Coupling of multi-zone dynamic energy simulations with life cycle assessment for residential building renovation

In the EU, buildings account for 40% of energy consumption and 36% of greenhouse gas emissions from energy. Therefore, the building sector plays a crucial role in achieving the 2050 climate goals. Existing buildings need to prepare for low-temperature readiness and move away from fossil fuels. However, it is not enough to focus solely on reducing energy use during the operational phase of buildings. As buildings are constructed to be more energy-efficient, the embodied carbon increases. It’s important to address this impact as well to develop carbon efficient renovation strategies.

In life cycle assessment (LCA) the energy use is most often calculated by a simplified, steady-state approach, which does not take into account real user behaviour and climate change. Consequently, the results are not always realistic.

Limited research has been done on the implementation of dynamic simulations in LCA calculations. E.g., previous research by Ramon et al. studies the effect of multi-zone dynamic simulations in office buildings, taking into account climate change and a dynamic electricity mix.

This research investigates how this method can be used for residential buildings. In addition, the occupant profiles have been refined, by implementing multiple statistically representative occupancy profiles using the EROB model (event-based residential occupant behaviour).

A multi-zone dynamic simulation model of an archetype dwelling is set up in Dymola. Multiple variations of renovation scenarios with low-temperature heating are simulated to come to a distribution of the potential energy use over the life cycle of the building. Further, the calculation of the total environmental impact per simulated case is automated.

The results are analysed to see which adjustments have the largest impact on the results and cannot be neglected. The results are also compared to the output of the Belgian LCA calculation tool Totem, to see if the results differ a lot from this more simplified approach. It is expected to find a large difference in the results, since Totem doesn’t use dynamic simulations and does not take climate change and a dynamic electricity mix into account.