Research on Production Efficiency of China's Power Systems from the Perspective of Network Structure

doi:10.11930/j.issn.1004-9649.202012113

Abstract

Abstract: Power systems play an important role in China’s energy security strategy. It is of great significance for high-quality social and economic development to comprehensively evaluate the production efficiency of power systems and their divisions in power generation, transmission, and distribution. This article adopts the data envelopment analysis (DEA) method to analyze the production efficiency of China’s power systems from 2014 to 2017. Compared with traditional DEA models, the network DEA model employs the link variables such as the on-grid electricity and distributed electricity to model the internal connections of a power system and explore the internal factors of system inefficiency. The results show that obvious regional differences in the production efficiency exist among China’s power systems, and the new round of power system reform has promoted the power system development. The heterogeneous characteristics of the external environment lead to different development paths for power systems in various regions. The effects of the policies aiming to improve the production performance are heavily dependent on the actual situations and environment where the power system locates.

Key words: network DEA, power system, production efficiency, divisional efficiency

XIE Baichen, LU Long, DUAN Na. Research on Production Efficiency of China's Power Systems from the Perspective of Network Structure[J]. Electric Power, 2021, 54(12): 128-136.

Add to citation manager EndNote|Ris|BibTeX

URL: https://www.electricpower.com.cn/EN/10.11930/j.issn.1004-9649.202012113

https://www.electricpower.com.cn/EN/Y2021/V54/I12/128

References

[1] 李科. 基于阈值回归模型的中国电力消费与经济增长的关系[J]. 系统工程理论与实践, 2012, 32(8): 1704–1711
LI Ke. Relationship between electricity consumption and economic growth of China based on threshold regression model[J]. Systems Engineering-Theory & Practice, 2012, 32(8): 1704–1711
[2] 徐云鹏. 中国电力生产业的效率: 一个基于政府管制的研究视角[J]. 数理统计与管理, 2012, 31(1): 85–95
XU Yunpeng. The efficiency of Chinese electricity production industry: a perspective of government regulation[J]. Journal of Applied Statistics and Management, 2012, 31(1): 85–95
[3] 冯梅, 于可慧. 我国电力产业技术创新效率的实证研究[J]. 中国科技论坛, 2015(1): 69–72,131
FENG Mei, YU Kehui. An empirical study on technological innovation efficiency of China electric power industry[J]. Forum on Science and Technology in China, 2015(1): 69–72,131
[4] 范玉仙, 袁晓玲. 基于NSBM-ML模型的中国电力行业技术效率和全要素生产率研究[J]. 当代经济科学, 2015, 37(4): 90–99,127
FAN Yuxian, YUAN Xiaoling. Research on technical efficiency of Chinese electricity industry and total factor productivity based on NSBM-ML model[J]. Modern Economic Science, 2015, 37(4): 90–99,127
[5] 王婵, 邹斌, 金茜, 等. 基于两阶段DEA方法的中国省际电力能源利用效率评估[J]. 数学的实践与认识, 2020, 50(2): 150–161
WANG Chan, ZOU Bin, JIN Xi, et al. Efficiency evaluation on energy utilization of Chinese inter-provincial electric power based on two-stage DEA method[J]. Mathematics in Practice and Theory, 2020, 50(2): 150–161
[6] 仇磊, 王俊和, 仲跃, 等. 基于因子分析和数据包络分析的发电企业能效评价研究[J]. 热力发电, 2019, 48(12): 87–91
QIU Lei, WANG Junhe, ZHONG Yue, et al. Research on energy efficiency evaluation for power generation enterprises based on factor analysis and data envelopment analysis[J]. Thermal Power Generation, 2019, 48(12): 87–91
[7] 王婷婷, 朱建平. 环境约束下电力行业能源效率研究[J]. 中国人口·资源与环境, 2015, 25(3): 120–127
WANG Tingting, ZHU Jianping. Energy efficiency of the electric power industry research under environmental constraints[J]. China Population, Resources and Environment, 2015, 25(3): 120–127
[8] 解百臣, 徐大鹏, 刘明磊, 等. 基于投入型Malmquist指数的省际发电部门低碳经济评价[J]. 管理评论, 2010, 22(6): 119–128
XIE Baichen, XU Dapeng, LIU Minglei, et al. Low carbon economy study on Provinces'Power generation sector based on input malmquist index[J]. Management Review, 2010, 22(6): 119–128
