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Determination of a Building's balance point temperature as an energy characteristic

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  • Krese, Gorazd
  • Lampret, Žiga
  • Butala, Vincenc
  • Prek, Matjaž

Abstract

The building's balance point temperature represents the outdoor temperature at which no auxiliary energy is needed to ensure thermal comfort. Its estimation presents the main challenge of applying the degree day method for space cooling applications, since in addition to building thermal characteristics it also depends on internal and external heat gains. In this paper, a new approach for determining the instantaneous balance point temperature, based on an optimization-based grey-box modelling procedure, is presented. The developed grey-box model is built on an assumed functional dependency between the building thermal load and the power demand of its HVAC system. Its application requires only the use of basic building geometric parameters apart from the cooling electricity demand and corresponding meteorological data, which are utilized to estimate the model parameters using a derivate-free optimization procedure. Additionally, a new technique for visualizing and analyzing the behavior of the obtained instantaneous balance point temperature is introduced. The proposed methodology is verified on a set of artificially generated data, achieving an average prediction error of 5.2%, and its applicability demonstrated on a sample of real tertiary sector buildings. The results indicate that the presented methodology can be used to deduce building and corresponding HVAC system characteristics.

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  • Krese, Gorazd & Lampret, Žiga & Butala, Vincenc & Prek, Matjaž, 2018. "Determination of a Building's balance point temperature as an energy characteristic," Energy, Elsevier, vol. 165(PB), pages 1034-1049.
    • Handle: RePEc:eee:energy:v:165:y:2018:i:pb:p:1034-1049
    DOI: 10.1016/j.energy.2018.10.025
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    1. Papakostas, K. & Kyriakis, N., 2005. "Heating and cooling degree-hours for Athens and Thessaloniki, Greece," Renewable Energy, Elsevier, vol. 30(12), pages 1873-1880.
    2. Psiloglou, B.E. & Giannakopoulos, C. & Majithia, S. & Petrakis, M., 2009. "Factors affecting electricity demand in Athens, Greece and London, UK: A comparative assessment," Energy, Elsevier, vol. 34(11), pages 1855-1863.
    3. Kim, Wonuk & Jeon, Yongseok & Kim, Yongchan, 2016. "Simulation-based optimization of an integrated daylighting and HVAC system using the design of experiments method," Applied Energy, Elsevier, vol. 162(C), pages 666-674.
    4. Luis Rios & Nikolaos Sahinidis, 2013. "Derivative-free optimization: a review of algorithms and comparison of software implementations," Journal of Global Optimization, Springer, vol. 56(3), pages 1247-1293, July.
    5. Dombaycı, Ö. Altan, 2009. "Degree-days maps of Turkey for various base temperatures," Energy, Elsevier, vol. 34(11), pages 1807-1812.
    6. Isaac, Morna & van Vuuren, Detlef P., 2009. "Modeling global residential sector energy demand for heating and air conditioning in the context of climate change," Energy Policy, Elsevier, vol. 37(2), pages 507-521, February.
    7. Sailor, David J. & Muñoz, J.Ricardo, 1997. "Sensitivity of electricity and natural gas consumption to climate in the U.S.A.—Methodology and results for eight states," Energy, Elsevier, vol. 22(10), pages 987-998.
    8. Melo, A.P. & Cóstola, D. & Lamberts, R. & Hensen, J.L.M., 2014. "Development of surrogate models using artificial neural network for building shell energy labelling," Energy Policy, Elsevier, vol. 69(C), pages 457-466.
    9. 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.
    10. Ihara, T. & Genchi, Y. & Sato, T. & Yamaguchi, K. & Endo, Y., 2008. "City-block-scale sensitivity of electricity consumption to air temperature and air humidity in business districts of Tokyo, Japan," Energy, Elsevier, vol. 33(11), pages 1634-1645.
    11. Olonscheck, Mady & Holsten, Anne & Kropp, Jürgen P., 2011. "Heating and cooling energy demand and related emissions of the German residential building stock under climate change," Energy Policy, Elsevier, vol. 39(9), pages 4795-4806, September.
    12. Sivak, Michael, 2009. "Potential energy demand for cooling in the 50 largest metropolitan areas of the world: Implications for developing countries," Energy Policy, Elsevier, vol. 37(4), pages 1382-1384, April.
    13. Durmayaz, Ahmet & Kadıoǧlu, Mikdat & Şen, Zekai, 2000. "An application of the degree-hours method to estimate the residential heating energy requirement and fuel consumption in Istanbul," Energy, Elsevier, vol. 25(12), pages 1245-1256.
    14. Papakostas, K. & Mavromatis, T. & Kyriakis, N., 2010. "Impact of the ambient temperature rise on the energy consumption for heating and cooling in residential buildings of Greece," Renewable Energy, Elsevier, vol. 35(7), pages 1376-1379.
    15. Nagy, Zoltán & Rossi, Dino & Hersberger, Christian & Irigoyen, Silvia Domingo & Miller, Clayton & Schlueter, Arno, 2014. "Balancing envelope and heating system parameters for zero emissions retrofit using building sensor data," Applied Energy, Elsevier, vol. 131(C), pages 56-66.
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