Analysis of China s Energy Intensity and Its Forecast

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1 ISSN (print, (online International Journal of Nonlinear Science Vol.9(2010 No.3,pp Analysis of China s Energy Intensity and Its Forecast Beibei Zhang, Lixin Tian Nonlinear Scientific Research Center, Jiangsu University Zhenjiang, Jiangsu, , P.R. China (Received 7 January 2010, accepted 9 April 2010 Abstract:This paper which used the method of nonlinear dynamic systems gives a new model of energy intensity, parameters in the model were estimated by the estimation method for statistical test, and China s energy intensity was predicted. The development trend of the energy efficiency was analyzed by the data of China Statistical Yearbook 2008 and China Energy Statistical Yearbook 2008.The related measures are also proposed. Keywords: energy intensity model; statistical test; forecast; energy resource measures 1 Introduction The integrated energy efficiency indicator in a country or region can be shown by energy consumption of per unit GDP, i.e. the energy intensity. The State Council Development Research Center estimates that, during the period before 2020, energy saving potentials are about 250 million tons of standard coal, equivalent to 25% to 54% of increasing energy consumption forecasted by industrial sector in the same period. Although China has increased the energy efficiency in the industrial sector, there are still large gaps in industrial efficiency between international standards. With the rapid development of domestic and international economyenergy constraint and environmental constraint are increasingly becoming an important bottleneck for sustainable development, which makes governments and business pay more and more concern on improving energy consumption efficiency. In China today the main economic development model of energy is still based on coal, oil and natural gas and other fossil fuel. Among the primary energy consumption, the proportion of coal is generally 2/3. This typical carbon-based energy economy induces the high-carbon feature and high intensity of co 2 emission, and a serious situation of energy saving and emission reduction. In recent years, high-carbon economic growth model in China based on burning coal has also caused serious environmental problems. Because of pollution, the country s annual economic losses reach thousands of billion Yuan RMB. With the development of society and the improvement of people s living standards, shortage of low-carbon energy sources facing in China will become more severe, while the essence of low-carbon economy is to improve the energy efficiency and to optimize the energy structure [1]. In the eve of Climate Change Conference in Copenhagen, in the UN summit President Hu Jintao pledged that China will reduce carbon emissions intensity of per unit of GDP notably in China wants to transform the economic growth mode and to adjust the economic structure. The transition to low-carbon economy has became urgent. There are a lot of researches on the trends of energy intensity change overseas. Ian Sue Wing [2] reconciles conflicting explanations for the decline in U.S. energy intensity over the last 40 years of the 20th century and shows that price-induced substitution of variable inputs generated transitory energy savings, while innovation induced by energy prices had only a minor impact. Na Liu, B.W. Ang [3] understand the mechanisms of change of energy consumption in industry has attracted much attention since the 1973 world oil crisis. A popular line of research has been to decompose changes in the aggregate energy intensity of industry to give the relative impacts arising from energy intensity change and product-mix change using a decomposition technique. Hengyun Ma, LesOxley, JohnGibson [4] use individual fuel price data and a two-stage approach to estimate total factor cost functions and fuel share equations. Energy intensity changes vary by region but the major drivers seem to be budget effect and the adoption of energy-intensive technologies, which might be embodied in high-level energy-using exports and sectors, capital investment and even old technique and equipment imports. Whether the trend in rising energy intensity continues will be significant for China and the rest of the world. Fernando Castellanos Corresponding author. address: zbb @126.com Copyright c World Academic Press, World Academic Union IJNS /353

