Source Journal of Chinese Scientific and Technical Papers
Included as T2 Level in the High-Quality Science and Technology Journals in the Field of Architectural Science
Core Journal of RCCSE
Included in the CAS Content Collection
Included in the JST China
Indexed in World Journal Clout Index (WJCI) Report
FANG Tao, LIU Ruijie, WANG Yanzheng, ZOU Ran. Comprehensive Optimization and Empirical Verification of Office Building Design Parameters in Cold Regions Based on Nearly Zero Energy Consumption Targets[J]. INDUSTRIAL CONSTRUCTION, 2023, 53(7): 16-24,78. doi: 10.13204/j.gyjzG22120509
Citation: FANG Tao, LIU Ruijie, WANG Yanzheng, ZOU Ran. Comprehensive Optimization and Empirical Verification of Office Building Design Parameters in Cold Regions Based on Nearly Zero Energy Consumption Targets[J]. INDUSTRIAL CONSTRUCTION, 2023, 53(7): 16-24,78. doi: 10.13204/j.gyjzG22120509

Comprehensive Optimization and Empirical Verification of Office Building Design Parameters in Cold Regions Based on Nearly Zero Energy Consumption Targets

doi: 10.13204/j.gyjzG22120509
  • Received Date: 2022-12-05
  • At present, the nearly zero energy consumption building is showing the trend of scale promotion in China, and the design and evaluation standards from the national to the local have been gradually improving, and most of the standards limit the value of energy-saving design parameters to achieve the goal of near-zero energy consumption. However, office buildings have diverse demands for energy consumption and complex structure of energy consumption, so it is necessary to comprehensively optimize the energy-saving design parameters to achieve the design goal of energy consumption minimization. Based on this, the paper firstly constructed the base model of energy consumption composition and building information for the office buildings in cold regions through investigation, and constructed a parameterized integrated platform with model construction, energy consumption simulation and automatic optimization through grasshopper; secondly, a comparative study of office buildings with different thermal design parameters of building envelopes was conducted, and the importance of lighting energy consumption and the influence law of total energy consumption by multi-parameter interaction with this platform was determined; then, on this basis, the paper optimized the energy consumption-oriented design parameters by genetic algorithm, and the optimal results were obtained; thirdly, with the Comprehensive Lab Building of Shandong Jianzhu University as an example, the paper verified the reliability and accuracy of the research results by comparing the measured data with the simulation data; finally, a correlation analysis of design parameters and energy consumption results was conducted by data statistics software, and a machine learning model was established by training data sets in MATLAB, thus verifying the accuracy of the model.
  • [1]
    中国建筑节能协会.2019中国建筑能耗研究报告[J].建筑,2020(7):30-39.
    [2]
    China Association of Building Energy Effectiency. China building energy consumption research report 2020[EB/OL].2022-01-20[2022-12-05]. https://www.cabee.org/site/content/23568.html, 2020.
    [3]
    MACHAIRAS V, TSANGRASSOULIS A, AXARLI K. Algorithms for optimization of building design:a review[J]. Renewable and Sustainable Energy Reviews,2014,31:101-112.
    [4]
    KHEIRI F. A review on optimization methods applied in energy-efficient building geometry and envelope design[J]. Renewable and Sustainable Energy Reviews, 2018, 92(9):897-920.
    [5]
    SAHU M, BHATTACHARJEE B, KAUSHIK S C.Thermal design of air-conditioned building for tropical climate using admittance method and genetic algorithm[J]. Energy and Buildings, 2012, 53(1):1-6.
    [6]
    刘可,徐小东,王伟.以节能为导向的住区形态布局及自动寻优方法研究[J].工业建筑,2021,51(8):1-10

