| Zdroj: |
Aachen : E.ON Energy Research Center, RWTH Aachen University, E.ON Energy Research Center ; EBC, Energy efficient buildings and indoor climate 110, 1 Online-Ressource : Illustrationen, Diagramme (2022). doi:10.18154/RWTH-2022-06640 = Dissertation, RWTH Aachen University, 2022 |
| Popis: |
Heat pumps are a key technology for decarbonizing the building sector, as they use electricity from renewable energy sources to supply heating and cooling in a resource-saving way. To reliably estimate the potential of resource conservation, it is essential to realistically predict the efficiency of energy conversion systems. However, common evaluation methods significantly neglect dynamics and the holistic evaluation of the system as a whole when determining the seasonal coefficient of performance (SCOP), which is a long-term efficiency metric for heat pumps. Predicted SCOPs are generally overestimated compared to real measured values. In addition to the energetic considerations, the demand for thermal comfort in indoor environments, which must be ensured by the energy conversion systems through space heating or cooling, is increasing nowadays. Thus, there is need to be able to evaluate energy conversion systems with respect to multi-criteria key performance indicators (KPIs) such as efficiency and comfort, which current assessment methods do not allow. This dissertation presents a novel method, which allows a holistic, multi-criteria KPI evaluation of complex energy conversion systems under realistic, dynamic boundary conditions. Applied to scenarios of heat pump systems for single-family houses, the evaluation objectives are the SCOP and the deviation of indoor temperature from its set point as representative of thermal comfort. The novel method uses the hardware-in-the-loop (HiL) concept and is referred to as “Dynamic System Evaluation” (DSE). Applying the HiL approach in this scope, the real energy system under test interacts in real-time and frequently exchanges data with dynamic simulation models of a heat transfer system and a building envelope. To apply the DSE method, the evaluation period is reduced from one year to a selection of experimental test days. In this work, we apply k-medoids clustering and demonstrate an information loss regarding the SCOP of 1.87 % due to the test time reduction from one year to four test days. Moreover, we show that the DSE method is repeatable and can be reproduced independently of the test facility and modeling language. To score the obtained results, we compare the DSE method to a pure system simulation, where the entire evaluation period of one year is assessed. In order to ensure valid system behavior of the air-to-water heat pump, which is the system under test, we perform a detailed model calibration. It turns out that the physical properties of the heat pump system can be calibrated well. In contrast, there are deviations in the operational behavior, which we can mainly ascribe to the actions of the created model of the real system controller. With respect to SCOP, the investigation leads to a relative difference of 8.43 %. The assessment of thermal comfort – primarily based on the deviations of set and actual room air temperatures – proves that the demand of space heating can be covered. In terms of the predicted mean vote (PMV) and the mean deviation of temperature residuals on each test day, the heat pump system ensures a comparable thermal comfort between the DSE method and system simulation. The mean deviation is between 2.12 K and 2.34 K. This maximum difference of 0.22 K remains in a range which is almost non-perceivable for the human body. To conclude: When a dedicated multi-criteria KPI can be defined and quantified, the reduction of the evaluation period to a selection of representative test days is verified. Hence, we recommend applying the DSE method for holistic evaluations of energy conversion systems. |
