• • 上一篇    

技术创新情境下中国电力行业要素生产弹性及生产效率分析

杨栩1, 卢焱1,2, 马艺翔3, 余乐安1,3,4   

  1. 1. 哈尔滨工程大学经济管理学院, 哈尔滨 150001;
    2. 中交第四公路工程局有限公司, 北京 100022;
    3. 北京化工大学经济管理学院, 北京 100029;
    4. 滨州魏桥国科高等技术研究院, 滨州 256600
  • 收稿日期:2022-05-24 修回日期:2022-08-05 发布日期:2022-11-04
  • 基金资助:
    国家自然科学基金项目(72034003)资助课题.

杨栩, 卢焱, 马艺翔, 余乐安. 技术创新情境下中国电力行业要素生产弹性及生产效率分析[J]. 系统科学与数学, 2022, 42(10): 2727-2739.

YANG Xu, LU Yan, MA Yixiang, YU Lean. Analysis on Factor Production Elasticity and Production Efficiency of China's Power Industry in the Context of Technological Innovation[J]. Journal of Systems Science and Mathematical Sciences, 2022, 42(10): 2727-2739.

Analysis on Factor Production Elasticity and Production Efficiency of China's Power Industry in the Context of Technological Innovation

YANG Xu1, LU Yan1,2, MA Yixiang3, YU Lean1,3,4   

  1. 1. School of Economics and Management, Harbin Engineering University, Harbin 150001;
    2. CCCC Fourth Highway Engineering Co. Ltd, Beijing 100022;
    3. School of Economics and Management, Beijing University of Chemical Technology, Beijing 100029;
    4. School of Business, Binzhou Institute of Technology, Binzhou 256600
  • Received:2022-05-24 Revised:2022-08-05 Published:2022-11-04
为探究技术创新对于电力市场供给的影响,文章通过构建面板随机前沿模型,研究新常态时期中国电力行业要素投入生产弹性及生产效率的变动趋势,并分析了不同投入要素对电力市场供给的影响力大小和方向.进而,通过对比不同地区和省份在新常态时期前后生产效率的差异,分析了中国各地电力行业技术创新的变动趋势.通过一系列假设检验,证明了面板随机前沿模型的适用性,可以对中国电力行业的技术效率进行分析,并确定了包含时间变量的超越对数生产函数设定形式.结合参数估计结果,证明了资本的生产弹性为正,这说明电力行业仍属于资本密集型行业,现阶段资本投入的增加能够较大提高电力市场供给.同时,研究证明了中国电力行业整体技术效率较高,且步入新常态时期以来,西部地区电力行业平均技术效率的增长幅度高于其他地区,西部地区电力行业高技术效率省份明显增多,宁夏、云南和新疆省份的电力行业技术效率较新常态时期之前提升明显,说明包括高压/特高压输电技术、节能技术、新能源技术、储能技术等电力创新技术的应用,有助于提高电力行业技术效率.
In order to explore the effect of technological innovation on the supply of the electricity market,this paper investigates the changing trend of the production efficiency of China's power industry during the "New Normal " period by constructing a panel stochastic frontier model,and analyzes the impact and direction of different input factors on the supply of the electricity market.Furthermore,by comparing the differences in production efficiency between different regions and provinces before and after the "New Normal" period,the changing trend of technological innovation in the power industry in various regions of China is analyzed.Through a series of hypothesis tests,the applicability of the panel stochastic frontier model is proved.By using this model,the technical efficiency of China's power industry can be analyzed,and the set form of the transcendent logarithmic production function with time variables can be determined.Combined with the results of parameter estimation,we prove that the output elasticity of capital is positive,indicating that the power industry is still a capital-intensive industry,and the increase in capital input at this stage can greatly improve the supply of the electricity market.At the same time,this study proves that the overall technical efficiency of China's power industry is relatively high.In particular,since entering the "New Normal" period,the average technical efficiency of the power industry in the western region has increased significantly relative to other regions,the provinces with high technical efficiency in the power industry in the western region have increased significantly,and the technical efficiency of the power industry in Ningxia,Yunnan and Xinjiang provinces has improved significantly compared with before the "New Normal" period,indicating that the application of power innovation technologies including high voltage/ultra-high voltage transmission technology,energy saving technology,new energy technology,energy storage technology and other power innovation technologies will help improve the technical efficiency of the power industry.