    ,27.
    [7]
    FAN C, CHEN M, TANG R, et al. A novel deep generative modeling-based data augmentation strategy for improving short-term building energy predictions[C]//Building Simulation. Tsinghua University Press, 2022, 15:197-211.
    [8]
    FENG G, DOU B, XU X, et al. Research on energy efficiency design key parameters of envelope for nearly zero energy buildings in cold area[J]. Procedia Engineering, 2017,205:686-693.
    [9]
    LI H, WANG S,CHEUNG H. Sensitivity analysis of design parameters and optimal design for zero/low energy buildings in subtropical regions[J]. Applied Energy, 2018,228:1280-1291.
    [10]
    WANG Y, WEI C. Design optimization of office building envelope based on quantum genetic algorithm for energy conservation[J/OL]. Journal of Building Engineering, 2020,35[2022-12-05]. https://doi.org/10.1016/j.jobe.2020.102048.
    [11]
    YAN H, YAN K, JI G. Optimization and prediction in the early design stage of office buildings using genetic and XGBoost algorithms[J/OL]. Building and Environment, 2022(6):218[2022-12-05].https://doi.org/10.1016/j.buildenv.2022.109081.
    [12]
    KURNITSKI J, PIKAS E, THALFELDT M. Cost optimal and nearly zero energy building solutions for office buildings[J]. Energy and Buildings, 2014, 74:30-42.
    [13]
    LU F, YU Z, ZOU Y, et al. Cooling system energy flexibility of a nearly zero-energy office building using building thermal mass:Potential evaluation and parametric analysis[J/OL]. Energy and Buildings, 2021, 236(3).[2022-12-05]. https://doi.org/10.1016/j.enbuild.2021.110763
    [14]
    XU X, FENG G, CHI D, et al. Optimization of Performance Parameter Design and Energy Use Prediction for Nearly Zero Energy Buildings[J/OL]. Energies, 2018, 11(12)[2022-12-05]. https://doi.org/10.3390/en11123252.
    [15]
    Wallacei. An analytic engine for evolutionary algorithms[EB/OL].[2022-12-05]. https://www.wallacei.com.
    [16]
    Design Builder Software Ltd.DesignBuilder v7.0.2.006[EB/OL].[2022-12-05].https://designbuilder.co.uk.
  • Relative Articles

