Assessment of rooftop photovoltaic potentials at the urban level using publicly available geodata and image recognition techniques

Abstract

The local generation of renewable electricity through roof-mounted photovoltaic (PV) systems on buildings in urban areas provides huge potentials for the mitigation of greenhouse gas emissions. This contribution presents a new method to provide local decision makers with tools to assess the remaining PV potential within their respective communities. It allows highly detailed analyses without having to rely on 3D city models, which are often not available. This is achieved by a combination of publicly available geographical building data and aerial images that are analyzed using image recognition and machine learning approaches. The method also employs sophisticated algorithms for irradiance simulation and power generation that exhibit a higher accuracy than most existing PV potential studies. The method is demonstrated with an application to the city of Freiburg, for which a technical PV electricity generation potential of about 524 GWh/a is identified. A validation with a 3D city model shows that the correct roof azimuth can be determined with an accuracy of about 70% and existing solar installations can be detected with an accuracy of about 90%. This demonstrates that the method can be employed for spatially and temporally detailed PV potential assessments in arbitrary urban areas when only public geographical building data is available instead of exact 3D city model data. Future work will focus on methodological improvements as well as on the integration of the method within an urban energy system modeling framework

Exploring Data Model Relations in OpenStreetMap

“…Schultz et al [45] conclude that the composition of relations, the spatial relations they represent and the tags associated with the relations could provide opportunities for applications such as the derivation of Land Cover classes from Land User map data. Mainzer et al [46] present a new method to provide local decision makers with tools to assess the remaining (roof-mounted photovoltaic) PV potential within their respective communities. It allows highly detailed analyses without having to rely on 3D city models.…”

Renewable Energy Generation Scenarios Using 3D Urban Modeling Tools—Methodology for Heat Pump and Co-Generation Systems with Case Study Application †

“…Another important step for reducing emissions is to use the solar irradiance to produce electricity with photovoltaic (PV) systems. There are several studies that show methods on how to analyze the PV potential in urban areas [21,22]. Most of the studies investigating the PV potential are based on the 3D geometry of the buildings and their roofs [23][24][25][26] since knowing the exact roof shape and orientation helps to calculate more accurate values for the PV potential energy yield.…”

Optimization of Solar Panel Orientation Considering Temporal Volatility and Scenario-Based Photovoltaic Potential: A Case Study in Seoul National University

“…There is considerable previous literature regarding estimating solar potential in urban areas such as a university. Some studies have focused on building roofs [12][13][14][15][16][17][18][19]. These mainly studied the extraction of high potential roofs of buildings considering roof orientation and shadowing.…”

“…These mainly studied the extraction of high potential roofs of buildings considering roof orientation and shadowing. Some have focused on the detection of building roofs [12][13][14][15] and various scales of this method were applied from specific detailed building roofs [12,16] to the national scale [17]. This method is appropriate for urban areas with low buildings.…”