Due to the complexity and importance of energy-political decisions, optimization models, which are able to capture the many interactions between different energy carriers and technologies, have become common tools for decision support.
Especially for regional energy systems, i.e. for the scope of single municipalities, demand side residential efficiency measures, like domestic retrofitting or the installation of efficient lighting and white goods, are vital tools for reducing and shaping the future energy demand.
These measures, however, are commonly not integrated well in optimization models – or not at all. This paper proposes a new method for the integration of residential efficiency measures in optimizing urban energy system models, which seeks to remedy with these issues. Efficiency measures are modelled as technologies which are able to convert energy between carriers with given conversion rates, e.g. in the case of LEDs from electricity to luminous energy and heat. In order to achieve this, demand is fed into the model as an energy services demand. This allows the model to choose from a range of available technologies which are able to satisfy this demand.
The model results for a German municipality show that the techno-economic incentives for investing in more efficient demand- and supply-side technologies are not sufficient: while a slow shift to more efficient building insulations and appliances can be observed, it is not enough in order to reach the German government’s greenhouse gas reduction plans. If these plans are enforced in the model, however, more efficient technologies are employed on the supply side as well as on the demand side. These findings can be used by policymakers in the form of local energy efficiency roadmaps, which are tailored to the specific setting of municipalities.