Aarhus Universitets segl


The reason why we live in buildings is to have a healthy, productive and comfortable (indoor) environment for long-term stays. It is important that we achieve this with a sustainable use of natural resources.

The Indoor Climate and Energy research group focus on the development of sustainable methods and technologies to achieve sustainable, healthy, comfortable, and productive indoor environments. We have four focus areas:


The research group makes investigations that quantifies how indoor climate affects human comfort and productivity. Here are some examples.

  • Increased classroom ventilation rate can improve the performance of schoolwork by children 11% [1].
  • How thermal conditions in bedrooms may affect sleep [2]
  • Large-scale subjective assessment of comfort in real homes and offices may alter our models used in design [3,4].
  • Virtual reality in climate chamber experiments helps us understand the holistic nature of indoor environment.


It is important to be aware of the how potential design decisions may affect the indoor environment and use of natural resources. For this purpose, we make use of legacy simulation tools but also develop new software. Here are some examples:

  • iDbuild is a combined daylight and thermal simulation tool for climate-based daylight and energy performance simulation [5].
  • ICEbear is like iDbuild but has extended and updated features and works in SketchUp, Rhino, and Revit.


The future energy source is primarily solar and wind energy which vary with weather conditions. Future building energy management must accommodate this. Here are some examples:

  • We can make use of model predictive control of building heating systems to save money and CO<font size="2">2</font> [6]
  • Smart control of domestic hot water production [7]
  • Increasing the value of energy renovations using model predictive control [8]
  • Predict the effect of energy renovations on urban scale [9]


The research group research in resource-efficiency in buildings. Here are some examples:

  • Absolute environmental performance of buildings [10]
  • Diffuse ceiling ventilation [11]
  • Detecting room occupancy [12]
  • Embodied energy in windows [13]

[1] Petersen S., Jensen K.L., Pedersen A.L.S., Rasmussen H.S. The effect of increased classroom ventilation rate indicated by reduced CO2-concentration on the performance of schoolwork by children. Indoor Air 26 (2016) 366–379

[2] Strøm-Tejsen P., Mathiasen S., Bach M. and Petersen S. The effects of increased bedroom air temperature on sleep and next-day mental performance. The 14th international Conference on Indoor Air Quality and Climate. Ghent, Belgium. 2016
[3] Petersen S., Clausen A.H. and Knudsen L.D.S. Investigating the Ability of Prevailing Thermal Comfort Models to Predict Thermal Comfort in Homes. 12th REHVA World Conference CLIMA. Aalborg, Denmark. 2016

[4] Petersen S. and Pedersen S.M.L. Desktop polling station for real-time building occupant feedback. 12th REHVA World Conference CLIMA. Aalborg, Denmark. 2016

[5] www.idbuild.dk

[6] Knudsen M.D. and Petersen S. Demand Response Potential of Model Predictive Control of Space Heating based on Price and Carbon Dioxide Intensity Signals. Energy and Buildings 145 (2016) 196–204

[7] Knudsen M.D. and Petersen S. Model Predictive Control of Domestic Hot Water Preparation in Ultra-Low Temperature District Heating Systems. Energy and Buildings 141 (2017) 158–166

[8] Pedersen T.H., Hedegaard R.E., Petersen S. Space Heating Demand Response Potential for Retrofitted Residential Apartment Blocks. Energy and Buildings 141 (2017) 158–166

[9] Kristensen, M.H, Hedegaard R.E., Petersen S. Hierarchical calibration of archetypes for urban building energy modeling. Energy and Buildings (2018) 175, 219-234

[10] Brejnrod K.N., Kalbar P., Petersen S., Birkved M. The absolute environmental performance of buildings. Building and Environment 9 (2017) 87–98

[11] Petersen S., Christensen N.U., Heinsen C., Hansen A.S. Investigation of the displacement effect of a diffuse ceiling ventilation system. Energy and Buildings 85 (2014) 265–274.

[12] Pedersen T.H., Nielsen K.U., Knudsen, M.D., Petersen S. Method for room occupancy detection based on trajectory of indoor climate sensor data. Building and Environment 115 (2017) 147–156

[13] Kristensen M.H. and Petersen S. Does embodied energy in windows affect their
energy-efficiency ranking? 12th REHVA World Conference CLIMA. Aalborg, Denmark. 2016