A university researcher is aiming to close the performance gap by coming up with a software tool that can give a more realistic prediction of the energy consumption of buildings.
Architects’ current predictions of potential energy consumption of new buildings can be very inaccurate, leaving buildings consuming up to twice as much energy as designers expect. A scientist at the University of Huddersfield is developing a dynamic behaviour model (DBM) that will use realistic data to make a much more accurate prediction of the energy usage of non-domestic buildings. DBM will take into account a range of factors, such as occupancy level, the behaviour of the building’s occupants, equipment use and the nature of the business.
Song Wu, professor of surveying and IT at the university’s school of art, design and architecture, has been granted a Newton Research Collaboration Award by the Royal Academy of Engineering for the project. He will work closely with the Huazhong University of Science and Technology (HUST) in China, where a proliferation of new building means that suitable case studies are easier to identify.
A new exhibition centre in Wuhan, China, is to be the focus of the first phase of research. HUST researchers will gather observational data and Huddersfield’s Wu will use it to create a computer model.
“When you design a building you do a prediction of what potential energy consumption will be,” said Wu. “But when you compare that with actual usage, the gap can be between 50 to 100 percent.” This performance gap arises because architects or engineers might not have a full understanding of how the building is going to be used, he continued. They have to make a great many assumptions based on benchmark data in order to arrive at an energy analysis. But when occupants of the building behave differently, and other factors come into play, the predicted level of energy use is often highly inaccurate.”
He continued: “What we are now trying to do with DBM is to develop a platform, or technology, that can simulate the usage of a building dynamically.
“If you have an understanding of how a building is potentially going to be used, then you can put into the simulation platforms and you run it to generate data, which is based on occupancy, and this can become input for an accurate energy analysis tool.”
In addition to providing data about energy, the model – based on actual usage and occupancy of a building – could have other applications, such as security and acoustics.