Optimization of concurrency of PV-generation and energy demand for a heat pump – comparison of a monitored building and simulation data
06 - Präsentation
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Monitoring data of a small, well-insulated residential building shows that the electricity consumption of the heat pump amounts to approx. 30% of the total electricity consumption of the building. Shifting duty cycles of the heat pump into the daytime would therefore be a possible means to greatly increase the concurrency of electricity production and consumption and reduce the grid interaction without an expensive technical effort. Experimentally, the duty cycle of the heat pump is limited to daytime from 10 am through 7 pm. The monitored data shows this is sufficient to heat the building and the domestic hot water. Interesting questions that arise are e.g. if such run-time limitations can also be used with a heavy (concrete) and a lightweight (wood) construction and if further reduction of the run-time is possible. Reducing run-time even more would further increase self-consumption and reduce grid interaction. The impact of the thermal mass of the construction and the limiting of the runtime are investigated by transient thermal building simulation. The simulation model with constructions “as built” is calibrated based on measurement values from temperature sensors in the living rooms and the measured heating demand of all three apartments. Simulation results are evaluated based on thermal comfort criteria in the living rooms of each apartment. The results obtained show that for the construction types “as built” and “heavyweight” no differences in resulting thermal comfort are to be expected. Construction types “as built” and “heavy weight” show good robustness in regard to the limitation of the run-time of the heat pump. The construction type “lightweight” cannot be used with limited run-times of the heat pump without a significant drop in thermal comfort as defined by the metrics used. The paper gives detailed results for the mentioned construction types and 4 different run-time scenarios.