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Investigating the impact of smart energy management system on the residential electricity consumption in Austria

Author

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  • Mascherbauer, Philipp
  • Kranzl, Lukas
  • Yu, Songmin
  • Haupt, Thomas

Abstract

This paper addresses the following question: How can smart energy management system (SEMS) influence the residential electricity consumption at both individual household and national level? First, we developed an hourly optimization model for individual households. The energy cost of an individual household is minimized under given assumptions on outside temperature, radiation, (dynamic) electricity price, and feed-in tariff. By comparing the optimization to the reference scenario, we show the impact of SEMS on grid-electricity consumption and photovoltaic (PV) selfconsumption at the individual household level. Second, to aggregate the results to the national level, we constructed a detailed building stock taking Austria as an example. By aggregating the results of 2112 representative households, we investigate the impact of SEMS in the residential building stock on the national electricity system. As a result, we found that for individual singlefamily-houses (SFHs) with PV (no battery) and heat pump adoption, SEMS can significantly reduce the grid-electricity consumption up to 40.7% for a well-insulated building. At the national level we found that, for the buildings with 5 kWp PV but without hot water tank or battery storage, SEMS can still reduce the grid-electricity consumption by 7.4% by using the building mass as thermal storage.

Suggested Citation

  • Mascherbauer, Philipp & Kranzl, Lukas & Yu, Songmin & Haupt, Thomas, 2022. "Investigating the impact of smart energy management system on the residential electricity consumption in Austria," Working Papers "Sustainability and Innovation" S04/2022, Fraunhofer Institute for Systems and Innovation Research (ISI).
    • Handle: RePEc:zbw:fisisi:s042022
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    References listed on IDEAS

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    1. Le Dréau, J. & Heiselberg, P., 2016. "Energy flexibility of residential buildings using short term heat storage in the thermal mass," Energy, Elsevier, vol. 111(C), pages 991-1002.
    2. William E. Hart & Carl D. Laird & Jean-Paul Watson & David L. Woodruff & Gabriel A. Hackebeil & Bethany L. Nicholson & John D. Siirola, 2017. "Pyomo — Optimization Modeling in Python," Springer Optimization and Its Applications, Springer, edition 2, number 978-3-319-58821-6, September.
    3. Klingler, Anna-Lena, 2018. "The effect of electric vehicles and heat pumps on the market potential of PV + battery systems," Energy, Elsevier, vol. 161(C), pages 1064-1073.
    4. Kuczyński, T. & Staszczuk, A., 2020. "Experimental study of the influence of thermal mass on thermal comfort and cooling energy demand in residential buildings," Energy, Elsevier, vol. 195(C).
    5. Yildiz, Baran & Bilbao, Jose I. & Roberts, Mike & Heslop, Simon & Dore, Jonathon & Bruce, Anna & MacGill, Iain & Egan, Renate J. & Sproul, Alistair B., 2021. "Analysis of electricity consumption and thermal storage of domestic electric water heating systems to utilize excess PV generation," Energy, Elsevier, vol. 235(C).
    6. Heinen, Steve & Turner, William & Cradden, Lucy & McDermott, Frank & O'Malley, Mark, 2017. "Electrification of residential space heating considering coincidental weather events and building thermal inertia: A system-wide planning analysis," Energy, Elsevier, vol. 127(C), pages 136-154.
    7. Chen, Yongbao & Xu, Peng & Chen, Zhe & Wang, Hongxin & Sha, Huajing & Ji, Ying & Zhang, Yongming & Dou, Qiang & Wang, Sheng, 2020. "Experimental investigation of demand response potential of buildings: Combined passive thermal mass and active storage," Applied Energy, Elsevier, vol. 280(C).
    8. Salpakari, Jyri & Rasku, Topi & Lindgren, Juuso & Lund, Peter D., 2017. "Flexibility of electric vehicles and space heating in net zero energy houses: an optimal control model with thermal dynamics and battery degradation," Applied Energy, Elsevier, vol. 190(C), pages 800-812.
    9. Luthander, Rasmus & Widén, Joakim & Nilsson, Daniel & Palm, Jenny, 2015. "Photovoltaic self-consumption in buildings: A review," Applied Energy, Elsevier, vol. 142(C), pages 80-94.
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    Keywords

    demand-side management; PV; heat pump; energy storage; optimization; building stock;
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