Key facts

  • Funding Body/Client: IEA ECB
  • Project Partners: KUL,BCIT,DTU,TUT,TTU,IBP,TUD,UP,CTH,LTH,SP
  • Total Project Value: N/A
  • UCL/IEDE Project Value Share: N/A
  • Duration:  2009-2013
  • Status: Complete

The scope of the project is to develop and provide decision support data and tools for energy retrofitting measures. The tools were based on probabilistic methodologies for prediction of energy use, life cycle cost and functional performance. The impact of uncertainty on the performance and costs was considered. Methods based on probability give powerful tools that can provide us with reliable ranges for the outcome.

The ultimate outcome of the project will be to develop knowledge and tools that support the use of probability based design strategies in retrofitting of buildings to ensure that the anticipated energy benefits can be realized. These give reliable information about the true outcome of retrofitting measures regarding energy use, cost and functional performance. The principle objective was realized by merging hygrothermal building physics with probability and economic analyses. The methods developed were then applied to optimize energy retrofitting methods. The main objectives of the project are to:

  • Develop a common framework for probabilistic assessment of energy retrofitting measures
  • Develop and validate probabilistic tools for energy use, life cycle cost and hygrothermal performance
  • Collect and analyze data in order to create stochastic data sets
  • Apply and demonstrate probabilistic methodology on (at least) five real life case studies, with a focus on residential buildings

PI- Michael Davies

Rs: Payel Das, Benjamin Jones, Valentina Marincioni and Rokia Raslan 

The project outputs include:

  • A range of probabilistic datasets regarding material properties, ventilation characteristics, airtightness, indoor loads, and weather for various external climates and housing stocks.
  • A detailed assessment of tools for probabilistic assessment of retrofitting measures, such as Monte Carlo procedures, sensitivity analyses, meta-modelling techniques, and optimization methods.
  • A framework for integrating the various tools for probabilistic assessment.
  • A detailed collection of practice and guidelines across the countries of contributing institutes, to enable the framework to be adequately tailored to each setting. 

The work has been regularly exchanged between participating institutes in bi-annual meetings, and disseminated to a range of audiences through conference attendance and publication in scientific journals. 

Annex 55 RAP-RETRO website

For further information please contact: Michael Davies