0
  • DE
  • EN
  • FR
  • Internationale Datenbank und Galerie für Ingenieurbauwerke

Anzeige

Sensitivity Analysis of Factors Influencing Rural Housing Energy Consumption in Different Household Patterns in the Zhejiang Province

Autor(en): ORCID






ORCID
Medium: Fachartikel
Sprache(n): Englisch
Veröffentlicht in: Buildings, , n. 2, v. 13
Seite(n): 463
DOI: 10.3390/buildings13020463
Abstrakt:

Unlike urban dwellings, it is very common for elderly people to stay at home alone in Chinese rural families, and some families have three generations in the same house who are in different situations, and their different family patterns lead to different highly sensitive parameters of building energy consumption. This paper first selects the three most common family patterns based on a questionnaire survey. The measured energy consumption behavior and electrical parameters, energy consumption time, and basic building parameters were input into DesignBuilder to build three building simulation models, and these were verified by comparing the predicted and measured values of the residential month-by-month electricity consumption. The global sensitivity analysis was then conducted using DesignBuilder software to determine the interactions between the variables by using the second-order Sobol index for cooling load, heating load, and comfort of the models to obtain standardized regression coefficients (SRC) for each factor to determine the most sensitive parameters. The results show that the different household patterns had little influence on the ranking of highly sensitive factors for heating and cooling, but annual electricity consumption and discomfort in different household patterns had a significant influence on the ranking of highly sensitive factors. For example, model 1 showed the most sensitivity to general lighting power density when optimizing the total amount of electricity was the goal, while the one that had the greatest degree of influence on the total amount of electricity in model 2 and model 3 was equipment power density.

Copyright: © 2023 by the authors; licensee MDPI, Basel, Switzerland.
Lizenz:

Dieses Werk wurde unter der Creative-Commons-Lizenz Namensnennung 4.0 International (CC-BY 4.0) veröffentlicht und darf unter den Lizenzbedinungen vervielfältigt, verbreitet, öffentlich zugänglich gemacht, sowie abgewandelt und bearbeitet werden. Dabei muss der Urheber bzw. Rechteinhaber genannt und die Lizenzbedingungen eingehalten werden.

Geografische Orte

  • Über diese
    Datenseite
  • Reference-ID
    10712642
  • Veröffentlicht am:
    21.03.2023
  • Geändert am:
    10.05.2023
 
Structurae kooperiert mit
International Association for Bridge and Structural Engineering (IABSE)
e-mosty Magazine
e-BrIM Magazine