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Energies
Article . 2023 . Peer-reviewed
License: CC BY
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Energies
Article . 2023
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Evaluation of Building Mass Characterization for Energy Flexibility through Rule- and Schedule-Based Control: A Statistical Approach

Authors: Joscha Reber; Xenia Kirschstein; Nadja Bishara;

Evaluation of Building Mass Characterization for Energy Flexibility through Rule- and Schedule-Based Control: A Statistical Approach

Abstract

As renewables become more established in the electricity grid, the focus, and therefore adaptability, will need to shift from the generation side to the demand side. Since the building sector accounts for a large share of the energy demand, it will be strongly affected by this development. One possibility for adaptation is so-called demand side management (DSM). To assess the contribution of the building sector to energy flexibility, some key performance indicators (KPIs) have already been developed in previous work. In this study, we investigate and statistically compare two control strategies for temporarily raising the room temperature—one rule-based and one schedule-based—with regard to their influence on the characterization of the building mass as a type of thermal energy storage. In each case, we determine the thermal energy demand of a residential district based on a dynamic simulation that occurred for a period of one year. The rule-based control assigns in the median approximately 60% (mean: 41%) less capacity to the building mass than the schedule-based control for the same boundary conditions. The calculation of the time-independent heating load results in a median difference of 34% (mean: 36%). In addition, the establishment of energy-flexible control in the evening hours just before a night-time reduction in the room temperature has a negative impact on the efficiency of the thermal storage.

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Keywords

buildings labeling, Technology, active demand response, thermal storage, T, energy flexibility

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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
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