    [1]CAO Dun, HAO Zhanguo, DING Yang, WEI Wei. Research on Energy-Saving Design of Office Building Forms in Cold C-Region Based on Daylighting and Thermal Performance[J]. INDUSTRIAL CONSTRUCTION, 2023, 53(6): 84-90,121. doi: 10.13204/j.gyjzG22122307
    [2]WU Di, ZHANG Hengyu, TANG Li, LYU Hongyi, FU Mengze. Research on Thermal Environment Evaluation of a Traditional Brick-Timber House in Daokou Town of the Northern Henan in Winter[J]. INDUSTRIAL CONSTRUCTION, 2022, 52(3): 85-91. doi: 10.13204/j.gyjzG22010416
    [3]LI Jinyang, HUANG Yong, ZHANG Longwei, ZHANG Minyi. CLIMATE ADAPTABILITY OPTIMIZATION OF LARGE SPACE BUILDING FORM IN COLD AREA: TAKE LIAODONG BAY CRUISE TERMINAL PASSENGER TRANSPORT CENTER AS AN EXAMPLE[J]. INDUSTRIAL CONSTRUCTION, 2021, 51(4): 6-11. doi: 10.13204/j.gyjzG20030609
    [4]WU Di, ZHANG Xinwei, FU Mengze. RESEARCH ON TARGET VALUE OF AUXILIARY ENERGY CONSUMPTION IN PASSIVE ULTRA-LOW ENERGY CONSUMPTION BUILDING DESIGN IN COLD ZONE[J]. INDUSTRIAL CONSTRUCTION, 2021, 51(10): 81-86. doi: 10.13204/j.gyjzG21060909
    [5]HOU Wei, WANG Xuhong, YANG Qiuyu, LYU Tao, LI Yuxi, LYU Min, YIN Yue. DESIGN REQUIREMENTS OF BUFFER MATERIALS FOR GEOLOGICAL DISPOSAL REPOSITORIES OF HIGH-LEVEL RADIOACTIVE WASTES IN CHINA[J]. INDUSTRIAL CONSTRUCTION, 2020, 50(9): 8-11. doi: 10.13204/j.gyjzG20063013
    [6]ZHANG Fangfang, ZHANG Qun, WANG Jiangli. VENTILATION OPTIMIZATION STRATEGY AND EFFICIENCY OF RURAL DWELLINGS IN LUOYANG[J]. INDUSTRIAL CONSTRUCTION, 2020, 50(7): 34-40. doi: 10.13204/j.gyjzG19113002
    [11]Liu Qibo, Zhou Ruoqi. RESEARCH OF ENERGY EFFICIENCY TECHNOLOGY SYSTEM OF UNIVERSITY EXISTING BUILDING IN COLD CLIMATE ZONE[J]. INDUSTRIAL CONSTRUCTION, 2013, 43(4): 49-53. doi: 10.13204/j.gyjz201304010
    [12]Yang Zijiang. ENERGY-SAVING DESIGN OF TEACHING BUILDINGS OF HOT IN SUMMER AND COLD IN WINTER REGIONS[J]. INDUSTRIAL CONSTRUCTION, 2013, 43(4): 165-167. doi: 10.13204/j.gyjz201304034
    [13]Shu Xin, Ji Xiang. STUDY ON ENERGY- EFFICIENT OF RESIDENTIAL BUILDINGS IN COLD REGIONS OF JIANGSU PROVINCE[J]. INDUSTRIAL CONSTRUCTION, 2012, 42(5): 67-70,164. doi: 10.13204/j.gyjz2011205011
    [14]Li Xueping. ENERGY CONSERVATION DESIGN OF HIGH - RISE OFFICE BUILDING[J]. INDUSTRIAL CONSTRUCTION, 2010, 40(12): 13-15. doi: 10.13204/j.gyjz201012004
    [15]Li Yingmin, Zheng Nina, Zhao Jing, Li Yanmin, Xiao Hongwei. THE FACTORS INFLUENCING RELIABILITY OF POLE AND TOWER STRUCTURES[J]. INDUSTRIAL CONSTRUCTION, 2010, 40(7): 47-51. doi: 10.13204/j.gyjz201007013
    [16]Zhou Dongliang, Chi Xiaoyan. AN INITIAL STUDY ON DESIGN OF INNER PUBLIC SPACE OF OFFICIAL BUILDINGS[J]. INDUSTRIAL CONSTRUCTION, 2009, 39(3): 23-25. doi: 10.13204/j.gyjz200903008
    [17]Liu Qiang, Zhou Ruizhong, Zou Zujun. DESIGN OF REDUCING SEISMIC RESPONSE OF MULTI-STOREY BUILDING BY TAKING ITS THERMAL-INSULATING ROOF AS TMD[J]. INDUSTRIAL CONSTRUCTION, 2008, 38(7): 11-15. doi: 10.13204/j.gyjz200807003
    [18]Dong Hairong, Qi Shaoming, Jiang Guaini, Li Chunju. ENERGY_SAVING MEASURES OF SUBURBAN HOUSES IN THE COLD DISTRICT[J]. INDUSTRIAL CONSTRUCTION, 2007, 37(3): 30-32,22. doi: 10.13204/j.gyjz200703009
    [19]Mao Yan, Liu Jiaping. ANALYSIS OF ENERGY EFFICIENCY OF HOME WINDOWS IN COLD REGIONS[J]. INDUSTRIAL CONSTRUCTION, 2006, 36(1): 11-13. doi: 10.13204/j.gyjz200601004
  • Cited by

    Periodical cited type(4)

    1. 鲁晓玲. 近零能耗办公建筑设计策略与实践研究. 建材发展导向. 2024(07): 50-52 .
    2. 黄帆,李小华,曾智,陈歆儒,张哲. 湘潭市公共办公建筑能源审计及能耗计算模型研究. 湖南工程学院学报(自然科学版). 2024(02): 83-89 .
    3. 周正航. 基于遗传算法的建筑节能集成优化设计初探. 中国高新科技. 2024(15): 155-157 .
    4. 郝莹莹,韩姝娴,宋业辉,赵凯佳,陈易玄,钱程. 蚌埠市超低能耗建筑实现路径研究. 建设科技. 2024(23): 69-72 .

