• Class: Building stock model
  • Analytical approach: Bottom-up
  • Purpose:
  • Methodology: Building stock simulation
  • Deterministic
  • Regions: Cities and districts
  • Sectors: Electricity, heat, cooling, domestic hot water
  • Demand sectors: Residential, commercial
  • Generation technologies: Boilers and heating
  • Energy carriers: Electricity, heat
  • Time horizon: One year
  • Time resolution: Hourly

Combined Energy Simulation and Retrofitting-[CESAR]-Tool

CESAR is composed of two sub-models: a Demand Model (DM) and a Retrofitting Model (RM). The DM is tasked with identifying the current energy demand of buildings in districts. Once current energy demands are calculated by the DM, the RM further offers the possibility to apply a set of energy transformation scenarios, based on the Swiss Energy Strategy 2050, to generate future demand and emission projections of districts including key economic indicators.

Generic model structure

Model inputs

  • 2.5D building data
  • TMY weather files (Meteonorm)
  • Gebäude und Wohnungsstatistik (GWS) data
  • Gebäude- und Wohnungsregister (GWR) data

Model outputs

  • Energy demand profiles (hourly, building-scale) per retrofit scenario
  • Primary energy and greenhouse gas emissions per retrofit scenario
  • Investment costs per retrofit scenario
  • Payback time per retrofit scenario


  • Danhong Wang, Jonas Landolt, Georgios Mavromatidis, Kristina Orehounig, Jan Carmeliet. (2018). CESAR: A bottom-up building stock modelling tool for Switzerland to address sustainable energy transformation strategies. Energy and Buildings, 169, 9-26.
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