methodology for identifying utilizable rooftop areas for deploying PV systems.
The method integrates techniques used for the automatic extraction of buildings along with their underlying roof faces, as well as the identification of utilizable rooftop areas for solar arrays. It is described as a three-step approach including automatic extraction of buildings footprint, automatic segmentation of roof faces, and automatic identification of utilizable areas.
“Specifically, the innovations of this work are a new method for roof face segmentation and a new method for the identification of utilizable rooftop areas,” the scientists stated, noting that the correctness and completeness for the first operation were found to be 95% and 85%, respectively. “The proposed methodology only requires digital surface models (DSMs) as input, and it is independent of other auxiliary spatial data to become more functional.”
The suitability of a roof for PV deployment is also evaluated by considering the area’s solar radiation, with the modeling taking into account atmospheric effects, site elevation and orientation, daily and seasonal changes of the sun position, and the shadow effect of surrounding objects.
The roof faces suitable for PV installations are then captured by partitioning rooftops into planar segments. In this phase, the system utilizes geometric features including the height and greatest width of an above-ground object, and regional features, including the area of an object and the area of its constituent planar segments.
When these operations are carried out, the system is able to automatically identify the solar-suitable surfaces. “Having the spatial distribution of solar irradiation along with planar segments of roofs, utilizable rooftop areas can be automatically identified,” the academics explained. “Technical, geometric, and solar limitations are considered to accomplish this task.”
The methodology was tested in part of the Swedish city of Gothenburg, which the scientists describe as a city with buildings with complex roof forms. They found that around 27% of its roofs are suitable for PV installations. “The results also indicated that the proposed roof face segmentation method outperforms region growing, a widely used plane segmentation method,” they added.
The novel approach is proposed in the paper “Automatic identification of utilizable rooftop areas in digital surface models for photovoltaics potential assessment,” published in Applied Energy. The research group includes scientists from Sweden’s University of Gävle and Uppsala University.