AIRBORNE AND OPENGEO DATA FOR ENERGY SYSTEM MODEL APPLICATIONS

Abstract

In order to achieve significant reduction of CO2 emissions to 80% compared to 1990 by 2050, government agencies and power grid operators support the construction of solar power plants. Therefore, public authorities and electricity grid operators are interested in change detection methods to observe the buildup of renewable energy sources, like private solar module systems or to forecast the electric grid demand and production. To support energy system analyzing applications we extent and/or replace the current used free OpenStreetMap (OSM) data to Earth Observation (EO) detected energy infrastructure sources. First results show an impact of modelling results depending on the level of detail information between free available OSM and EO data. Building information are generated from 3K data by GIS standard tools and developed extraction algorithm show a limitation to polycrystalline Photovoltaic module detection. Shadowing effects of PV modules as well as classification of photovoltaic and solar thermal modules from optical airborne data play an important role.