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Energy modelling for the built environment

Objectives: The 'PROCLIMATION' project investigated the use of probabilistic climate projections in energy modelling of the built environment. The work informs the building energy research community as well as the Chartered Institute of Building Service Engineers (CIBSE) of the methods required to take account of the probabilistic nature of the climate projections. Ultimately, the research helps CIBSE devise policy for industry to use UKCP09 projections in building simulation.

UKCP09 products used: Weather Generator; User Interface

How were UKCP09 products used?

1. The first stage for investigating development of probabilistic reference years required an understanding of the change factors used in combination with the Weather Generator to produce future reference years. Using the UKCP09 User Interface, the probabilistic change factors were selected for the above variables. A focus was given to the Medium emissions scenario and the 2050s and repeated for all available temporal averages (annual, seasonal and monthly).

2. The location of interest was identified and the grid square selected that most closely matched the location of interest (e.g. London Heathrow).

3. Using a random sample of the projections the impact of the number of requested sets of change factors on the resulting statistics associated with the change factors were investigated.

4. From this it was deemed adequate to consider the minimum of 100 sets of change factors to produce 100 x 30 years of hourly data.

5. The raw Weather Generator output was converted into weather file formats necessary for building energy modelling such as the standard TMY2 format.

6. The resulting 3,000 weather years were then used to investigate building performance (energy and thermal). Different methods for defining a subset of weather years that capture a probabilistic range such as the 80% confidence interval were investigated.

7. These looked at the impact of different assessment criteria for defining the files as well as different methods of sampling the projections via the UKCP09 User Interface.

Difficulties & limitations

Communicating the notion of probabilistic data and its application to building energy modelling to project stakeholders was difficult. The costs associated were considered a significant barrier to the uptake of these methods within industry.

Lessons learned

  • UKCP09 is a complex tool for a risk-based understanding of adaptation measures in building design and retrofit. A considered approach to the use of the Weather Generator output is essential in order to maintain and fully appreciate the statistical understanding of future climates. 
  • UKCP09 provides a more robust account of energy modelling and understanding risk of, for example, over heating or meeting low energy targets in its operation. The challenges lie within handling large amounts of data and correctly interpreting the statistical meaning of results.

How will the results be communicated to the target audience?

The work carried out under this project has three audiences, i) an academic audience ii) an industry focused audience and iii) a political audience.

In the case of the academic audience communication is through papers, conferences, reports and presentations. In the case of industry and policy, communication of results is led through stakeholder engagement via, for example, the ACN website and institutes such as CIBSE.

Find out more 

  • Contact details: Stefan Thor Smith, Victor Ian Hanby, Institute of Energy and Sustainable Development, De Montfort University.