Presentation at the 11th International Energy Conference IEWT 2019 in Vienna
The electrification of heating applications represents one significant component in the decarbonisation of private households . The spatial distribution of diverse kinds of energy carriers used for heating applications within a country (heating structure) is usually not homogeneous. Population density and climatic conditions are influencing factors determining the type of energy carrier and the used heating system in a region. Hence, the selective substitution of fossil-fired heating systems by electrically fired ones induces spatially varying changes in the electrical load. Accordingly, the key motivation for this paper is to develop a methodology to generate spatially differentiated electrical load profiles by using heating structures.
A top-down approach is used to model space heating and hot water load profiles in the spatial resolution of NUTS‑3‑regions. The study focuses on the German energy system. Hence, in the context of the European electricity market coupling the 14 current and future electrical neighbouring countries of Germany and Austria as well as Austria itself are of major interest.
For these 15 countries, national energy balances are modified to generate application balances in which the yearly final energy consumption is determined. The part of final energy needed for space heating and hot water split up into energy carriers is allocated to the NUTS‑3‑regions by using the distribution of heating systems. Variations in climatic conditions are taken into account by degree day numbers at NUTS‑3‑level. The spatial distribution of heating systems by energy carriers is provided by the national offices for statistics. If the data quality is lower, regional final energy consumption by energy carrier is used. Thereby additional applications (lighting, cooking, …) have to be subtracted from the data to derive the heating structure for space heating and hot water. However, these methods cannot be applied to all countries due to variations in data availability and quality, making individual methods necessary. The annual final energy consumption for space heating and hot water of each NUTS‑3‑region is converted into daily resolved data using the degree day numbers, whereby no seasonal effect is assumed for hot water consumption. Using temperature-dependent standard gas load profiles the daily quantities of space heating and hot water demand are transformed into hourly load profiles. Finally it is shown how a change in energy carrier towards electricity based energy carrier impacts peak load and load distribution on NUTS-3-level for a chosen scenario.
Methodology and results summarized in this paper were compiled within the project eXtremOS, which is supported by the Federal Ministry for Economic Affairs and Energy of Germany (funding id: 03ET4062).