Early-stage optimal design of hybrid GEOTABS buildings in terms of costs and CO2 emissions

The high potential of ground source heat pumps (GSHP) to reduce the carbon dioxide emissions of heating, ventilation, and air conditioning (HVAC) systems has been widely acknowledged. GEOTABS combines GSHP systems (which generate heating and cooling) and TABS (thermally activated building structure) systems as storage-integrated emission systems. GEOTABS has been proposed to improve GSHP performance while potentially decreasing investment cost. Moreover, implementing a secondary system in parallel with GEOTABS extends the applicability of these systems to a larger variety of buildings. This combination is referred to as hybrid-GEOTABS. The dynamic behavior of TABS introduces challenges in the design of these systems including a) thermal comfort uncertainty (typically when fast disturbances occur), b) determining optimal load split between GEOTABS and the secondary system, and c) complexity in sizing the production units. In this paper, a novel dynamic simulation-based design methodology is proposed. The methodology incorporates advantages of TABS such as load-shifting and peak-shaving and produces Pareto optimal solutions. The methodology is applied to nine case studies with variable electricity prices and carbon emission dioxide factors. Results show that the optimal load split is found near the maximum physically possible share of GEOTABS. Consequently, the near-optimal design of hybridGEOTABS can be achieved using simple guidelines without solving an optimization problem. Moreover, the results show that GEOTABS always provides carbon dioxide emission savings of up to 85% but requires higher investment costs of up to 238% that of conventional systems. However, due to the operational cost savings of up to 76%, the use of GEOTABS achieved net present cost (NPC) savings of 2% to 19% in five out of the nine case studies, for 25 years of operation. Finally, it was observed that this NPC is highly sensitive to building design and economic parameters. Hence, an early-stage design analysis with iterations between the HVAC designer and the architect should be performed using case-specific economic parameter values