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Analysis of Driving Factors of Photovoltaic Power Generation Efficiency: A Case Study in China

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  • Tao Yi

    (School of Economics and Management, North China Electric Power University, Beijing 102206, China
    Beijing Key Laboratory of New Energy and Low-Carbon Development (North China Electric Power University), Beijing, 102206, China)

  • Ling Tong

    (School of Economics and Management, North China Electric Power University, Beijing 102206, China
    Beijing Key Laboratory of New Energy and Low-Carbon Development (North China Electric Power University), Beijing, 102206, China)

  • Mohan Qiu

    (School of Economics and Management, North China Electric Power University, Beijing 102206, China
    Beijing Key Laboratory of New Energy and Low-Carbon Development (North China Electric Power University), Beijing, 102206, China)

  • Jinpeng Liu

    (School of Economics and Management, North China Electric Power University, Beijing 102206, China
    Beijing Key Laboratory of New Energy and Low-Carbon Development (North China Electric Power University), Beijing, 102206, China)

Abstract

With the increasing consumption of fossil energy and changes in the ecological environment, meeting the energy demands required for industrial and economic development with clean and efficient power generation is a major challenge of our society. Solar energy is considered to be one of the most renewable and sustainable energy sources, and photovoltaic power generation has become an important research topic. This study combines data envelopment analysis (DEA) with Tobit regression analysis to assess the efficiency of photovoltaic power generation in China and analyze factors affecting efficiency to improve the efficiency of photovoltaic power generation. The results show that there are obvious regional differences in photovoltaic power generation efficiency in China. The phenomenon of focusing on economic development at the expense of the use of solar power generation still exists. The establishment of photovoltaic demonstration projects, the implementation of differential electricity price policies, and the promotion of photovoltaic precision poverty alleviation can alleviate economic pressure and effectively improve the efficiency of photovoltaic power generation.

Suggested Citation

  • Tao Yi & Ling Tong & Mohan Qiu & Jinpeng Liu, 2019. "Analysis of Driving Factors of Photovoltaic Power Generation Efficiency: A Case Study in China," Energies, MDPI, vol. 12(3), pages 1-15, January.
    • Handle: RePEc:gam:jeners:v:12:y:2019:i:3:p:355-:d:200236
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    References listed on IDEAS

