LAPSE:2023.15038
Published Article
LAPSE:2023.15038
Real-Time Grid Signal-Based Energy Flexibility of Heating Generation: A Methodology for Optimal Scheduling of Stratified Storage Tanks
Matthias Eydner, Lu Wan, Tobias Henzler, Konstantinos Stergiaropoulos
March 2, 2023
Heat pumps coupled with thermal energy storage (TES) systems are seen as a promising technology for load management that can be used to shift peak loads to off-peak hours. Most of the existing model predictive control (MPC) studies on tariff-based load shifting deploying hot water tanks use simplified tank models. In this study, an MPC framework that accounts for transient thermal behavior (i.e., mixing and stratification) by applying energy (EMPC) and exergy (XMPC) analysis is proposed. A case study for an office building equipped with an air handling unit (AHU) revealed that the MPC strategy had a high load-shifting capacity: over 80% of the energy consumption took place during off-peak hours when there was an electricity surplus in the grid. An analysis of a typical day showed that the XMPC method was able to provide more appropriate stratification within the TES for all load characteristics. An annual exergy analysis demonstrated that, during cold months, energy degradation in the TES is mainly caused by exergy destruction due to irreversibility, while, during the transition to milder months, exergy loss dominates. Compared to the EMPC approach, the XMPC strategy achieves additional reductions of 18% in annual electricity consumption, 13% in operating costs, and almost 17% in emissions.
Keywords
active demand response, energy flexibility, exergy analysis, Model Predictive Control, stratified hot water storage tank
Suggested Citation
Eydner M, Wan L, Henzler T, Stergiaropoulos K. Real-Time Grid Signal-Based Energy Flexibility of Heating Generation: A Methodology for Optimal Scheduling of Stratified Storage Tanks. (2023). LAPSE:2023.15038
Author Affiliations
Eydner M: Institute for Building Energetics, Thermotechnology and Energy Storage (IGTE), University of Stuttgart, 70565 Stuttgart, Germany
Wan L: Institute for Building Energetics, Thermotechnology and Energy Storage (IGTE), University of Stuttgart, 70565 Stuttgart, Germany
Henzler T: Institute for Building Energetics, Thermotechnology and Energy Storage (IGTE), University of Stuttgart, 70565 Stuttgart, Germany
Stergiaropoulos K: Institute for Building Energetics, Thermotechnology and Energy Storage (IGTE), University of Stuttgart, 70565 Stuttgart, Germany
Journal Name
Energies
Volume
15
Issue
5
First Page
1793
Year
2022
Publication Date
2022-02-28
Published Version
ISSN
1996-1073
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Original Submission
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PII: en15051793, Publication Type: Journal Article
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doi:10.3390/en15051793
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