ONGOING DEVELOPMENT OF AN EASY-TO-USE HYBRIDGEOTABS DESIGN METHODOLOGY

Rana Mahmoud and Mohsen Sharifi from University of Ghent introduce a planned design methodology for sizing GEOTABS and secondary energy sources.

Ongoing development of an easy-to-use hybridGEOTABS design methodology

The design of hybridGEOTABS requires the sizing of both the GEOTABS and the secondary energy sources consuming and expensive – especially in feasibility stage, or rule of thumb by experienced designers, that are not validated for a wider range of typologies and climates throughout Europe.

So, this project is providing a design methodology for making the hybridGEOTABS design process more accessible to building HVAC designers, and more economically feasible. In the process of developing this design methodology, we are developing an automated methodology to (1) calculate dynamic heat demand of buildings starting from general building data and (2) size the main hybridGEOTABS components using these heat demand curves. This automated process will be used to assess the sizing of numerous cases representing the EU building stock, since the whole process is automated. Easy-to-use design guidelines will then be derived from the analysis and meta-analysis of the obtained sizes for a variety of buildings and climates, taking into account the effects of optimized control.

1:

To calculate heating and cooling demand curves starting from building stock data: The building stock data contains general information about the building, similar to the data that are available for system designers in the design stages (e.g. building volume, gross floor area, U-values…). We developed a methodology that allows obtaining building energy simulation models in an automated way starting from general building information data. These data were gathered from a whole population of building stock data. An essential part in this modelling process is using a model of multi-zone archetype building that is adapted to the investigated typology (the typologies of focus in this research are offices, schools, elderly homes and multi-family buildings). Each of these archetypes is fitted to the building stock data of the individual cases. The output of this process is dynamic heating and cooling demand and load duration curves.

2:

To size main hybridGEOTABS components: On the other hand, a methodology to size main hybridGEOTABS components is developed that starts from the heat demand curves, calculated in previous part of research. The idea of this methodology is that the heating and cooling ‘baseload’ is covered by the GEOTABS, and the residual loads by the secondary system. By definition, the baseload is considered the maximum load that the TABS can provide (being a system with high thermal inertia), without wasting energy (as a result of a quick changing between heating and cooling). An algorithm is developed that allows to split the heating and cooling load curves from step (1) into a baseload and residual load, thus to size the secondary system from the maximum residual loads that appear.

The figure above shows how the two parts of this research interact: the black curve is a heat demand curve which is output of the first part of the research. The red curve is the power of GEOTABS which is the output of the second part of the research. The blue region is the share of the secondary system.