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A considerable share of greenhouse gas (GHG) emissions is caused by the energy consumption for space heating and cooling in residential buildings. In Germany for instance about one third of the end energy consumption is accounted to space heating and cooling of buildings. Consequently, efforts to increase energy efficiency and substitute non-renewable energy with renewables are high. To explore the technical, economic and social effects of environmental mitigation strategies in order to increase energy efficiency in the building stock various models are used. Many of these models have to deal with the challenges of how to estimate energy demand levels. Derived from the recent development in this field researchers, planners and politicians are increasingly relying on energy models with integrated energy performance rating for environmental policy and strategy evaluation. However, energy assessments suffer from the common barriers of data access and data granularity. Therefore the approaches of energy building stock models comprise a mixture and variety of methods and have limits, which will be addressed in this contribution. The goal is to show how uncertainty is considered in existing models. This contribution provides general overview and key takeaways from the insight into different models and methodologies on the different levels of detail of building stock models.

From the Building Level Energy Performance Assessment to the National Level: How are Uncertainties Handled in Building Stock Models