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Optimal day-to-day scheduling of multiple energy assets in residential buildings equipped with variable-speed heat pumps

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  • Efkarpidis, Nikolaos A.
  • Vomva, Styliani A.
  • Christoforidis, Georgios C.
  • Papagiannis, Grigoris K.

Abstract

The largest parts of energy demand within the residential sector are used for space heating (SH), domestic hot water (DHW) and space cooling (SC). The thermal and electrical needs can be mainly covered by energy systems that consist of Photovoltaics (PVs), solar thermal collectors (STCs), heat pumps (HPs) and flexibility sources, e.g. battery energy storage (BES) and thermal energy storage (TES). In this paper, various control strategies for the optimal day-to-day operation of residential energy systems that consist of a variable-speed HP, STCs, PVs, as well as BES and TES units are examined. The proposed strategies are based on the concepts of self-consumption maximization (SCM) and time-of-use arbitrage (ToUA) considering priorities on BES and TES charging. A typical Greek single-family building is assumed examining multiple criteria for the assessment of the rule-based approaches. The results demonstrate that priority on TES charging can lead to higher system performance than on BES charging. Regardless of the number of ToU tariff zones, during off/mid-peak periods the upper energy needs of the SH/SC trajectory should be fulfilled only in case of excess PV power, otherwise the cost of imported energy increases significantly. Both SCM and ToUA strategies can lead to rates of self-consumption and self-sufficiency that deviate in average per about 4% from the optimal values. Moreover, the ToUA-based strategies can approach the minimum cost of imported energy with a relative increase of 22% compared to the optimum. However, the minimum thermal discomfort due to space temperature cannot be achieved without the prediction of the daily SH/SC demand. Furthermore, the proposed strategies can reach the minimum thermal discomfort due to DHW losses, while leading to lower BES degradation rates than the optimization. Finally, from the multi-objective optimization for the first year of system operation, it is verified that the optimal dimensioning of PV, BES and TES is considerably affected by the type of rule-based strategy selected.

Suggested Citation

  • Efkarpidis, Nikolaos A. & Vomva, Styliani A. & Christoforidis, Georgios C. & Papagiannis, Grigoris K., 2022. "Optimal day-to-day scheduling of multiple energy assets in residential buildings equipped with variable-speed heat pumps," Applied Energy, Elsevier, vol. 312(C).
    • Handle: RePEc:eee:appene:v:312:y:2022:i:c:s0306261922001635
    DOI: 10.1016/j.apenergy.2022.118702
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    2. Brudermueller, Tobias & Kreft, Markus & Fleisch, Elgar & Staake, Thorsten, 2023. "Large-scale monitoring of residential heat pump cycling using smart meter data," Applied Energy, Elsevier, vol. 350(C).
    3. Chen, Minghao & Xie, Zhiyuan & Sun, Yi & Zheng, Shunlin, 2023. "The predictive management in campus heating system based on deep reinforcement learning and probabilistic heat demands forecasting," Applied Energy, Elsevier, vol. 350(C).
    4. Víctor Sanz i López & Ramon Costa-Castelló & Carles Batlle, 2022. "Literature Review of Energy Management in Combined Heat and Power Systems Based on High-Temperature Proton Exchange Membrane Fuel Cells for Residential Comfort Applications," Energies, MDPI, vol. 15(17), pages 1-22, September.
    5. Maier, Laura & Schönegge, Marius & Henn, Sarah & Hering, Dominik & Müller, Dirk, 2022. "Assessing mixed-integer-based heat pump modeling approaches for model predictive control applications in buildings," Applied Energy, Elsevier, vol. 326(C).

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