IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v16y2023i22p7485-d1276035.html
   My bibliography  Save this article

Radiators Adjustment in Multi-Family Residential Buildings—An Analysis Based on Data from Heat Meters

Author

Listed:
  • Karol Bandurski

    (Faculty of Environmental Engineering and Energy, Institute of Environmental Engineering and Building Installations, Poznań University of Technology, Berdychowo 4, 60-965 Poznań, Poland)

  • Andrzej Górka

    (Faculty of Environmental Engineering and Energy, Institute of Environmental Engineering and Building Installations, Poznań University of Technology, Berdychowo 4, 60-965 Poznań, Poland)

  • Halina Koczyk

    (Faculty of Environmental Engineering and Energy, Institute of Environmental Engineering and Building Installations, Poznań University of Technology, Berdychowo 4, 60-965 Poznań, Poland)

Abstract

Energy is consumed in buildings through the use of various types of energy systems, which are controlled by the occupants via provided interfaces. The quality of this control should be verified to improve the efficiency of the systems and for the comfort of the occupants. In the case of residential buildings, due to privacy reasons, it is problematic to directly monitor human–building interactions using sensors installed in dwellings. However, data from increasingly common smart meters are easily available. In this paper, the potential use of data from heat meters is explored for the analysis of occupant interactions with space-heating (SH) systems. A pilot study is conducted based on a one-year set of daily data from 101 dwellings. First, the identification of an indoor temperature and a strategy for thermostatic radiator valve (TRV) adjustments for all the investigated dwellings is presented. Second, the performed analysis suggests that 96% of the households did not use the automatic adjustment function of the TRVs since adjustments using the on–off mode were the most common, which could be empirical evidence for Kempton’s theory on mental models of home heating controls. The reasons for this could be the weakness of the TRV as an SH interface and the technical specificity of the analyzed SH (its supply temperature). The preliminary investigation confirms the potential of the proposed methodology, but further research is needed.

