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Assessment of the Impact of Using a Smart Thermostat and Smart Meter Data on a Whole-Building Energy Simulation

Author

Listed:
  • Sukjoon Oh

    (Department of Building Research, Korea Institute of Civil Engineering and Building Technology, Goyang-si 10223, Korea)

  • Juan-Carlos Baltazar

    (Energy Systems Laboratory, Texas A&M Engineering Experiment Station, Bryan, TX 77807, USA
    Department of Architecture, Texas A&M University, College Station, TX 77843, USA)

  • Jeff S. Haberl

    (Energy Systems Laboratory, Texas A&M Engineering Experiment Station, Bryan, TX 77807, USA
    Department of Architecture, Texas A&M University, College Station, TX 77843, USA)

Abstract

Building energy simulation models have been used to assist the design and/or optimization of buildings energy performance. The results from building energy simulation models can be more reliable when measured energy use data, indoor environmental condition data, system operation status, and coincident weather data are used to validate the simulation results. In this paper, given the wide-spread use of home automation devices in residential buildings, we studied how well a residential building energy simulation model can be tuned using measured interval data from a smart thermostat and smart meter. The analysis is based on a multi-stage approach that can help improve the reliability of the use of building energy simulation models that reflect both the indoor air temperature and whole-building energy use. Results from changing the input parameters in the building simulation show that the comparison of the simulated and measured indoor temperatures fall in a range below a NMBE of 1.5% and a CV-RMSE of 2.2%, while the simulated whole-building energy use matches the measured energy use below a NMBE of −2.7% and a CV-RMSE of 10.9%. We found that the most significant parameters for the indoor air temperature and whole-building energy use were the effective U-value for the slab-on-grade floor and the heating and cooling system operation status, respectively.

Suggested Citation

  • Sukjoon Oh & Juan-Carlos Baltazar & Jeff S. Haberl, 2022. "Assessment of the Impact of Using a Smart Thermostat and Smart Meter Data on a Whole-Building Energy Simulation," Sustainability, MDPI, vol. 14(10), pages 1-21, May.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:10:p:6299-:d:821029
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    References listed on IDEAS

    as
    1. Enrico Fabrizio & Valentina Monetti, 2015. "Methodologies and Advancements in the Calibration of Building Energy Models," Energies, MDPI, vol. 8(4), pages 1-27, March.
    2. Germán Ramos Ruiz & Carlos Fernández Bandera, 2017. "Validation of Calibrated Energy Models: Common Errors," Energies, MDPI, vol. 10(10), pages 1-19, October.
    3. Israel Torres Pineda & Jeong Hwa Cho & Dongkeun Lee & Sang Min Lee & Sangseok Yu & Young Duk Lee, 2020. "Environmental Impact of Fresh Tomato Production in an Urban Rooftop Greenhouse in a Humid Continental Climate in South Korea," Sustainability, MDPI, vol. 12(21), pages 1-13, October.
    4. Mustafaraj, Giorgio & Marini, Dashamir & Costa, Andrea & Keane, Marcus, 2014. "Model calibration for building energy efficiency simulation," Applied Energy, Elsevier, vol. 130(C), pages 72-85.
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    Cited by:

    1. Sukjoon Oh & John F. Gardner, 2022. "Energy Consumption Analysis Using Measured Data from a Net-Zero Energy Commercial Building in a Cold and Dry Climate," Sustainability, MDPI, vol. 14(16), pages 1-22, August.

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