PV4EAG - Analysis of area and energy potential using AI for alternative PV systems as a contribution to the EAG

Project: Research project

Project Details

Description

With the Renewable Expansion Act (EAG), the goal set by the federal government to cover 100% of total electricity consumption from 2030 on a national balance sheet from renewable energy sources is to be implemented. For this purpose, the annual electricity generation from renewable sources is to be increased by 27 TWh by 2030 through new construction, expansion and revitalization, with 11 TWh being realized by means of photovoltaic systems (PV). In 2019, the installed PV capacity in Austria was 1.7 GWp (1.7 TWh of generated energy). The annual growth rates in the years 2014-2018 were 150-180 MWp / a. Only in 2019 was it possible to achieve a higher value of 250 MWp / a. To achieve the target of 11 TWh by 2030, an annual expansion rate of 1,000 MWp / a would have to be achieved. Current studies show that the available roof areas with an expansion potential of 3.5 TWh are not sufficient and therefore alternative PV systems are required. For the reasons mentioned above, in addition to the planned roof systems, innovative alternative area potentials for PV systems must be tapped. The reports from other projects show the available space and energy potential, but these were determined using statistical methods, so that no statement is made regarding the actual suitability. Alternative PV areas / yields in a city were specified, but no methodically systematic localization of these places was carried out. The motivation of PV4EAG is to close this gap and to develop a process for the automated discovery of alternative PV areas. This addresses the sub-topic "Creation of a freely accessible data platform with energy-relevant forecasts" In the PV4EAG project, alternative PV areas are to be analyzed using methods from the field of Geographic Information Science & Technology and artificial intelligence for their suitability in terms of shading, yield potential, construction costs, and grid connection options. The starting point is the existing GIS data (digital building heights, vegetation models, terrain models from airborne laser scanning data, cadastral data), in combination with other publicly available data (Open Governmental Data) and other open data sources (OpenStreetMap, Corine Landcover, etc.), as well as remote sensing data and products (ie orthophotos and satellite image data) are used. By using smart data fusion, semantic annotation of the data (for semantic data integration), and spatial analysis techniques paired with artificial intelligence (GeoAI in the broadest sense), the data should be suitable for large-scale facade-integrated systems on high-rise buildings, sealed parking spaces in shopping centers and residential areas , Traffic areas and rail systems as well as floating PV are analyzed. For the development and testing of the analysis method, the project is limited to selected locations in Styria, with the aim of scaling it up. For these locations, a plausibility check is carried out using the existing VR installation in the EAS lab using a virtual 3D process, and detailed project planning is used to specify the realistic PV yield to be expected.
StatusActive
Effective start/end date1/01/2231/12/23

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