Simstock: a free and open-source tool for urban-scale building energy modelling

08 December, 2023

Reading time: 4 minutes

Researchers at University College London have released SimStock, a freely available and open-source tool for urban-scale building energy modelling. It is available both as a Python library and a QGIS plugin.

SimStock is a modelling platform which automatically generates dynamic building energy simulation models ready to be executed by EnergyPlus, an open-source whole-building energy modelling (BEM) engine.

The generated models can be simulated locally or with high performance computing, making use of all available computing power by running simulations in parallel. Simulation outputs are collected and post-processed automatically which prepares them for various analysis to be applied, such as sensitivity analysis, regressions, uncertainty quantification etc.

SimStock allows the automatic creation of dynamic thermal simulation models of all buildings within an area of analysis; allowing a wide range of scenario analyses to be performed. These include:

  • Analysis of the efficacy of various retrofit measures applied to the building stock, such as improved insulation, replacing an artificial lighting with more efficient LED lighting, glazing replacement, improved heating, ventilating and air-conditioning systems’ control strategies.
  • Testing the potential for integration of renewable technologies in the building stock. Roof area availability for installation of Photovoltaic (PV) systems and/or solar-thermal systems and the performance of these systems can be evaluated at both the stock level and individual building level. Similarly, the potential for integration of ground source heat pumps can be assessed.
  • Investigating the feasibility of integration of thermal and/or electrical storage systems for the purpose of demand-side management in various-sized areas.
  • Assessing daylight availability and a quality of daylight by taking into account the surrounding context.
  • Estimating the overheating risk of the stock as a whole, a stock segment (e.g. schools) or individual buildings under both current climate conditions and predictions of future climate conditions.
  • Mapping buildings, mainly in dense urban areas, which are under the risk of decreased Indoor Air Quality (IAQ) due to various reasons such as reduced natural ventilation due to Urban Heat Island (UHI) effect, increased particulate pollution either due to poor ventilation or external air pollution and/or exposure to nitrogen oxides (NOx) from traffic due to closeness to the major roads.

Download SimStock

SimStock is available both as a Python library and a QGIS plugin.

SimStock publications:

Research which has made use of SimStock:

Banner photo credit: Jon Tyson on Unsplash