2 B. B. Zhang, L. X. Tian: Analysis of China s Energy Intensity and Its Forecast 321 Silveria, Ralph A. Luken [5] estimate trends in global decoupling of energy use and manufacturing value added, compare energy-use intensity in six country groups. The comparison of energy intensities across country groups and among countries suggests that there still remains significant potential to reduce energy use and associated co 2 emissions. The analysis of four sub-sectors in developing and transition economies also shows similar but varied potential for reducing energy use and associated co 2 emissions. In China, analysis on the determining factors of energy intensity is comparatively mature. However, fewer researchers study the trends of energy intensity change. Applling the input-output method and scenario analysis, Qiaomei Liang, Yi-Ming Wei et al [6] introduced the basic principles for energy demand and energy intensity prediction. Zhiyong Han, Yi-Ming Wei and Fan Ying [7] analyzed the trends of energy intensity change in China and they pointed out these trends are consistent and reasonable. Dong Li[8] empirically analyzed the relationship between China energy intensity and per capita GDP, using the panel data of 30 provinces during Their results support the hypothesis of the existence of U shape relationship. Many experts and scholars made analyses of influencing factors on the trends of energy intensity change in China, which are decomposition analysis of structural effects and technical effects, using input-output and scenario analysis to predict, but few take into account the economic system itself constraints. Many economic systems are constrained by its own growth of capacity and resources and the environment in its survival and development process, and thus its evolution process has a limitation. This paper which based on the improved Logistic model gives a new evaluation model of energy intensity. It can adapt to changes in the economic system, a better description of the phenomenon of bounded growth, which is used to describe the relationship between economic variables, with particular emphasis on factors that energy-saving and new high-quality energy development and promotion. Parameters in the model were estimated by the estimation method for statistical test, China s energy intensity was predicted, the trend of China s energy intensity, the next few years, the decrease in energy intensity is basically stable. 2 Establishment of energy intensity model The Logistic model is dx dt = rx(1 x K (1 where x 0 = x t=0, By solving it, we can get the solution of this model: { x = K/[1 + e rt ( K x 0 1], x 0 = x t=0, (2 where r and k are model parameters. In order to estimate this equation, we assume Y = ln K x x, K x 0 1 = e a, and then substitute the solution of Logistic model into this equation. Through the deformation we can get a linear equation: Y = a rt. Next we estimate the parameter a and r. The supposed sample data {x t } contain the information of K, so a reasonable parameter estimation method is: based on sample data and using the coefficient of determination R 2 or S.E of regression as a standard, the amount of the greatest demand gaps K is determinated, and then other corresponding parameters are got. Energy intensity refers to the energy quantity which is consumed by the unit of gross domestic product, i.e I = E Y, where E indicates the energy consumption (ten thousand tons of standard coal and Y indicates the gross domestic product (hundred million yuan. As the Logistic model has the mathematical simplicity and obvious actuality, the short-term forecasting of this model is more accurate[9]. Therefore, from the forecast of energy consumption and gross domestic product based on Logistic model, a reasonable energy intensity model can be obtained: ( I (t = r E r Y r E K E E + r Y K E = E Y = K Y Y, E 1+e r E t ( K E 0 = E t=0, E0 1 K Y, Y 1+e r Y t ( K Y 0 = Y t=0, Y0 1 I, I 0 = I t=0, where r E, r Y are coefficients of economic growth. K E, K Y are energy demand and the biggest gap amount of GDP. From above equations, we can get energy intensity I (t: di(t dt = ( r Y r E r Y e a Y r Y t r E 1 + e a E r E I (4 t (3 IJNS homepage:

3 322 International Journal of NonlinearScience,Vol.9(2010,No.3,pp where e a E = K E E 0 1, E 0 = E t=0, e a Y = K Y Y 0 1, Y 0 = Y t=0. ( lni(t = (r E r Y t + r Y 1 + e a Y r Y t r E 1 + e a E r E t dt (5 then I(t = 1+ea Y r Y t C is the general solution of this equation, in which C is an arbitrary constant. 1+e a E r E t By using the initial conditions, we can determine constant C: C = 1+ea E 1+e I a Y 0 Then the solution of the equation which satisfies the initial conditions is I(t = I ea E 1 + e a Y 1 + eay ry t 1 + e a E r E t. (6 According to the data from Table 1, next we will make a reasonable estimate to parameters. Table 1: Statistics about energy consumption and gross domestic product in China from 1999 to 2008 Year Total energy consumptionten thousand tons of standard coal GDP (a hundred million yuan Year Total energy consumptionten thousand tons of standard coal GDP (a hundred million yuan According to Table 1, we can determine in the next 10 years, the approximate range about K E, K Y are [ , ] (ten thousand tons of standard coal l and [ , ] (a hundred million yuan, by using points selected by computer, we can get the regression analysis results which reflect in Table 2 and Table 3. And from these two tables, we can see that when K E = , K Y = , the goodness of fit of coefficient of determination R 2 is the highest. Table 2: The Statistical test and estimation of energy consumption in China K R a r and then Table 3: The Statistical test and estimation of GDP in China K R a r I(t = I e e t. (7 1 + e e t IJNS for contribution: editor@nonlinearscience.org.uk

