Regionalised heat demand and power-to-heat capacities in Germany -- An open data set for assessing renewable energy integration

TL;DR

This paper provides a detailed, open dataset on regional heat demand and power-to-heat capacities in Germany, enabling better assessment of renewable energy integration through spatially-resolved analysis of heating needs.

Contribution

It introduces a novel, detailed dataset and methodology for assessing regional heat demand and power-to-heat potential across Germany using census data and open source tools.

Findings

Higher small-scale heating in cities, larger-scale in rural areas

Electric heating share varies by region and building type

Open dataset supports renewable energy integration analysis

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 minutes. 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.