Analysis of energy intensity trend as a tool for long-term forecasting of energy consumption

被引:0
|
作者
Leontiy Eder
Irina Provornaya
机构
[1] Novosibirsk State University,Institute of petroleum Geology and Geophysics of the Siberian branch of the Russian Academy of Sciences
[2] Economics Department,Institute of Petroleum Geology and Geophysics of the Siberian branch of the Russian Academy of Sciences
[3] Novosibirsk State University,undefined
来源
Energy Efficiency | 2018年 / 11卷
关键词
Energy intensity; Forecasting; Macro-regions; Convergence; Industrially developed countries; Developing countries;
D O I
暂无
中图分类号
学科分类号
摘要
The paper presents retrospective developments of energy intensity of the world economy differentiated by regions and their levels of economic development. The analysis has revealed the persistent decreasing trend in energy intensity across all the macro-regions and most countries, showing diversity of its course regarding both the starting point and rate of energy intensity reduction. Based on the time series, it has been shown that energy intensity of an economy is best described by an exponential trend, indicating a fairly uniform decline in energy efficiency in the economies. A power index of the exponential equation is one of the critical parameters characterizing reduction rate of energy intensity—the index of energy intensity reduction (IEIR). The authors have proposed an approach to measuring beta-convergence in time series of energy intensity, substantiating thereby convergence of economies. A comprehensive analysis of the time series and trend model served as a basis for prediction of variation in energy intensity of economies of the macro-regions for the period until 2040, which also included its quality and rationale verification. It has been shown that the trend method can be successfully applied to forecasting energy intensity developments to economically developed regions, whereas for developing countries such a forecast is less reliable. In these conditions, a comprehensive use of the trend model and the convergence model is necessary. The forecast of changes in energy intensity of the world economies grouped into macro-regions until 2040 has shown that the economically developed countries of Europe will remain to be the energy efficiency leaders until the mid-twenty-first century. The energy intensity indicators for less developed regions will gradually converge in their domain; yet, they are not expected to reach the level of the economically developed countries by 2040.
引用
收藏
页码:1971 / 1997
页数:26
相关论文
共 50 条
  • [1] Analysis of energy intensity trend as a tool for long-term forecasting of energy consumption
    Eder, Leontiy
    Provornaya, Irina
    ENERGY EFFICIENCY, 2018, 11 (08) : 1971 - 1997
  • [2] Sustainable development of the world energy taking into account dynamic of energy intensity: current trends and long-term forecast
    Eder, L., V
    Provornaya, I., V
    Filimonova, I., V
    5TH INTERNATIONAL CONFERENCE ON ENERGY AND ENVIRONMENT RESEARCH (ICEER 2018), 2018, 153 : 174 - 179
  • [3] Long-Term Energy Demand Forecasting Based on a Systems Analysis
    Filippov, S. P.
    Malakhov, V. A.
    Veselov, F. V.
    THERMAL ENGINEERING, 2021, 68 (12) : 881 - 894
  • [4] Long-Term Energy Demand Forecasting Based on a Systems Analysis
    S. P. Filippov
    V. A. Malakhov
    F. V. Veselov
    Thermal Engineering, 2021, 68 : 881 - 894
  • [5] Long-term electric energy consumption forecasting via artificial cooperative search algorithm
    Kaboli, S. Hr. Aghay
    Selvaraj, J.
    Rahim, N. A.
    ENERGY, 2016, 115 : 857 - 871
  • [6] The Role of Energy Quality in Shaping Long-Term Energy Intensity in Europe
    Gentvilaite, Ruta
    Kander, Astrid
    Warde, Paul
    ENERGIES, 2015, 8 (01): : 133 - 153
  • [7] Long-term energy demand forecasting and planning in Taiwan
    Bor, YJ
    Liu, SM
    Jan, HK
    Chou, FY
    ENERGY AND ECONOMIC GROWTH: IS SUSTAINABLE GROWTH POSSIBLE?, VOLS 1-3, 1997, : 305 - 315
  • [8] General Equilibrium Analysis of Mid-long Term Energy Intensity Changing Trend in China
    Li Aijun
    RECENT ADVANCE IN STATISTICS APPLICATION AND RELATED AREAS, PTS 1 AND 2, 2008, : 1222 - 1226
  • [9] Long-term electrical energy consumption formulating and forecasting via optimized gene expression programming
    Kaboli, S. Hr Aghay
    Fallahpour, A.
    Selvaraj, J.
    Rahim, N. A.
    ENERGY, 2017, 126 : 144 - 164
  • [10] US long-term energy intensity: Backcast and projection
    Dowlatabadi, Hadi
    Oravetz, Matthew A.
    ENERGY POLICY, 2006, 34 (17) : 3245 - 3256