Regionalised heat demand and power-to-heat capacities in Germany – An open dataset for assessing renewable energy integration. (1st February 2020)

• Record Type: Journal Article
• Authors: Heitkoetter, Wilko; Medjroubi, Wided; Vogt, Thomas; Agert, Carsten
• Is Part Of: Applied energy. Volume 259(2020)
• Publication Date: 2020-02-01
• Subjects: Regionalised heat demand -- Power-to-heat capacities -- Open data -- Open source -- Census special evaluation -- Heating capacity classes; Power (Mechanics) -- Periodicals; Energy conservation -- Periodicals; Energy conversion -- Periodicals; 621.042
• DOI: 10.1016/j.apenergy.2019.114161
• Languages: English
• ISSNs: 0306-2619

Abstract

Graphical abstract: Highlights: Residential heat demand calculated for each administrative district in Germany. Determination of heat demand share covered by electric heating technologies. 729 building categories defined from a special evaluation of census data. Five classes of heating types and installed heating capacity considered. Resulting data and developed source code provided under open source licenses. Abstract: Higher shares of fluctuating generation from renewable energy sources in the power system lead to an increase in grid balancing demand. One approach for avoiding curtailment of renewable energies is to use excess electricity feed-in for heating applications. To assess in which regions power-to-heat technologies can contribute to renewable energy integration, detailed data on the spatial distribution of the heat demand are needed. We determine the overall heat load in the residential building sector and the share covered by electric heating technologies for each administrative district in Germany, with a temporal resolution of 15 min. Using a special evaluation of German census data, we defined 729 building categories and assigned individual heat demand values. Furthermore, heating types and different classes of installed heating capacity were defined. Our analysis showed that the share of small-scale single-storey heating and large-scale central heating is higher in cities, whereas there is more medium-scale central heating in rural areas. This results from the different shares of single and multi-family houses in the respective regions. To determine the electrically-covered heat demand, we took into account heat pumps and resistive heating technologies. All results, as well as the developed code, are published under open source licenses and can thus also be used by other researchers for the assessment of power-to-heat for renewable energy integration.