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Large Scale Energy Signature Analysis: Tools for Utility Managers and Planners

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  • Sukjoon Oh

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

  • John F. Gardner

    (Mechanical and Biomedical Engineering, Boise State University, 1910 University Drive, Boise, ID 83725, USA)

Abstract

Building energy signature analysis is a well-established tool for understanding the temperature sensitivity of building energy consumption and measuring energy savings. This tool has been used to measure energy savings of residential, commercial, and even industrial buildings. The public availability of electricity loads (i.e., hourly electricity demand (MW)) from entire Balancing Authorities (BAs) provide an interesting opportunity to apply this approach to a large aggregate load. In this paper, we explore that opportunity for BAs and show that the correlations for large geographical areas are surprisingly coherent when the change-point linear regression analysis is used with the daily interval data of electricity demand and outside air temperature. The change-point linear regression models of all the BAs, except WAUW and OVEC, show R 2 of 0.70 or more and CV-RMSE of 10.0% or less. We also suggest an analysis method that allows for meaningful comparisons between BAs and to assess changes in time for a given BA which could be used to interpret changes in load patterns year-to-year, accounting for changes in weather. This approach can be used to verify the impact of energy efficiency programs on a building component/system-wide basis. This study shows the annual electricity demand reductions for SCL and IPCO are 136,655 MWh (1.5%) and 182,053 MWh (1.1%), respectively.

Suggested Citation

  • Sukjoon Oh & John F. Gardner, 2022. "Large Scale Energy Signature Analysis: Tools for Utility Managers and Planners," Sustainability, MDPI, vol. 14(14), pages 1-19, July.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:14:p:8649-:d:863018
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    References listed on IDEAS

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    1. Büyükalaca, Orhan & Bulut, Hüsamettin & YIlmaz, Tuncay, 2001. "Analysis of variable-base heating and cooling degree-days for Turkey," Applied Energy, Elsevier, vol. 69(4), pages 269-283, August.
    2. Martin Eriksson & Jan Akander & Bahram Moshfegh, 2022. "Investigating Energy Use in a City District in Nordic Climate Using Energy Signature," Energies, MDPI, vol. 15(5), pages 1-22, March.
    3. Bukarica, Vesna & Tomšić, Željko, 2017. "Energy efficiency policy evaluation by moving from techno-economic towards whole society perspective on energy efficiency market," Renewable and Sustainable Energy Reviews, Elsevier, vol. 70(C), pages 968-975.
    4. Kelly Kissock, J. & Eger, Carl, 2008. "Measuring industrial energy savings," Applied Energy, Elsevier, vol. 85(5), pages 347-361, May.
    5. Christine S. M. Currie & Trivikram Dokka & John Harvey & Arne K. Strauss, 2018. "Future research directions in demand management," Journal of Revenue and Pricing Management, Palgrave Macmillan, vol. 17(6), pages 459-462, December.
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