Empirical research on technical efficiency of wind power industry in China based on SFA method

被引:1
作者
Zhang, Jiahui [1 ]
Wang, Yibing [1 ]
Gao, Li [1 ]
机构
[1] China Univ Petr, Sch Econ & Management, Beijing 102249, Peoples R China
基金
英国科研创新办公室;
关键词
Wind farm; Technical efficiency; Stochastic frontier analysis; Data envelopment analysis; PERFORMANCE ASSESSMENT; PRODUCTIVE EFFICIENCY; FARMS; GENERATION;
D O I
10.1007/s10668-023-03072-9
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
In recent years, the vigorous development of the wind power industry has become an important measure in the transformation of energy structure in China. However, the overall low technical efficiency of wind farms has severely hindered wind power industrial development. It is of great practical significance to evaluate the technical efficiency (TE) of wind power in China and analyze its main factors. Most of the existing literature on the assessment of the TE of wind power in China focuses only on large listed companies and applies the traditional data envelopment analysis (DEA) while ignoring its potential shortcomings for TE estimation. Based on panel data, this paper used stochastic frontier analysis (SFA) to construct an analytical model for assessing the TE and influencing factors of Chinese wind farms and compared the results with those from DEA to verify the robustness. The empirical results showed that the TE of Chinese wind farms was generally low. The age of a wind farm and its power consumption have a negative impact on its technical efficiency, while the utilization of power generation equipment has a positive impact on its technical efficiency. Enhancing the technological innovation capabilities of wind power companies, speeding up the construction of supporting infrastructure and solving structural problems of wind power supply and demand are important measures for the wind power industry to improve the overall TE and promote industrial development in China.
引用
收藏
页码:8443 / 8465
页数:23
相关论文
共 33 条
[1]   A cross-European efficiency assessment of offshore wind farms: A DEA approach [J].
Akbari, Negar ;
Jones, Dylan ;
Treloar, Richard .
RENEWABLE ENERGY, 2020, 151 :1186-1195
[2]   Wind energy resource assessment for Kiribati with a comparison of different methods of determining Weibull parameters [J].
Aukitino, Tiaon ;
Khan, M. G. M. ;
Ahmed, M. Rafiuddin .
ENERGY CONVERSION AND MANAGEMENT, 2017, 151 :641-660
[3]   Performance assessment of Portuguese wind farms: Ownership and managerial efficiency [J].
Barros, Carlos Pestana ;
Antunes, Olinda Sequeira .
ENERGY POLICY, 2011, 39 (06) :3055-3063
[4]  
Battese G., 1995, J. Econom., V20, P325, DOI DOI 10.1007/BF01205442
[5]   Measuring the long run technical efficiency of offshore wind farms [J].
Benini, Giacomo ;
Cattani, Gilles .
APPLIED ENERGY, 2022, 308
[6]   Comparison of seven numerical methods for determining Weibull parameters for wind energy generation in the northeast region of Brazil [J].
Costa Rocha, Paulo Alexandre ;
de Sousa, Ricardo Coelho ;
de Andrade, Carla Freitas ;
Vieira da Silva, Maria Eugenia .
APPLIED ENERGY, 2012, 89 (01) :395-400
[7]   Economic and climate impacts of reducing China's renewable electricity curtailment: A comparison between CGE models with alternative nesting structures of electricity [J].
Cui, Qi ;
Liu, Yu ;
Ali, Tariq ;
Gao, Ji ;
Chen, Hao .
ENERGY ECONOMICS, 2020, 91 (91)
[8]  
Dennis A., 1977, J. Econ., V6, P21, DOI [10.1016/0304-4076(77)90052-5, DOI 10.1016/0304-4076(77)90052-5]
[9]   Regional differences study of renewable energy performance: A case of wind power in China [J].
Dong, Fugui ;
Shi, Lei .
JOURNAL OF CLEANER PRODUCTION, 2019, 233 :490-500
[10]   THE RELATIVE EFFICIENCY OF ILLINOIS ELECTRIC UTILITIES [J].
FARE, R ;
GROSSKOPF, S ;
LOGAN, J .
RESOURCES AND ENERGY, 1983, 5 (04) :349-367