A new research project being undertaken by the University of Sheffield into the use of predictive modelling to save energy in non-domestic buildings, is drawing on expertise and data from leading smoke and environmental ventilation specialist, SE Controls, to help support the study.
Funded by a grant from the Engineering and Physical Sciences Research Council (EPSRC), the new research programme explores the potential of making energy savings of up to 25 per cent through the development and use of Model Predictive Control (MPC) in commercial buildings.
The project will use advanced machine learning techniques, a branch of artificial intelligence, to construct a building control system that produces good internal conditions while using the smallest amount of energy possible, allowing more sustainable design and usage.
This knowledge and expertise of controlling natural ventilation was one of the reasons behind SE Controls being invited to form part of the project steering group for the MPC research.
SE Controls’ Design Manager, Dr. Chris Iddon, who will attend the steering group meetings, explained:
“Non-domestic buildings, such as office spaces, currently account for 18 per cent of the UK’s carbon emissions and between 40-90 per cent of this is energy consumed in the heating and cooling of buildings. Also, data from The Carbon Trust estimates that around £500 million worth of energy is wasted by commercial buildings every year, so this research into more effective building control and management is essential.”
In addition to the involvement of SE Controls, academics from the university’s departments of Civil & Structural Engineering, Electronic & Electrical Engineering and School of Architecture are also working with other leading industry partners, including Arup, Buro Happold, LCMB and Trend Control Systems as part of the process of exploring methods to make MPC economically viable for building energy management.
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