中国可再生能源消费预测及补贴策略研究

doi:10.11930/j.issn.1004-9649.2016.04.181.07

中国电力 ›› 2016, Vol. 49 ›› Issue (4): 181-187.DOI: 10.11930/j.issn.1004-9649.2016.04.181.07

中国可再生能源消费预测及补贴策略研究

赵文会,高姣倩,宋亚君,黄海涛

上海电力学院经济与管理学院,上海 200090

收稿日期:2015-10-10 出版日期:2016-04-20 发布日期:2016-04-27
作者简介:赵文会(1977-),女,辽宁朝阳人,博士,教授,从事能源环境政策分析和系统分析与优化等研究。E-mail: wenhui_zhao@163.com
基金资助:
国家自然科学基金项目(71403163,71203137); 教育部人文社会科学研究一般项目(11YJC790295); 中国博士后科学基金项目(2013M540910); 上海市哲学社科规划基金项目(2014BJB017)

Forecasting Analysis and Subsidy Strategy on Renewable Energy Consumption of China

ZHAO Wenhui, GAO Jiaoqian, SONG Yajun, HUANG Haitao

Shanghai University of Electric Power, School of Economics and Management, Shanghai 200090, China

Received:2015-10-10 Online:2016-04-20 Published:2016-04-27
Supported by:
This work is supported by National Natural Science Foundation Project of China (No. 71403163, 71203137); General Project of Humanities and Social Sciences in the Ministry of Education(No. 11YJC790295); The Post-doctoral Science Foundation Project of China (No. 2013M540910); Shanghai Municipal Philosophy and Social Science Planning Fund Project (No. 2014BJB017).

摘要/Abstract

摘要： 可再生能源消费受多种因素影响,简单的灰色模型已经不能对可再生能源消费作出准确预测。将传统的灰色GM(1,1)模型与缓冲算子相结合,模拟和预测中国的可再生能源消费,探究了政策补贴对中国可再生能源消费的影响,在预测结果基础之上构建了2种政策补贴策略模型,研究了中国可再生能源消费的政策补贴力度。结果显示,基于缓冲算子的GM(1,1)方法拟合效果更好,模型精度更高; 2013—2020年中国可再生能源消费占比呈现递增趋势,但是在停止政策补贴力度的情况下,增长趋势明显低于延续原有政策补贴力度。

关键词: 可再生能源, 政策补贴, 缓冲算子, GM(1, 1), 补贴策略

Abstract: The consumption of renewable energy is influenced by several factors, and the gray model cannot make accurate forecast in this case. The renewable energy consumption in China is simulated and forecasted based on combination of buffer operator and grey GM(1, 1) model. Impact of policy subsidy on renewable energy consumption is also discussed. Two kinds of subsidy strategy models based on renewable energy consumption forecasting are established to explore the impact strength of policy subsidy on renewable energy consumption. Excel is used to solve the model and the result shows that the GM(1, 1) method combined with buffer operator has better fitting accuracy. During period of 2013-2020, the ratio of renewable energy consumption trend to increase. However, the growth rate without policy subsidies is significantly lower than that with continuation of the original policy subsidies. In addition, in order to successfully complete plan goal of “long-term planning for renewable energy development”, policy subsidy need to be adjust to at least 1.65 times of previous value.

Key words: renewable energy, policy subsidy, buffer operator, GM(1, 1), subsidy strategy

中图分类号:

F206

赵文会,高姣倩,宋亚君,黄海涛. 中国可再生能源消费预测及补贴策略研究[J]. 中国电力, 2016, 49(4): 181-187.

ZHAO Wenhui, GAO Jiaoqian, SONG Yajun, HUANG Haitao. Forecasting Analysis and Subsidy Strategy on Renewable Energy Consumption of China[J]. Electric Power, 2016, 49(4): 181-187.