4 B. B. Zhang, L. X. Tian: Analysis of China s Energy Intensity and Its Forecast The estimation and forecasting of energy intensity Relative to economic aggregate and total energy consumption, energy intensity is an exogenous variable to a great extent [10]. Theoretically, the energy intensity is the result of energy efficiency changes, but it can reflect the dynamic characteristics of energy efficiency. So it is appropriate for the requirements of this study. We estimate the energy intensity in China (Table 4 and make short-term forecasts (Figure 1 by applying the model. Table 4: The energy intensity estimation in China Year Real value Predicted value Estimation error relative error/% Figure 1: Trend of China s energy intensity 4 Evaluation of predictions and energy measures By analyzing the energy intensity model, the conclusion that the overall trend of decline in energy intensity is a curve of convex to origin can be obtained. Figure 1 shows the trend of China s energy intensity, the next few years, the decrease in energy intensity is basically stable, which is in a near-linear part of the downward phase. From the model we can see that energy consumption is an important factor in energy intensity. We know that coal consumption accounts for a large proportion in China s energy structure, its change remains the main factors affecting economic growth, in order to improve energy efficiency, we must improve the utilization efficiency of coal. Based on the analysis above, in this paper, in order to achieve rapid decline in energy intensity, several measures are proposed as follows: (1 Improve utilization efficiency of coal. We must make full use of coal resources, attaches importance to developing China-made large-scale thermal power and improve utilization efficiency of coal, while strengthening the development of clean coal technology and controlling environmental pollution. (2 Take the path from High-carbon energy sources towards low-carbon energy sources. Developing low-carbon economy and building a low-carbon society, promoting china s economic development from high-carbon energy economy to a low-carbon, carbon-free energy economy, this is a strategic choice of improving energy efficiency and reducing energy intensity. (3 Attaches great importance to development and utilization of new energy and renewable energy. As technological advances and economic development, new energy and renewable energy will play increasingly important role in our society and eventually replace High-carbon energy sources to become energy protagonist. So it is an important measure to reduce energy intensity that attaching great importance to research and development and utilization of new energy and renewable energy. IJNS homepage:

5 324 International Journal of NonlinearScience,Vol.9(2010,No.3,pp Acknowledgments Research was supported by the National Nature Science Foundation of China (No: , the Ph.D. Programs Foundation of Ministry of Education of China (No , the Humanities and Social Sciences Research general project of Ministry of Education(No.08JA and the College of Philosophy and Social Sciences key research base of major project of Jiangsu(No References [1] Y. Z. Chen and Y. T. Li. Research on Low-carbon economy and regional energy use of China. Jilin University Journal Social Sciences Edition, 49(2:(2009, [2] I. S. Wing. Explaining the declining energy intensity of the US economy. Resource and energy economics, 30(1:(2008, [3] N. Liu and B. W. Ang. Factors shaping aggregate energy intensity trend for industry: Energy intensity versus product mix. Energy Economics, 29(4:(2007, [4] H. Y. Ma, LesOxley and JohnGibson. Substitution possibilities and determinants of energy intensity for China. Energy Policy, 37:(2009, [5] F. C. Silveria and R. A. Luken. Global overview of industrial energy intensity. Energy Policy, 36:(2008, [6] Q. M. Liang, Y. M. Wei, Y. Fan and N. Okad. A Model for Scenario Analysis of China s Energy Requirement and Energy Intensity and Its Applications. Chinese Journal of Management, 1(1:(2004, [7] Z. Y. Han, Y. M. Wei and Y. Fan. Research on change features of Chinese energy intensity and economic structure. Application of Statistics and Management, 23(1:(2004,1 6. [8] L. Dong. Energy Intensity Trend and Its Influential Factors in China. Industrial Economics Research, 1:(2008,8 18. [9] Y. Fu and L. X. Tian. Statistical Verifying Estimation and Application of Logistic Model in the Forecast of Energy Consuming in Jiangsu Province. Journal of Jiangsu University of Science and Technology, 3(1:(2001, [10] G. Y. Zhuang. The energy needs and policy measures under the constraints that energy intensity decreased by 20% during the eleventh five-year plan. Review of Economic Research, 77:(2006,5 15. IJNS for contribution: editor@nonlinearscience.org.uk