Master's Thesis Dario Bihn
Influences of thermal energy storages analyzed in the context of heat pump systems using hardware-in-the-loop experiments
In a current research project at the Institute for Energy Efficient Buildings and Indoor Climate of
the RWTH Aachen University the long-time efficiency of heat pump systems, including thermal
energy storages and auxiliary components, is dynamically evaluated by using the hardware-inthe-
loop concept. In order to minimized the testing time, amathematical optimization method is
used to reduce the evaluation period from one year to four typical dayswhich are meteorologically
representative for one year.
In contrast to an efficiency evaluation of one year, two additional effects have to be considered if
the time horizon is reduced: firstly, there is no unique order the typical days have to be arranged in.
This is due to the fact that the typical days are selected according to their weather characteristics
and not according to their order of occurrence in a calender year. In particular this means that
there are different possible orders to evaluate the system efficiency in an experimental manner.
Secondly, by using a thermal energy storage the processes of energy production and energey usage
are decoupled from the perspective of time. In combination with a reduced evaluation period
there is the possibility of shifting energy between test days that represent different periods of the
year. For instance, thermal energy could be shifted from a winter to a summer day. As the efficiency
of the heat pump depends on the outdoor air conditions, different amounts of electrical energy
are required to generate certain amounts of heat. Due to that this evaluation of the long-time efficiency
of the heat pump system is influenced by the effect of seasonal energy shifting.
To quantify how much these effects influence the evaluation of the system efficiency, the seasonal
performance factor PF1a is determined in three experiments with different orders of the typical
days. With the aim to point out how ordering the typical days influences the system efficiency
evaluation, the mean value of the three absolute deviations aorder Æ 0.048 is derived from the experiments.
In a second step a mathematical correction method is introduced to compensate the
influence of the seasonal energy shifting on the long-time efficiency evaluation and to determine
the corrected seasonal performance factor PF€
1a. In order to quantify the influence of this method,
more specifically the influence of the seasonal energy shifting, the mean value of the three absolute
corrections ae¡shifting Æ 0.041 is determined. The comparison between aorder and ae¡shifting
points out that both effects lead to deviations in the system efficiency evaluation in terms of the
seasonal performance factor with the magnitude of 10-2 to 10-1. In this case none of these effects
Based on a final study, aiming to analyze how close a certain systembehaviour can be reproduced,
it has to be considered that the statistical scattering of the seasonal performance factors PF1a and