Suggested Citation

  • Karol Bandurski & Andrzej Górka & Halina Koczyk, 2023. "Radiators Adjustment in Multi-Family Residential Buildings—An Analysis Based on Data from Heat Meters," Energies, MDPI, vol. 16(22), pages 1-22, November.
  • Handle: RePEc:gam:jeners:v:16:y:2023:i:22:p:7485-:d:1276035
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/16/22/7485/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1996-1073/16/22/7485/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Kelly, Scott & Shipworth, Michelle & Shipworth, David & Gentry, Michael & Wright, Andrew & Pollitt, Michael & Crawford-Brown, Doug & Lomas, Kevin, 2013. "Predicting the diversity of internal temperatures from the English residential sector using panel methods," Applied Energy, Elsevier, vol. 102(C), pages 601-621.
    2. Peeters, Leen & Dear, Richard de & Hensen, Jan & D'haeseleer, William, 2009. "Thermal comfort in residential buildings: Comfort values and scales for building energy simulation," Applied Energy, Elsevier, vol. 86(5), pages 772-780, May.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Yang, Liu & Yan, Haiyan & Lam, Joseph C., 2014. "Thermal comfort and building energy consumption implications – A review," Applied Energy, Elsevier, vol. 115(C), pages 164-173.
    2. McKenna, R. & Hofmann, L. & Merkel, E. & Fichtner, W. & Strachan, N., 2016. "Analysing socioeconomic diversity and scaling effects on residential electricity load profiles in the context of low carbon technology uptake," Energy Policy, Elsevier, vol. 97(C), pages 13-26.
    3. Taleghani, Mohammad & Tenpierik, Martin & Kurvers, Stanley & van den Dobbelsteen, Andy, 2013. "A review into thermal comfort in buildings," Renewable and Sustainable Energy Reviews, Elsevier, vol. 26(C), pages 201-215.
    4. Eyre, Nick & Baruah, Pranab, 2015. "Uncertainties in future energy demand in UK residential heating," Energy Policy, Elsevier, vol. 87(C), pages 641-653.
    5. Lü, Xiaoshu & Lu, Tao & Kibert, Charles J. & Viljanen, Martti, 2015. "Modeling and forecasting energy consumption for heterogeneous buildings using a physical–statistical approach," Applied Energy, Elsevier, vol. 144(C), pages 261-275.
    6. Enescu, Diana, 2017. "A review of thermal comfort models and indicators for indoor environments," Renewable and Sustainable Energy Reviews, Elsevier, vol. 79(C), pages 1353-1379.
    7. Wang, Zhe & Hong, Tianzhen, 2020. "Learning occupants’ indoor comfort temperature through a Bayesian inference approach for office buildings in United States," Renewable and Sustainable Energy Reviews, Elsevier, vol. 119(C).
    8. Wang, Zhu & Wang, Lingfeng & Dounis, Anastasios I. & Yang, Rui, 2012. "Multi-agent control system with information fusion based comfort model for smart buildings," Applied Energy, Elsevier, vol. 99(C), pages 247-254.
    9. Rama Curiel, José Adrián & Thakur, Jagruti, 2022. "A novel approach for Direct Load Control of residential air conditioners for Demand Side Management in developing regions," Energy, Elsevier, vol. 258(C).
    10. Jin Wei & Fangsi Yu & Haixiu Liang & Maohui Luo, 2020. "Thermal Performance of Vertical Courtyard System in Office Buildings Under Typical Hot Days in Hot-Humid Climate Area: A Case Study," Sustainability, MDPI, vol. 12(7), pages 1-14, March.
    11. Arteconi, Alessia & Patteeuw, Dieter & Bruninx, Kenneth & Delarue, Erik & D’haeseleer, William & Helsen, Lieve, 2016. "Active demand response with electric heating systems: Impact of market penetration," Applied Energy, Elsevier, vol. 177(C), pages 636-648.
    12. Filippín, C. & Flores Larsen, S., 2012. "Summer thermal behaviour of compact single family housing in a temperate climate in Argentina," Renewable and Sustainable Energy Reviews, Elsevier, vol. 16(5), pages 3439-3455.
    13. Roberto Robledo-Fava & Mónica C. Hernández-Luna & Pedro Fernández-de-Córdoba & Humberto Michinel & Sonia Zaragoza & A Castillo-Guzman & Romeo Selvas-Aguilar, 2019. "Analysis of the Influence Subjective Human Parameters in the Calculation of Thermal Comfort and Energy Consumption of Buildings," Energies, MDPI, vol. 12(8), pages 1-23, April.
    14. Lu, Heli & Liu, Guifang, 2014. "Spatial effects of carbon dioxide emissions from residential energy consumption: A county-level study using enhanced nocturnal lighting," Applied Energy, Elsevier, vol. 131(C), pages 297-306.
    15. Ardeshir Mahdavi & Christiane Berger & Hadeer Amin & Eleni Ampatzi & Rune Korsholm Andersen & Elie Azar & Verena M. Barthelmes & Matteo Favero & Jakob Hahn & Dolaana Khovalyg & Henrik N. Knudsen & Ale, 2021. "The Role of Occupants in Buildings’ Energy Performance Gap: Myth or Reality?," Sustainability, MDPI, vol. 13(6), pages 1-44, March.
    16. Wang, Shaojian & Fang, Chuanglin & Guan, Xingliang & Pang, Bo & Ma, Haitao, 2014. "Urbanisation, energy consumption, and carbon dioxide emissions in China: A panel data analysis of China’s provinces," Applied Energy, Elsevier, vol. 136(C), pages 738-749.
    17. Masoud Esfandiari & Suzaini Mohamed Zaid & Muhammad Azzam Ismail & Mohammad Reza Hafezi & Iman Asadi & Saleh Mohammadi, 2021. "A Field Study on Thermal Comfort and Cooling Load Demand Optimization in a Tropical Climate," Sustainability, MDPI, vol. 13(22), pages 1-25, November.
    18. Dodds, Paul E., 2014. "Integrating housing stock and energy system models as a strategy to improve heat decarbonisation assessments," Applied Energy, Elsevier, vol. 132(C), pages 358-369.
    19. Andersen, Kristoffer Steen & Wiese, Catharina & Petrovic, Stefan & McKenna, Russell, 2020. "Exploring the role of households’ hurdle rates and demand elasticities in meeting Danish energy-savings target," Energy Policy, Elsevier, vol. 146(C).
    20. Zhang, Sheng & Cheng, Yong & Fang, Zhaosong & Huan, Chao & Lin, Zhang, 2017. "Optimization of room air temperature in stratum-ventilated rooms for both thermal comfort and energy saving," Applied Energy, Elsevier, vol. 204(C), pages 420-431.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jeners:v:16:y:2023:i:22:p:7485-:d:1276035. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.