Estimating India's commercial building stock to address the energy data challenge

被引:12
|
作者
Kumar, Satish [1 ]
Yadav, Neha [1 ]
Singh, Mohini [1 ]
Kachhawa, Sandeep [1 ]
机构
[1] Alliance Energy Efficient Econ, Delhi, India
来源
BUILDING RESEARCH AND INFORMATION | 2019年 / 47卷 / 01期
关键词
big data; building stock; commercial buildings; energy data; energy intensity; floor area; India;
D O I
10.1080/09613218.2018.1515304
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
Estimating the commercial building stock in terms of energy and area usage can be a tricky exercise in the absence of reliable and structured data. While the benefits of such an exercise are widely understood in some countries, no standard framework works in all countries due to the differences in workforce capacity and resources, national priorities, and energy data and analytics maturity of various countries. Hence, this paper documents an energy-accounting exercise that first collects commercial building sector data in India from multiple sources. An approach is then proposed that first divides the commercial building sector into categories and subcategories and then estimates the floor area (1.1 billion m(2)) and energy intensity (69 kWh/m(2)) of the entire commercial stock in 2017. Based on macro-economic parameters, the floor area (1.78 billion m(2)) and energy intensity (81 kWh/m(2)) are projected for 2027 in a business-as-usual scenario. This research sends a clear signal to other researchers and policy-makers in the central and state government about the need and potential to refine and adopt more rigorous data-collection and analytical methods by institutionalizing the process and advancing data-driven policies and evaluation in future.
引用
收藏
页码:24 / 37
页数:14
相关论文
共 50 条
  • [41] Data collection and analysis of the building stock and its energy performance-An example for Hellenic buildings
    Dascalaki, Elena G.
    Droutsa, Kaliopi
    Gaglia, Athina G.
    Kontoyiannidis, Simon
    Balaras, Constantinos A.
    ENERGY AND BUILDINGS, 2010, 42 (08) : 1231 - 1237
  • [42] Assessing and monitoring the energy consumption of a large building stock by the means of a dynamic data-base
    Beccali, M
    Caponio, R
    Ferrari, S
    Schultze, G
    REBUILD - THE EUROPEAN CITIES OF TOMORROW: SHAPING OUR EUROPEAN CITIES FOR THE 21ST CENTURY, 1998, : 220 - 223
  • [43] COMBINING GIS DATA SETS AND MATERIAL INTENSITIES TO ESTIMATE VIENNA'S BUILDING STOCK
    Kleemann, F.
    Lederer, J.
    Rechberger, H.
    Fellner, J.
    EXPANDING BOUNDARIES: SYSTEMS THINKING IN THE BUILT ENVIRONMENT, 2016, : 274 - 278
  • [44] ZERO-ENERGY OR ZERO-ARCHITECTURE BUILDING? DESIGNING ASPECTS IN CONTEXT OF BUILDING'S COMMERCIAL SUCCESS
    Zalewski, Krzysztof
    Gil, Adam
    ARTS, PERFORMING ARTS, ARCHITECTURE AND DESIGN, 2014, : 1167 - 1174
  • [45] Unveiling renovation patterns in the French building stock using archetype classification and energy performance certificates data
    Araujo, Lorena de Carvalho
    Bonhomme, Marion
    Faraut, Serge
    Tornay, Nathalie
    ENERGY AND BUILDINGS, 2025, 336
  • [46] Assessing the energy performance certification effectiveness for the Spanish building stock in response to recent climate change data
    Sarabia-Escriva, Emilio-Jose
    Jimenez-Navarro, Juan-Pablo
    Soto-Frances, Victor-Manuel
    Pinazo-Ojer, Jose-Manuel
    ENERGY AND BUILDINGS, 2024, 323
  • [47] Developing a Data-driven school building stock energy and indoor environmental quality modelling method
    Schwartz, Y.
    Godoy-Shimizu, D.
    Korolija, I
    Dong, J.
    Hong, S. M.
    Mavrogianni, A.
    Mumovic, D.
    ENERGY AND BUILDINGS, 2021, 249
  • [48] The challenge of healthcare big data to China’s commercial health insurance industry: evaluation and recommendations
    Jun Wu
    Jiajun Qiao
    Stephen Nicholas
    Yunqiao Liu
    Elizabeth Maitland
    BMC Health Services Research, 22
  • [49] The challenge of healthcare big data to China's commercial health insurance industry: evaluation and recommendations
    Wu, Jun
    Qiao, Jiajun
    Nicholas, Stephen
    Liu, Yunqiao
    Maitland, Elizabeth
    BMC HEALTH SERVICES RESEARCH, 2022, 22 (01)
  • [50] Estimating energy savings for the residential building stock of an entire city: A GIS-based statistical downscaling approach applied to Rotterdam
    Mastrucci, Alessio
    Baume, Olivier
    Stazi, Francesca
    Leopold, Ulrich
    ENERGY AND BUILDINGS, 2014, 75 : 358 - 367