MR(2010)主题分类: 

()
[1] 袁奥.电气自动化技术在火力发电中的创新运用.通信电源技术, 2019, 36(8):243-244.(Yuan A. Innovative application of electrical automation technology in thermal power generation. Telecom Power Technology, 2019, 36(8):243-244.)%注:中文参考文献需附对应英文翻译,且中文文章杂志名称不用斜体.
[2] 黄迪南.以技术创新引领新一代高效洁净燃煤发电装备的开发.华东电力, 2014, 42(1):6-11.(Huang D N. Development of new efficient clean coal-fired power generation equipment led by technology innovation. East China Electric Power, 2014, 42(1):6-11.)
[3] 檀炜.热工自动化技术在火力发电中的应用与创新.工程建设与设计, 2018,(19):161-163.(Tan W. Application and innovation of thermal automation technology in thermal power generation. Construction and Design for Project, 2018,(19):161-163.)
[4] 林伯强."十三五"时期中国电力发展成就及"十四五"展望.中国电业, 2020,(12):22-23.(Lin B Q. China's electric power development achievements during the"13th Five-Year Plan "period and prospects for the" 14th Five-Year Plan". China Electric Power, 2020,(12):22-23.)
[5] Hast A, Alimohammadisagvand B, Syri S. Consumer attitudes towards renewable energy in China-The case of Shanghai. Sustainable Cities Society, 2015, 17:69-79.
[6] Wang S, Li J, Zhao D. The impact of policy measures on consumer intention to adopt electric vehicles:Evidence from China. Transportation Research Part A Policy, 2017, 105:14-26.
[7] Ou X, Yan X, Zhang X. Life-cycle energy consumption and greenhouse gas emissions for electricity generation and supply in China. Applied Energy, 2011, 88(1):289-297.
[8] Mikiewicz R. Efficiency of electricity production technology from post-process gas heat:Ecological, economic and social benefits. Energies, 2020, 13(22):6106.
[9] 李少林. 2001-2012年全球23国新能源发电效率测算与驱动因素分析.资源科学, 2016, 38(2):321-332.(Li S L. Research on calculation of new energy's power generation efficiency and analysis on its driving factors. Resource Science, 2016, 38(2):321-332.)
[10] Evans A, Strezov V, Evans T J. Sustainability considerations for electricity generation from biomass. Renewable Sustainable Energy Reviews, 2010, 14(5):1419-1427.
[11] 陈威,马永开,白春光.基于碳限额与交易机制的上下游企业可再生能源投资策略研究.中国管理科学, 2020, 1-19, DOI:10.16381/j.cnki.issn1003-207x.2020.1017.(Chen W, Ma Y K, Bai C G. Research on upstream and downstream enterprises of renewable energy investment under cap-and-trade mechanism. Chinese Journal of Management Science, 2020, 1-19, DOI:10.16381/j.cnki.issn1003-207x.2020.1017.)
[12] 何菲.广东省首个大兆瓦级海上风电项目年发电量超预期.新能源科技, 2021,(2):10-11.(He F. The annual power generation of the first large-megawatt offshore wind power project in Guangdong Province exceeds expectations. New Energy Technology, 2021,(2):10-11.)
[13] Lin B, Wu W. Cost of long distance electricity transmission in China. Energy Policy, 2017, 109:132-140.
[14] Zhang C, Zhong L, Liang S, et al. Virtual scarce water embodied in inter-provincial electricity transmission in China. Applied Energy, 2017, 187:438-448.
