The building sector is responsible for more than 30% of the total energy consumption (Perez et al., 2008). Glazing and the associated solar heat gains greatly affect a building's energy consumption, particularly under the warmer climatic conditions due to the effects of climate change (Berger et al., 2014; Hopfe and McLeod, 2015). Particularly in low energy building design concepts (e.g Passivhaus), the windows play a major role in ensuring thermal comfort (Hopfe and McLeod, 2015). The solar radiation admitted through the glazed envelope is a major factor in determining the total cooling load and thermal comfort of the occupants in general. However, it is not easy to estimate accurately this effect due to its transient and dynamic nature (Evola et al.,2015).

Aims
The aim of the research project is to explore the accuracy of calculating sunlight exposure in current steady-state and dynamic methodologies. Furthermore, with the combination of the SBI and lumped parameter modelling, the research study is going to assess the contribution of the SBI in representing accurately the solar gains in a space and propose a more detailed procedure that could be incorporated into current methodologies (e.g. Passivhaus) and future EU/CEN guidelines and legislations.

Objectives
The objectives of the research project are:

Analysis of the methodology of modelling and estimating the solar exposure used in current steady-state and dynamic building performance simulation methods.

Generation of a model in order to assess the accuracy of calculating sunlight accessibility using the aforementioned simulation methods.

Use of the lumped parameter modelling methodology in order to establish a link between sunlight exposure, calculated using the SBI method, and solar heat gains.

Investigation of the effectiveness and accuracy of coupling the SBI with the lumped parameter modelling methodology.

Examination of the overall performance and effectiveness of the SBI methodology and establishment of a template that could be integrated into current/future legislations, regarding the effect of glazing on low energy building design.

References
Berger T., Amann C., Formayer H., Korjenic A., Pospichal B., Neururer C., Smutny R., 2014. Impacts of urban location and climate change upon energy demand of office buildings in Vienna, Austria, Building and Environment 81 (2014), 258-269
Evola G. Marletta L., 2015. The Solar Response Factor to calculate the cooling load induced by solar gains. Applied Energy 160, 2015, 431-441.
Hopfe, CJ., McLeod, RS, 2015. The Passivhaus Designers Manual, Routlede
Kircher Kevin J., Zhang K. Max, 2015. On the lumped capacitance approximation accuracy in RC network building models. Energy and Buildings 108, 2015, 454-462.
Mardaljevic J., Roy N., 2016. The sunlight beam index. Lighting Res. Technol. Vol. 48, 2016, 55-69.
Perez-Lombard L., Ortiz J., Pout C., 2008. A review on buildings energy consumption information, Energy Build. 40 (2008), 394-398.