Development of a Space Heating Model Suitable for the Automated Model Generation of Existing Multifamily BuildingsA Case Study in Nordic Climate

被引:23
作者
Lundstrom, Lukas [1 ,2 ]
Akander, Jan [3 ]
Zambrano, Jesus [1 ]
机构
[1] Malardalen Univ, Sch Business Soc & Engn, S-72123 Vasteras, Sweden
[2] Eskilstuna Kommunfastighet AB, S-63005 Eskilstuna, Sweden
[3] Univ Gavle, Div Bldg Energy & Environm Technol, Dept Technol & Environm, S-80176 Gavle, Sweden
关键词
energy performance modeling; gray box; satellite-based solar radiation data; meteorological reanalysis data; ISO; 52016-1; ENERGY-CONSUMPTION; INFILTRATION; IMPACT; LIDAR;
D O I
10.3390/en12030485
中图分类号
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号
0807 ; 0820 ;
摘要
Building energy performance modeling is essential for energy planning, management, and efficiency. This paper presents a space heating model suitable for auto-generating baseline models of existing multifamily buildings. Required data and parameter input are kept within such a level of detail that baseline models can be auto-generated from, and calibrated by, publicly accessible data sources. The proposed modeling framework consists of a thermal network, a typical hydronic radiator heating system, a simulation procedure, and data handling procedures. The thermal network is a lumped and simplified version of the ISO 52016-1:2017 standard. The data handling consists of procedures to acquire and make use of satellite-based solar radiation data, meteorological reanalysis data (air temperature, ground temperature, wind, albedo, and thermal radiation), and pre-processing procedures of boundary conditions to account for impact from shading objects, window blinds, wind- and stack-driven air leakage, and variable exterior surface heat transfer coefficients. The proposed model was compared with simulations conducted with the detailed building energy simulation software IDA ICE. The results show that the proposed model is able to accurately reproduce hourly energy use for space heating, indoor temperature, and operative temperature patterns obtained from the IDA ICE simulations. Thus, the proposed model can be expected to be able to model space heating, provided by hydronic heating systems, of existing buildings to a similar degree of confidence as established simulation software. Compared to IDA ICE, the developed model required one-thousandth of computation time for a full-year simulation of building model consisting of a single thermal zone. The fast computation time enables the use of the developed model for computation time sensitive applications, such as Monte-Carlo-based calibration methods.
引用
收藏
页数:27
相关论文
共 41 条
  • [1] Akander J., 2000, THESIS
  • [2] A review of data-driven building energy consumption prediction studies
    Amasyali, Kadir
    El-Gohary, Nora M.
    [J]. RENEWABLE & SUSTAINABLE ENERGY REVIEWS, 2018, 81 : 1192 - 1205
  • [3] [Anonymous], 2017, ASHRAE HDB FUND SI E
  • [4] [Anonymous], 2010, TECHNICAL REPORT
  • [5] [Anonymous], 2008, 137902008 ISO
  • [6] Identifying suitable models for the heat dynamics of buildings
    Bacher, Peder
    Madsen, Henrik
    [J]. ENERGY AND BUILDINGS, 2011, 43 (07) : 1511 - 1522
  • [7] Intelligent Systems for Building Energy and Occupant Comfort Optimization: A State of the Art Review and Recommendations
    Boodi, Abhinandana
    Beddiar, Karim
    Benamour, Malek
    Amirat, Yassine
    Benbouzid, Mohamed
    [J]. ENERGIES, 2018, 11 (10)
  • [8] Stan: A Probabilistic Programming Language
    Carpenter, Bob
    Gelman, Andrew
    Hoffman, Matthew D.
    Lee, Daniel
    Goodrich, Ben
    Betancourt, Michael
    Brubaker, Marcus A.
    Guo, Jiqiang
    Li, Peter
    Riddell, Allen
    [J]. JOURNAL OF STATISTICAL SOFTWARE, 2017, 76 (01): : 1 - 29
  • [9] Influence of Input Climatic Data on Simulations of Annual Energy Needs of a Building: EnergyPlus and WRF Modeling for a Case Study in Rome (Italy)
    Ciancio, Virgilio
    Falasca, Serena
    Golasi, Iacopo
    Curci, Gabriele
    Coppi, Massimo
    Salata, Ferdinando
    [J]. ENERGIES, 2018, 11 (10)
  • [10] Clarke J.A., 1985, Energy simulation in building design