DECOMPOSITION METHODOLOGY IN INDUSTRIAL ENERGY DEMAND ANALYSIS

被引:189
|
作者
ANG, BW
机构
[1] Department of Industrial and Systems Engineering, National University of Singapore, Singapore, 0511
关键词
D O I
10.1016/0360-5442(95)00068-R
中图分类号
O414.1 [热力学];
学科分类号
摘要
We discuss some methodological and application issues related to decomposing national industrial energy consumption into changes associated with aggregate industrial production level, production structure and sectoral energy intensity. Past studies are classified and reviewed with respect to study scope and decomposition technique. A framework for decomposition method formulation which incorporates three different approaches is presented. Several specific methods are described and their applications are illustrated with an example. Relevant application issues, such as method selection, periodwise vs time-series decomposition, significance of levels of sector disaggregation, and result interpretation are discussed.
引用
收藏
页码:1081 / 1095
页数:15
相关论文
共 50 条
  • [1] Determinants of electricity demand in the Chinese industrial sector: A decomposition analysis
    Wang, Wenchao
    Mu, Hailin
    Ning, Yadong
    Song, Yongchen
    EBM 2010: INTERNATIONAL CONFERENCE ON ENGINEERING AND BUSINESS MANAGEMENT, VOLS 1-8, 2010, : 3396 - 3399
  • [2] THE INDUSTRIAL DEMAND FOR ENERGY
    URI, ND
    RESOURCES AND ENERGY, 1982, 4 (01): : 27 - 57
  • [3] THE INDUSTRIAL DEMAND FOR ENERGY
    URI, ND
    SOCIO-ECONOMIC PLANNING SCIENCES, 1982, 16 (02) : 69 - 84
  • [4] Determinants of energy demand in the French service sector: A decomposition analysis
    Mairet, Nicolas
    Decellas, Fabrice
    ENERGY POLICY, 2009, 37 (07) : 2734 - 2744
  • [5] Industrial energy demand, a forecasting model based on an index decomposition of structural and efficiency effects
    Lescaroux, Francois
    OPEC ENERGY REVIEW, 2013, 37 (04) : 477 - 502
  • [6] Decomposition analysis of renewable energy demand and coupling effect between renewable energy and energy demand: Evidence from China
    Zhang, Xiaoyi
    Zhang, Rui
    Feng, Cuiyang
    Wang, Yue
    Zhao, Meilin
    Zhao, Xin
    RENEWABLE ENERGY, 2024, 237
  • [8] Hierarchical prediction of industrial water demand based on refined Laspeyres decomposition analysis
    Shang, Yizi
    Lu, Shibao
    Gong, Jiaguo
    Shang, Ling
    Li, Xiaofei
    Wei, Yongping
    Shi, Hongwang
    WATER SCIENCE AND TECHNOLOGY, 2017, 76 (11) : 2876 - 2887
  • [9] Active Demand Energy Services Decomposition
    Antolic, Mladen
    Fazo, Boris
    Nikolovski, Srete
    Baus, Zoran
    2018 INTERNATIONAL CONFERENCE ON SMART SYSTEMS AND TECHNOLOGIES (SST), 2018, : 199 - 203
  • [10] Energy demand flexibilization of industrial consumers
    Dunkelberg, Heiko
    Heidrich, Tobias
    Weiss, Tim
    Hesselbach, Jens
    JOURNAL OF SIMULATION, 2020, 14 (01) : 53 - 63