    as
    1. Pérez-López, Gemma & Prior, Diego & Zafra-Gómez, José L., 2018. "Temporal scale efficiency in DEA panel data estimations. An application to the solid waste disposal service in Spain," Omega, Elsevier, vol. 76(C), pages 18-27.
    2. Wang, Jiangjiang & Lu, Yanchao & Yang, Ying & Mao, Tianzhi, 2016. "Thermodynamic performance analysis and optimization of a solar-assisted combined cooling, heating and power system," Energy, Elsevier, vol. 115(P1), pages 49-59.
    3. Abbas Mardani & Dalia Streimikiene & Tomas Balezentis & Muhamad Zameri Mat Saman & Khalil Md Nor & Seyed Meysam Khoshnava, 2018. "Data Envelopment Analysis in Energy and Environmental Economics: An Overview of the State-of-the-Art and Recent Development Trends," Energies, MDPI, vol. 11(8), pages 1-21, August.
    4. Babatunde, A.A. & Abbasoglu, S. & Senol, M., 2018. "Analysis of the impact of dust, tilt angle and orientation on performance of PV Plants," Renewable and Sustainable Energy Reviews, Elsevier, vol. 90(C), pages 1017-1026.
    5. Liping Ding & Fan Zhang & Jing Shuai, 2018. "How Do Chinese Residents Expect of Government Subsidies on Solar Photovoltaic Power Generation?—A Case of Wuhan, China," Energies, MDPI, vol. 11(1), pages 1-11, January.
    6. Li, Ji Feng & Wang, Xin & Zhang, Ya Xiong & Kou, Qin, 2014. "The economic impact of carbon pricing with regulated electricity prices in China—An application of a computable general equilibrium approach," Energy Policy, Elsevier, vol. 75(C), pages 46-56.
    7. García-Álvarez, María Teresa & Cabeza-García, Laura & Soares, Isabel, 2018. "Assessment of energy policies to promote photovoltaic generation in the European Union," Energy, Elsevier, vol. 151(C), pages 864-874.
    8. Wade D. Cook & Joe Zhu, 2015. "DEA Cross Efficiency," International Series in Operations Research & Management Science, in: Joe Zhu (ed.), Data Envelopment Analysis, edition 127, chapter 2, pages 23-43, Springer.
    9. Henrik Zsiborács & Nóra Hegedűsné Baranyai & András Vincze & István Háber & Gábor Pintér, 2018. "Economic and Technical Aspects of Flexible Storage Photovoltaic Systems in Europe," Energies, MDPI, vol. 11(6), pages 1-17, June.
    10. Han, Yongming & Geng, Zhiqiang & Zhu, Qunxiong & Qu, Yixin, 2015. "Energy efficiency analysis method based on fuzzy DEA cross-model for ethylene production systems in chemical industry," Energy, Elsevier, vol. 83(C), pages 685-695.
    11. Henrik Zsiborács & Attila Bai & József Popp & Zoltán Gabnai & Béla Pályi & István Farkas & Nóra Hegedűsné Baranyai & Mihály Veszelka & László Zentkó & Gábor Pintér, 2018. "Change of Real and Simulated Energy Production of Certain Photovoltaic Technologies in Relation to Orientation, Tilt Angle and Dual-Axis Sun-Tracking. A Case Study in Hungary," Sustainability, MDPI, vol. 10(5), pages 1-19, May.
    12. Nasirov, Shahriyar & Agostini, Claudio A., 2018. "Mining experts' perspectives on the determinants of solar technologies adoption in the Chilean mining industry," Renewable and Sustainable Energy Reviews, Elsevier, vol. 95(C), pages 194-202.
    13. Zhihai Yang & Dong Wang & Tianyi Du & Anlu Zhang & Yixiao Zhou, 2018. "Total-Factor Energy Efficiency in China’s Agricultural Sector: Trends, Disparities and Potentials," Energies, MDPI, vol. 11(4), pages 1-16, April.
    14. Tiba, Chigueru & de A. Beltrão, Ricardo E., 2012. "Siting PV plant focusing on the effect of local climate variables on electric energy production – Case study for Araripina and Recife," Renewable Energy, Elsevier, vol. 48(C), pages 309-317.
    15. Liqiang Duan & Zhen Wang, 2018. "Performance Study of a Novel Integrated Solar Combined Cycle System," Energies, MDPI, vol. 11(12), pages 1-22, December.
    16. Purohit, Ishan & Purohit, Pallav, 2018. "Performance assessment of grid-interactive solar photovoltaic projects under India’s national solar mission," Applied Energy, Elsevier, vol. 222(C), pages 25-41.
    17. Zou, Hongyang & Du, Huibin & Brown, Marilyn A. & Mao, Guozhu, 2017. "Large-scale PV power generation in China: A grid parity and techno-economic analysis," Energy, Elsevier, vol. 134(C), pages 256-268.
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    3. Liu, Jing & Huang, Fubin & Wang, Zihan & Shuai, Chuanmin, 2021. "What is the anti-poverty effect of solar PV poverty alleviation projects? Evidence from rural China," Energy, Elsevier, vol. 218(C).
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    6. Yongshi Jie & Xianhua Ji & Anzhi Yue & Jingbo Chen & Yupeng Deng & Jing Chen & Yi Zhang, 2020. "Combined Multi-Layer Feature Fusion and Edge Detection Method for Distributed Photovoltaic Power Station Identification," Energies, MDPI, vol. 13(24), pages 1-19, December.
    7. Xiaohua Song & Caiping Zhao & Jingjing Han & Qi Zhang & Jinpeng Liu & Yuanying Chi, 2020. "Measurement and Influencing Factors Research of the Energy and Power Efficiency in China: Based on the Supply-Side Structural Reform Perspective," Sustainability, MDPI, vol. 12(9), pages 1-23, May.
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    9. Wang, Zihan & Huang, Fubin & Liu, Jing & Shuai, Jing & Shuai, Chuanmin, 2020. "Does solar PV bring a sustainable future to the poor? -- an empirical study of anti-poverty policy effects on environmental sustainability in rural China," Energy Policy, Elsevier, vol. 145(C).

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