Note: This is an automated translation (using DeepL) of the original German article.

Kleine Zeitung reports: AI is used to search for and analyze new sites for power generation

The Renewable Energy Expansion Act (EAG) is intended to implement the federal government’s set target of covering 100% of total electricity consumption nationally from renewable energy sources on balance from 2030. To this end, annual electricity generation from renewable sources is to be increased by 27 TWh by 2030 through new construction, expansion and revitalization, with 11 TWh to be realized by means of photovoltaic (PV) plants (Austrian National Council: Government Bill on the Renewable Expansion Act Package, 2021).

To answer the question of where? and how?, the research project PV4EAG, by an interdisciplinary consortium of FH Joanneum Graz, FH Campus 02, TU Graz, the Energieagentur Steiermark and dwh GmbH, was started. Since there are already appropriate tools for the use of roofs as PV sites, the goal of this innovative project is to identify suitable areas for PV, which have not been considered so far or only rarely.

The dwh GmbH contributes to the project, among other things, machine learning expertise, with which aerial & satellite images are automatically searched for suitable areas for the installation of photovoltaic systems. These are then combined with further data and information (e.g. grid connections for feed-in). The goal is to feed this database into the geographic information system (GIS) of the province of Styria at the end of the project in order to serve as a basis for decision-making for politicians and other stakeholders.

We are very pleased that in the current discussion on the energy crisis, this project was taken up by the Kleine Zeitung (16.08.2022, print) and made known to a broad public (see cover photo).