    Other cited types(2)

  • Created with Highcharts 5.0.7Amount of accessChart context menuAbstract Views, HTML Views, PDF Downloads StatisticsAbstract ViewsHTML ViewsPDF Downloads2024-042024-052024-062024-072024-082024-092024-102024-112024-122025-012025-022025-0305101520
    Created with Highcharts 5.0.7Chart context menuAccess Class DistributionFULLTEXT: 10.1 %FULLTEXT: 10.1 %META: 86.8 %META: 86.8 %PDF: 3.2 %PDF: 3.2 %FULLTEXTMETAPDF
    Created with Highcharts 5.0.7Chart context menuAccess Area Distribution其他: 9.5 %其他: 9.5 %上海: 4.8 %上海: 4.8 %东莞: 2.1 %东莞: 2.1 %六安: 1.6 %六安: 1.6 %北京: 2.6 %北京: 2.6 %十堰: 0.5 %十堰: 0.5 %台州: 1.6 %台州: 1.6 %哈尔滨: 0.5 %哈尔滨: 0.5 %嘉兴: 0.5 %嘉兴: 0.5 %大连: 2.1 %大连: 2.1 %天津: 3.2 %天津: 3.2 %宣城: 0.5 %宣城: 0.5 %常州: 0.5 %常州: 0.5 %常德: 1.6 %常德: 1.6 %张家口: 3.2 %张家口: 3.2 %成都: 0.5 %成都: 0.5 %新乡: 0.5 %新乡: 0.5 %无锡: 1.1 %无锡: 1.1 %晋城: 0.5 %晋城: 0.5 %榆林: 0.5 %榆林: 0.5 %武汉: 1.1 %武汉: 1.1 %济南: 0.5 %济南: 0.5 %济宁: 0.5 %济宁: 0.5 %深圳: 0.5 %深圳: 0.5 %温州: 1.1 %温州: 1.1 %漯河: 1.1 %漯河: 1.1 %濮阳: 0.5 %濮阳: 0.5 %芒廷维尤: 25.9 %芒廷维尤: 25.9 %芝加哥: 1.6 %芝加哥: 1.6 %西宁: 17.5 %西宁: 17.5 %西安: 1.1 %西安: 1.1 %贵阳: 0.5 %贵阳: 0.5 %运城: 2.6 %运城: 2.6 %邯郸: 0.5 %邯郸: 0.5 %郑州: 1.6 %郑州: 1.6 %鄂尔多斯: 0.5 %鄂尔多斯: 0.5 %重庆: 1.1 %重庆: 1.1 %镇江: 0.5 %镇江: 0.5 %长沙: 1.1 %长沙: 1.1 %青岛: 1.6 %青岛: 1.6 %驻马店: 0.5 %驻马店: 0.5 %其他上海东莞六安北京十堰台州哈尔滨嘉兴大连天津宣城常州常德张家口成都新乡无锡晋城榆林武汉济南济宁深圳温州漯河濮阳芒廷维尤芝加哥西宁西安贵阳运城邯郸郑州鄂尔多斯重庆镇江长沙青岛驻马店

Catalog

    通讯作者: 陈斌, bchen63@163.com
    • 1. 

      沈阳化工大学材料科学与工程学院 沈阳 110142

    1. 本站搜索
    2. 百度学术搜索
    3. 万方数据库搜索
    4. CNKI搜索

    Article Metrics

    Article views (163) PDF downloads(6) Cited by(6)
    Proportional views
    Related

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return