A model-based assessment of climate and energy targets for the German residential heat system

The residential building sector has an important role to play in the energy transition due to a high share of final energy consumed and a considerable amount of CO2 emitted. Ambitious targets in Germany relate amongst other things to a primary energy reduction of 80% and an increased usage of renewable energy sources in heat supply to 60% in 2050. Existing research in this area both lacks detail in modelling decentralised heat supply in residential buildings and fails to adequately quantitatively analyse this target achievement for Germany. In order to overcome these limitations, a novel model-based approach is presented in which the developed TIMES-HEAT-POWER optimisation model is coupled with a decentralised energy system optimisation model to determine optimal and realistic technology configurations, and a building stock simulation model to adequately and consistently project the evolution of the building stock in Germany. This novel configuration of models is then used to investigate the evolution of the electricity system and the residential heat system in Germany in the context of key energy political targets up to 2050. The national goals related to primary energy reduction and the share of renewable energy sources in final energy demand in the residential heat sector are missed in the Reference Scenario. On the other hand, target achievement requires deep insulation measures and a supply-side technology shift away from gas and oil boilers towards heat pumps and solar thermal. The scenario analysis reveals a significant sensitivity of the deployment of micro-Combined heat and power technologies (mu CHP) and heat pumps to, amongst other things, the evolution of fuel prices, renewable electricity technologies, heat and electricity demand as well as technological progress. Further model extension can be identified inter alia in broadening the system boundaries to integrate further sectors (tertiary, industrial) or incorporating different user categories and decision rationales. (C) 2016 Elsevier Ltd. All rights reserved.