ISPRS-Annals ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences ISPRS-Annals ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci. 2194-9050 Copernicus Publications Göttingen, Germany 10.5194/isprsannals-II-4-W2-147-2015 SPATIOTEMPORAL MODELING FOR ASSESSING COMPLEMENTARITY OF RENEWABLE ENERGY SOURCES IN DISTRIBUTED ENERGY SYSTEMS Ramirez Camargo L. 1 2 Zink R. 1 Dorner W. 1 Applied Energy Research Group, Technologie Campus Freyung, Deggendorf Institute of Technology, Germany Institute of Spatial Planning and Rural Development, University of Natural Resources and life Sciences, Vienna, Austria 10 07 2015 II-4/W2 147 154 Copyright: © 2015 L. Ramirez Camargo et al. 2015 This work is licensed under the Creative Commons Attribution 3.0 Unported License. To view a copy of this licence, visit https://creativecommons.org/licenses/by/3.0/ This article is available from https://isprs-annals.copernicus.org/articles/II-4-W2/147/2015/isprs-annals-II-4-W2-147-2015.html The full text article is available as a PDF file from https://isprs-annals.copernicus.org/articles/II-4-W2/147/2015/isprs-annals-II-4-W2-147-2015.pdf

Spatial assessments of the potential of renewable energy sources (RES) have become a valuable information basis for policy and decision-making. These studies, however, do not explicitly consider the variability in time of RES such as solar energy or wind. Until now, the focus is usually given to economic profitability based on yearly balances, which do not allow a comprehensive examination of RES-technologies complementarity. Incrementing temporal resolution of energy output estimation will permit to plan the aggregation of a diverse pool of RES plants i.e., to conceive a system as a virtual power plant (VPP). This paper presents a spatiotemporal analysis methodology to estimate RES potential of municipalities. The methodology relies on a combination of open source geographic information systems (GIS) processing tools and the in-memory array processing environment of Python and NumPy. Beyond the typical identification of suitable locations to build power plants, it is possible to define which of them are the best for a balanced local energy supply. A case study of a municipality, using spatial data with one square meter resolution and one hour temporal resolution, shows strong complementarity of photovoltaic and wind power. Furthermore, it is shown that a detailed deployment strategy of potential suitable locations for RES, calculated with modest computational requirements, can support municipalities to develop VPPs and improve security of supply.