Key facts

  • Funding Body/Client:  FP6
  • Project Partners:  De Montfort University 
  • Total Project Value:  N/A 
  • UCL/IEDE Project Value Share: N/A
  • Duration: 2009-2012
  • Status: Complete

This project was part of the 2 million Euro FP6 Marie-Curie Actions Research Training Network: CityNet focusing on developing a model for energy consumption in office buildings at a stock level. Different HVAC systems have different energy requirements when responding to the same building heating and cooling demands. On the other hand, building heating and cooling demands depend on various parameters such as building fabrics, glazing ratio, building form, occupancy pattern, and many others. HVAC systems energy requirements and building energy demands can be determined by mathematical modelling. 

The widely accepted approach among building professionals is to use building energy simulation tools such as EnergyPlus, IES, DOE2, etc. which can precisely predict building energy consumption. However, preparing and running simulations in such tools is usually very complicated, time consuming and costly. Their complexity has been identified as the biggest obstacle. Adequate alternatives to complex building energy simulation tools are regression models which can provide results in an easier and faster way.  

This research deals with the development of regression models which enable the selection of HVAC system for office buildings. In addition, the models are able to predict annual heating, cooling and auxiliary energy requirements of different HVAC systems as a function of office building heating and cooling demands. 

As the first part of the data set development used for the regression analysis, the data set of office building simulation archetypes was developed. The four most typical building built forms narrow plan, open plan, combination of two and court-yard) were coupled with five types of building fabrics, three levels of glazing ratio, two measures of solar heat gains protection and daylight control. 

In total 3840 different office buildings were then further coupled with five different HVAC systems: variable air volume system, constant air volume system, fancoil system with dedicated air, chilled ceiling system with embedded pipes, dedicated air and radiator heating, and chilled ceiling system with exposed aluminium panels, dedicated air and radiator heating. 

Results indicate that it is possible to form reliable judgement about different HVAC systems heating, cooling and auxiliary energy requirements based only on office building heating and cooling demands. High coefficients of determination of proposed regression models prove that HVAC systems requirements can be predicted with great accuracy. 

Co-I: Ljiljana Marjanovic-Halburd 

The following publication have been produced as a result of the work undertaken for this project:

  • Korolija, I., Zhang, Y., Hanby, V. I., & Marjanovic-Halburd, L. (2013). Regression models for predicting UK office building energy consumption from heating and cooling demands. Energy and Buildings, 59, 214-227. 
  • Korolija, I., Zhang, Y., Hanby, V. I., & Marjanovic-Halburd, L. (2013). UK office buildings archetypal model as methodological approach in development of regression models for predicting building energy consumption from heating and cooling demands. Energy and Buildings, 60, 152-162. 

This research was part of the Marie-Curie Research Training Network (RTN) CITYNET, funded under the FP 6, "People" by the European Commission. CITYNET aims to provide education on an international level for excellent post graduate students by co-working on a common scientific project as part of their PhD thesis. The scientific work is accompanied by training courses and networking activities in order to complement the fellow’s scientific education with international research and industrial networks and secondary skills for their future career development.

Apart from Early Stage Researcher training and networking, CITYNET scientifically focuses on the development of tools to improve the energy management of large scale urban settlements. The common scope of the network research activities is to establish an innovative internet based on-line tool for planning, managing and operating urban quarters with low energy consumption and high renewable energy fraction in order to reduce up to 30% of state of the art quarters CO2-emissions.  

This system will provide internet on-line monitoring, simulation and visualization using a Geographical Information System (GIS) software as the front end. CITYNET consists of eight university research groups from six different European member countries and Turkey as an associated candidate-country and additionally involves commercial enterprises as well as community authorities as hosts for visits. The research is carried out in civil, mechanical and environmental engineering as well as architecture, computer science and economy.

The results from this research project as part of the wide and multidisciplinary CITYNET network and its open access on-line web-tool potentially have very wide impact not only on academic community but also all built environment professionals interested not only in the prediction of office building energy consumption but equally energy demand and supply planning and modelling.  

For further information please contact: Ljiljana Marjanovic-Halburd