Assessment of rooftop photovoltaic potentials at the urban level using publicly available geodata and image recognition techniques
Introduction
There is a worldwide consensus that greenhouse gas emissions should be substantially reduced over the next few decades in order to mitigate climate change (IPCC, 2015). This can only be accomplished through a massive decarbonization of the energy system. One of the most important levers in this endeavor are combinations of energy efficiency measures and renewable energy resources in cities, which will have to play a crucial role in the energy transition (IEA, 2016).
In order to develop local schemes and make informed decisions for the transition to renewable energies, policy makers need to be provided with accurate information on the potential contribution from each of these measures on global as well as on regional and local levels.
The local generation of clean power through PV systems on building roofs, in particular, provides huge potentials that are usually economically viable. Compared to other available options, PV has higher public acceptance, partly because there is less competition for land or other resources.
The assessment of the (remaining) potential for power generation from PV is an important field of study. Methods and tools that enable local decision makers to assess PV potentials in their respective communities are of vital importance for the energy transition. The literature review in Section 2 shows, however, that currently there are no tools available that allow local decision makers to assess these potentials in high detail and accuracy without first having to acquire large amounts of data. With this contribution, the authors intend to address this issue.
Since the requirements for detailed PV potential analyses usually include data that is not publicly available and, especially in smaller municipalities, can not be easily obtained, the objective of this contribution is to present a method for detailed urban PV potential assessment that relies solely on publicly available data and can be applied universally. The authors improve upon existing work as well as their previous publications (e.g. Mainzer et al., 2016) in a number of points:
- 1.
high-detailed, bottom-up PV potential analysis in the absence of 3D model data,
- 2.
discrete number of actually installable modules instead of just the area,
- 3.
consideration of roof objects, e.g. chimneys and windows,
- 4.
exact irradiance simulation with high temporal resolution (1/4 hourly),
- 5.
detailed, non-linear power generation model with consideration of temperature, module and inverter characteristics,
- 6.
consideration of already installed PV modules.
The present literature on the subject is analyzed in Section 2. In Section 3, all steps of the method that was developed are described in detail. Section 4 presents results from an example application of the method to the city of Freiburg, Germany. These results are further analyzed, validated and discussed. In Section 5, the findings are concluded.
Section snippets
Literature review
Several publications have already addressed the problem of identifying PV potentials. The main steps in PV potential estimation methods include the assessment of the available area for PV modules, the simulation of solar irradiance on the tilted module surfaces and the calculation of produced electrical power from the irradiance on these modules. Martín-Chivelet (2016) provides an overview of different methodologies that are employed for each of these steps. As discussed in the following
Methodology
The approach that is used to assess the remaining economic potential in a given region is conducted within nine distinct steps, as shown in Fig. 1.
While some of these steps rely on well-known methods and algorithms, some novel approaches are also presented in this work. These approaches, which are described in steps 2, 4 and 9, are based on the assumption that humans can usually tell the shape, size and suitability of a roof for PV based on its aerial image. Using image recognition techniques,
Results and discussion
The previous section has demonstrated how the method assesses the potential for PV installations in any region by analyzing the roof areas of all buildings and calculating the electricity that could be produced as well as the associated costs.
In this section, the example application of this method to the city of Freiburg, Germany is demonstrated. After showing the aggregated results as well as more detailed results for individual districts (subsection 4.1), the findings are validated by
Conclusion
In this contribution, a new method for the assessment of rooftop PV potentials at the urban level has been presented. This method can be used to conduct PV potential analyses in high detail and in many regions of the world. It uses publicly available geographical building data and aerial images in combination with image recognition techniques to derive the size and orientation of partial roof areas without having to rely on 3D model data.
Compared to existing methods for PV potential assessment,
Acknowledgments
The authors gratefully acknowledge the financial support of the Federal Ministry of Education and Research (BMBF – Germany) for the project Wettbewerb Energieeffiziente Stadt (03SF0415B) and the Nagelschneider Foundation. The authors would also like to thank David Schlund for his contributions to earlier versions of this method.
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