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参考文献

[1] 沈镭,刘立涛,王礼茂,等. 2050年中国能源消费的情景预测[J].自然资源学报,2014,30(3)：361－370.
SHEN Lei, LIU Litao, WANG Limao, et al. 2050 Energy consumption projection for China[J]. Journal of Natural Resources, 2014, 30(3): 361-370.
[2] PERRY S. Renewable energy consumption, CO2 emissions and oil prices in the G7 countries [J]. Energy Economics, 2009, 31(3): 456-462.
[3] NICHOLAS A, JAMES E, PAYNE. Renewable energy consumption and growth in eurasia [J]. Energy Economics, 2012, 32(6): 1392-1397.
[4] NICHOLAS A, JAMES E, PAYNE. Renewable and non- renewable energy consumption-growth nexus: Evidence from a panel error correction model [J]. Energy Economics, 2012, 34(3): 733-738.
[5] KOJO M, YEMANE W R. CO2 emissions, nuclear energy, renewable energy and economic growth in the US[J]. Energy Policy, 2010(38): 2911-2915.
[6] OGUZ O, ALPER A. Renewable energy consumption—economic growth nexus in Turkey[J]. Renewable and Sustainable Energy Reviews, 2013(28): 494-499.
[7] CAN T T, ILHAN O, ALPER A. Renewable and non-renewable energy consumption and economic growth relationship revisited: Evidence from G7 countries[J]. Energy Economics, 2012, 34(6): 1942-1950.
[8] MAAMAR S, OUSAMA B S. On the causal dynamics between economic growth, renewable energy consumption, CO2 emissions and trade openness: Fresh evidence from BRICS countries [J]. Renewable and Sustainable Energy Reviews, 2014(39): 14-23.
[9] BOQING L, MOHAMED M. Renewable energy consumption—Economic growth nexus for China [J]. Renewable and Sustainable Energy Reviews, 2014(40): 111-117.
[10] MUHAMMAD S, NANTHAKUMAN L, MOHAMMAD Z, et al. Does renewable energy consumption add in economic growth? An application of auto-regressive distributed lag model in Pakistan [J]. Renewable and Sustainable Energy Reviews, 2015(44): 576-585.
[11] 后勇,徐福缘,程维. 基于可再生能源替代的经济持续发展模型[J]. 系统工程理论与实践,2008(9)：67－71.
HOU Yong, XU Fuyuan, CHENG Wei. Sustainable growth model based on the substitution of renewable energy[J]. Systems Engineering Theory & Practice, 2008 (9): 67-71.
[12] 刘岩,于渤,洪富艳. 基于可持续发展的可再生能源替代动态增长模型研究[J]. 中国软件科学,2011(增刊上)：240－246.
LIU Yan, YU bo, HONG Fuyan. Study on renewable energy dynamic state growth model on sustainable development theory [J]. The Soft Science in China, 2011(Supplement): 240-246.
[13] 刘贞,张希良,高虎. 基于行业增长的省级可再生能源规划目标分解[J]. 中国人口·资源与环境,2011,21(4)：100－103.
LIU Zhen, ZHANG Xiliang, GAO Hu. Target decomposition of renewable energy based on industrial growth [J]. China Population, Resources and Environment, 2011, 21(4): 100-103.
[14] 刘贞,张希良,高虎. 可再生能源发展情景设计及评价研究[J].中国人口·资源与环境,2011,21(7)：28－31.
LIU Zhen, ZHANG Xiliang, GAO Hu. Study on design and evaluation of the development scenarios of renewable Energy [J]. China Population, Resources and Environment, 2011, 21(7): 28-31.
[15] 李虹,董亮,段红霞. 中国可再生能源发展综合评价与结构优化研究[J]. 资源科学,2011,33(3)：431－440.
LI Hong, DONG Liang, DUAN Hongxia. On comprehensive evaluation and optimization of renewable energy development in China [J]. Resources Science, 2011, 33(3): 431-440.
[16] 李继峰,张阿玲. 我国新能源和可再生能源发展预测方法研究：风能发电预测案例[J]. 可再生能源,2004,22(3)：1－4.
LI Jifeng, ZHANG Aling. Forecast method research of new energy and renewable energy development in China: Case of wind power forecase [J]. Renewable Energy Resources, 2004, 22(3): 1-4.
[17] AZADEH A, BABAZADEH R, ASADZDDEH S M. Optimum estimation and forecasting of renewable energy consumption by artificial neural networks[J]. Renewable and Sustainable Energy Reviews, 2013(27): 605-612.
[18] 宋辉,魏晓平. 中国可再生能源替代率的理性预测[J]. 经济经纬,2011(2)：10－13.
SONG Hui, WEI Xiaoping. A rational forecast of the replacement rate of renewable energy in China[J]. Economic Survey, 2011(2): 10-13.
[19] 殷英,谭元发. 我国新能源ARMA模型分析与预测[J]. 数学理论与应用,2009,29(4)：125－128.
YIN Ying, TAN Yuanfa. ARMA model analyzing and forecast on the new source of China[J]. Mathematical Theory and Applications, 2009, 29(4): 125-128.
[20] 罗鑫,张粒子,李才华. 可再生能源电力市场模式研究[J]. 中国电力,2006,39(9)：32－36.
LUO Xin, ZHANG Lizi, LI Caihua. Study on the power market mode of renewable energy [J]. Electric Power, 2006, 39(9): 32-36.
[21] 叶璟,李炳军,刘芳. 弱化缓冲算子对GM(1,1)模型的预测效应及适用性[J]. 系统工程理论与实践,2014,34(9)：2364－2370.
YE Jing, LI Bingjun, LIU Fang. Forecasting effect and applicability of weakening buffer operators on GM(1,1) [J]. Systems Engineering Theory & Practice, 2014, 34(9): 2364-2370.
[22] 花玲,谢乃明. 政策冲击影响下的中国能源消费预测分析及控制策略[J]. 中国管理科学,2014,22(7)：18－24.
HUA Ling, XIE Naiming. Forecasting analysis of chinese energy consumption and control strategy under policy impact [J]. Chinese Journal of Management Science, 2014, 22(7): 18-24.
[23] 刘思峰,党耀国,方志耕,等. 灰色系统理论及其应用[M]. 北京：科学出版社,2004.
[24] 刘思峰. 冲击扰动系统预测陷阱与缓冲算子[J]. 华中理工大学学报,1997,25(1)：25－29.
LIU Sifeng. The trap in the prediction of a shock disturbed system and the buffer operator [J]. Journal of Huazhong University of Science & Technology, 1997, 25(1): 25-27.

中国可再生能源消费预测及补贴策略研究

Forecasting Analysis and Subsidy Strategy on Renewable Energy Consumption of China

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中国可再生能源消费预测及补贴策略研究

Forecasting Analysis and Subsidy Strategy on Renewable Energy Consumption of China

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