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Modelling and simulation of building stock is a valuable source of information for investigating the feasibility of implementing new heating and cooling system technologies. Some of these technologies have oversizing problem as the designers rely on their experience and previous knowledge. Building stock modelling can provide a solution for more accurate designing process. However, some of the current building stock modelling methods uses a representative building which can exclude whole ranges of the different combinations of building geometry and physical properties that can be crucial for heating and cooling load estimation. Therefore, we developed a methodology that allows faster and accurate building energy simulation (BES) multizone models from general building information of the whole building stock that is able to estimate load duration. This will help engineers and designers to decide on the system sizing at the early design stages. This paper presents first, the process of generating dynamically heating and cooling load duration curves by using BES-models from general geometrical data of the building stock. Second, we examine the process on a sample of the building stock where geometrical and physical parameters were varied. The workflow of the process has worked successfully, generating heating and cooling duration curves for 14 case studies. We observed that heating and cooling loads are highly influenced by different combinations of parameters. High glazing percentage affects highly the heat losses, thus more heating loads. Besides, for a west oriented building, the high glazing percentage combined with high internal gains can be the reason for significant cooling loads. In next steps, we are going to extend the current methodology to cover different building typologies within different climates across Europe.

GEOTABS, a combination of TABS with a geothermal heat pump, is a promising heating and cooling system for decreasing greenhouse gas emissions in the building sector. However, TABS has a time delay when transferring energy from the pipes to the room. So, when the heat demand changes fast, TABS cannot properly compensate the heat demand. In order to solve this problem and maintain thermal comfort in the room, the concept of hybridGEOTABS proposes using a fast secondary system to assist the TABS. Yet, there is no integrated method for sizing both systems in a hybridGEOTABS building, considering the interaction between the secondary system and GEOTABS. This study will provide an integrated sizing methodology for hybridGEOTABS buildings. To that purpose, in this paper the interaction between the secondary system and TABS is investigated for two different scenarios by using a preference factor between the TABS and the secondary system. The methodology starts from heat demand curves, an analytic model for TABS, and optimal control principles for TABS to minimize the total energy use while providing thermal comfort. Finally, the method is used for 4 case studies in different scenarios with different secondary systems. Preliminary results of this research indicate that the secondary system type doesn’t have effect on the strategy of sizing. Therefore, designer can decide about secondary system type with investment and operating cost analysis.

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Detailed building models allow the HVAC designers to find optimal solutions. However, more complexity in modelling will also result in more efforts for the designers in the component sizing procedure specially when the optimal design of the system is highly depended on the control system. In Thermally Activated Building Systems (TABS), which are embedded pipes in the concrete of the building structure, the role of control is pivotal and thus the control has to be simulated during the design. Therefore, the building model and optimal control has to be coupled to an optimisation algorithm for optimal component sizing. This results in a computationally heavy design procedure. This paper addresses the need for a for a simplified methodology for modelling building with TABS. The dynamic heating and cooling loads of the building is calculated by a white-box detailed Modelica model and later used in an equivalent simplified resistorcapacitor (RC) model. The simplified model was developed by the grey-box approach and the parameters of RC model were estimated by inverse modelling approach. The methodology was applied on three different case studies and the results imply that the developed methodology can be confidently coupled to an optimal control algorithm to be used for sizing HVAC components optimally. Key Innovations• An automated algorithm for simplified dynamic modelling of building with TABS • Taking the advantage of white-box modelling to have high accuracy Practical ImplicationsA simplified modelling approach is proposed to simulate TABS and building interactions. The methodology can be efficiently integrated to the optimal design methodologies due its low mathematical complexity.