| Summary: | Due to the ongoing climate change, new energy efficient solutions with long-term effects are being sought, which should replace known energy systems with more efficient ones. This thesis arose from the occasion to find out whether the underground seasonal thermal energy storage, (USTES), is superior to the well-known borehole thermal energy storage (BTES) system. In this thesis, the energy balances and the different model structures are explained in a direct comparison in order to determine the more efficient system. The comparison is guided by three key questions, mostly related to the USTES system. These questions relate to: The amount of energy that can be stored, the amount of energy obtained from the storage and how the USTES has advantages over the BTES. In order to create optimal conditions for a comparison, the same approximately 150 m2 recreational house located in northern Finland with two apartments and utility building is used for both models. IDA-ICE, an energy simulation software, is used to create a 3D energy simulation model of the house. A set-up is created for both systems, which is described in detail. Both of these systems are then simulated in order to answer the key questions and finally to demonstrate the advantages of the USTES system. Both models are simulated over a period of one year in order to include summer- and wintertime in the total energy balance. The software IDA-ICE includes many factors, such as the location, the climate and the ground conditions, thus enables a very real simulation. The USTES model was additionally checked by an expert for IDA-ICE simulations. The results of the simulation show that the USTES system requires less purchased energy compared to BTES. The USTES has a slightly greater overall energy consumption due to the additional components, but the amount of purchased energy (electricity) is 60% lower. This knowledge is decisive for the further planning process of the house. On the other side, this could be an approach for further research in the optimization ...
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