[9] 何康, 方思然, 方虹. 绿色风电企业与非绿色风电企业的运营效率比较研究: 基于Malmquist-DEA模型分析[J]. 生态经济, 2019, 35(6): 60–65
HE Kang, FANG Siran, FANG Hong. Comparative study on operational efficiency of green wind power enterprises and non-green wind power enterprises: based on the Malmquist-DEA model analysis[J]. Ecological Economy, 2019, 35(6): 60–65
[10] 王敬敏, 薛雨田. 基于数据包络模型的电力行业碳排放权配额初始分配效率研究[J]. 中国电力, 2013, 46(10): 146–150
WANG Jingmin, XUE Yutian. Efficiency of power industry carbon emission quotas based on data envelopment[J]. Electric Power, 2013, 46(10): 146–150
[11] 唐标, 程志万, 李博, 等. 基于改进鲁棒DEA模型的电力系统评价研究[J]. 电子器件, 2020, 43(2): 273–279
TANG Biao, CHENG Zhiwan, LI Bo, et al. Research on power system evaluation based on improved robust DEA model[J]. Chinese Journal of Electron Devices, 2020, 43(2): 273–279
[12] 彭昱. 我国电力产业环境效率评价[J]. 财经科学, 2011(2): 76–83
PENG Yu. Rating electric industry's environment efficiency in China[J]. Finance & Economics, 2011(2): 76–83
[13] 姜雯昱, 曹俊文. 环境压力转移视角下电力行业生态效率区域差异研究[J]. 科技管理研究, 2019, 39(15): 252–259
JIANG Wenyu, CAO Junwen. Study on regional difference of ecological efficiency of electric power industry from the perspective of environmental pressure transfer[J]. Science and Technology Management Research, 2019, 39(15): 252–259
[14] 李力春. 中国各省份火电行业技术效率及其环境影响因素实证研究[J]. 经济问题, 2018(1): 71–77
LI Lichun. Empirical study on technical efficiency and its environmental factors of thermal power industry in China[J]. On Economic Problems, 2018(1): 71–77
[15] 严正, 李磊, 韩冬, 等. 基于改进超效率数据包络分析的低碳电力生产效率评估模型[J]. 电力系统自动化, 2014, 38(17): 170–176
YAN Zheng, LI Lei, HAN Dong, et al. Evaluation model for low-carbon electricity production efficiency based on improved super efficiency data envelopment analysis method[J]. Automation of Electric Power Systems, 2014, 38(17): 170–176
[16] 汪锋, 吴俊. 电力生产、跨省交易与能源环境效率[J]. 技术经济, 2016, 35(12): 90–96
WANG Feng, WU Jun. Electric power production, inter-provincial trade and energy environmental efficiency[J]. Technology Economics, 2016, 35(12): 90–96
[17] 姜春海, 胡亚妮. 火电上市公司的技术效率及影响因素: 基于DEA方法和Tobit模型的实证分析[J]. 宏观经济研究, 2014(8): 61–73
[18] 雍浩, 杨少华, 杨颖, 等. 基于DEA-Malmquist指数法的供电企业绩效评价研究[J]. 智慧电力, 2019, 47(4): 73–80
YONG Hao, YANG Shaohua, YANG Ying, et al. Performance evaluation of power supply enterprises based on DEA-malmquist index method[J]. Smart Power, 2019, 47(4): 73–80
[19] 赵天燕, 孙涛, 郭文. 火力发电企业环境效率及全要素生产率[J]. 财贸研究, 2015, 26(5): 19–25
ZHAO Tianyan, SUN Tao, GUO Wen. Environmental efficiency and its total factor productivity of thermal power enterprises[J]. Finance and Trade Research, 2015, 26(5): 19–25
[20] 邵留国, 何莹莹, 张仕璟, 等. 基于网络DEA的中国火电行业循环经济效率及影响因素研究[J]. 资源科学, 2016, 38(10): 1975–1987
SHAO Liuguo, HE Yingying, ZHANG Shijing, et al. Circulation economic efficiency and its influence factors of China's thermal power industry based on network DEA model[J]. Resources Science, 2016, 38(10): 1975–1987
[21] 闫志雄, 张宁, 宋红芳, 等. 基于DEA的电网绩效评估方法[J]. 电力系统保护与控制, 2014, 42(7): 67–72
YAN Zhixiong, ZHANG Ning, SONG Hongfang, et al. A grid performance assessment method based on DEA[J]. Power System Protection and Control, 2014, 42(7): 67–72
[22] 鲁强, 刘进, 蒋东方. 中国电网行业发展效率及区域差异分析[J]. 中国电力, 2019, 52(2): 119–124
LU Qiang, LIU Jin, JIANG Dongfang. Analysis of development efficiency and regional differences in China power grid industry[J]. Electric Power, 2019, 52(2): 119–124
[23] 魏权龄. 数据包络分析[M]. 北京: 科学出版社, 2004.
[24] CHARNES A, COOPER W W, RHODES E. Measuring the efficiency of decision making units[J]. European Journal of Operational Research, 1978, 2(6): 429–444.
[25] YOU Y Q, JIE T. A study of the operation efficiency and cost performance indices of power-supply companies in China based on a dynamic network slacks-based measure model[J]. Omega, 2016, 60: 85–97.
[26] 陈昌兵. 可变折旧率估计及资本存量测算[J]. 经济研究, 2014, 49(12): 72–85
CHEN Changbing. Estimation of variable depreciation rate and measurement of capital stock[J]. Economic Research Journal, 2014, 49(12): 72–85