[15] Xu J H, Yi B W, Fan Y. Economic viability and regulation effects of infrastructure investments for inter-regional electricity transmission and trade in China. Energy Economics, 2020, 91:104890.
[16] Zeng M, Peng L L, Fan Q N, et al. Trans-regional electricity transmission in China:Status, issues and strategies. Renewable Sustainable Energy Reviews, 2016, 66:572-583.
[17] 邓水群.基于低线损目标的输配电技术创新策略.技术与市场, 2020, 27(10):118-119.(Deng S Q. Innovation strategy of transmission and distribution technology based on low line loss target. Technology and Market, 2020, 27(10):118-119.)
[18] 张祖平.直流配电技术的发展前景.供用电, 2015,(2):52-53.(Zhang Z P. Development prospects of DC power distribution technology. Electricity Supply and Consumption, 2015,(2):52-53.)
[19] 杨秀峰.减少线损条件下的输配电技术创新探讨.电子制作, 2016,(15):90-92.(Yang X F. Discussion on innovation of transmission and distribution technology under the condition of reducing line loss. Electronic Manufacturing, 2016,(15):90-92.)
[20] 陈丛波,叶阿忠.传统能源、可再生能源电力生产与经济增长——基于半参数结构全局向量自回归模型的实证分析.华南理工大学学报(社会科学版), 2021, 23(1):60-72.(Chen C B, Ye A Z. Conventional Energy, Renewable energy electricity generation and economic growth-Empirical analysis based on global vector autoregressive model of semi-parametric structure. Journal of South China University of Technology (Social Science Edition), 2021, 23(1):60-72.)
[21] Lei H, Yao X, Zhang J. The competitiveness of provincial electric power supply in China:Based on a bottom-up perspective. International Journal of Electrical Power Energy Systems, 2020, 116:105557.
[22] 胡欣悦,任紫娟,汤勇力.我国重点高校技术转移效率变化的影响因素研究——基于面板随机前沿分析方法.技术经济, 2020, 39(7):200-208.(Hu X Y, Ren Z J, Tang Y L. Research on the influential factors of the technology transfer efficiency in Chinese key universities:Based on the panel stochastic frontier analysis. Technology and Economics, 2020, 39(7):200-208.)
[23] 史红亮,陈凯,闫波.我国钢铁行业能源-资本-劳动的替代弹性分析——基于超越对数生产函数.工业技术经济, 2010, 29(11):110-116.(Shi H L, Chen K, Yan B. Substitution elasticity among energy, capital and labor inputs in Chinese steel sector-Based on a trans-log production function. Journal of Industrial Technological Economics, 2010, 29(11):110-116.)
[24] 李锴科,肖先勇,汪颖,等.基于空间面板数据的中国省域用电需求空间效应实证分析模型.现代电力, 2017, 34(2):80-86.(Li K K, Xiao X Y, Wang Y, et al. The spatial effect empirical analysis model of provincial electricity demand in China based on spatial panel data. Modern Electric Power, 2017, 34(2):80-86.)
[25] 董梅,徐璋勇.中国能源回弹效应测度及集聚性研究——基于技术进步分解的视角.贵州大学学报(社会科学版), 2015, 33(5):89-95.(Dong M, Xu Z Y. Measure and agglomeration of energy consumption rebound effects in China:Based on decomposition of technological progress. Chinese Journal of Guizhou University (Social Science Edition), 2015, 33(5):89-95.)
[1] 陈理, 周忠宝, 黄珺. 供应网络位置、管理层能力与企业技术创新------基于融资和风险视角[J]. 系统科学与数学, 2021, 41(11): 3078-3092.
[2] 崔春生. 基于软集理论的技术创新方案评价方法研究[J]. 系统科学与数学, 2017, 37(4): 1092-1099.
[3] 王凤莲,赵骅. 技术创新对集群双寡头产量博弈均衡的影响分析[J]. 系统科学与数学, 2016, 36(8): 1255-1264.
阅读次数
全文


摘要