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Environment-adjusted operational performance evaluation of solar photovoltaic power plants: A three stage efficiency analysis

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  • Wang, Zhaohua
  • Li, Yi
  • Wang, Ke
  • Huang, Zhimin

Abstract

There is widespread concern that environmental factor may not be playing a pivotal role in influencing the generation performance of solar photovoltaic (PV) plants. The aim of this paper is to provide a fair and impartial operational performance evaluation of solar PV power plants taking into account of the impacts of environmental factors from real field data. Stochastic frontier analysis (SFA) is used to attribute the impacts of environmental factors (temperature, cloud amount, elevation, wind speed and precipitation) on inputs (like insolation and daylight hours) of solar PV power plants; while data envelopment analysis (DEA) is used to compute the environment-adjusted operational efficiency of these plants. SFA is utilized in the adjustment process for its merit of separating statistical noise from the error term, and DEA is used for its advantage of capturing the interaction among multiple inputs and outputs in a scalar value. The empirical analysis shows that the average operational efficiency of 70 grid-connected solar PV power plants in the United States slightly declines after accounting the impacts of environmental factors and statistical noise. Finally, the results partially support the initial concern from the statistical perspective and temperature is found to be the most significant influencing environmental factor, while precipitation and wind speed show no significant influence on operational efficiency. Therefore, the necessity of accounting for the impacts of environmental factors in the performance evaluation of solar PV power plants should not be omitted.

Suggested Citation

  • Wang, Zhaohua & Li, Yi & Wang, Ke & Huang, Zhimin, 2017. "Environment-adjusted operational performance evaluation of solar photovoltaic power plants: A three stage efficiency analysis," Renewable and Sustainable Energy Reviews, Elsevier, vol. 76(C), pages 1153-1162.
    • Handle: RePEc:eee:rensus:v:76:y:2017:i:c:p:1153-1162
    DOI: 10.1016/j.rser.2017.03.119
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    5. Zhang, Tiantian & Nakagawa, Kei & Matsumoto, Ken'ichi, 2023. "Evaluating solar photovoltaic power efficiency based on economic dimensions for 26 countries using a three-stage data envelopment analysis," Applied Energy, Elsevier, vol. 335(C).
    6. Yu, Bolin & Fang, Debin & Meng, Jingxuan, 2021. "Analysis of the generation efficiency of disaggregated renewable energy and its spatial heterogeneity influencing factors: A case study of China," Energy, Elsevier, vol. 234(C).
    7. Jing Yang & Changhui Yang & Xiaojia Wang & Manli Cheng & Jingjing Shang, 2020. "Efficiency Measurement and Factor Analysis of China’s Solar Photovoltaic Power Generation Considering Regional Differences Based on a FAHP–DEA Model," Energies, MDPI, vol. 13(8), pages 1-26, April.
    8. Chen, Xin & Zhou, Wenjia, 2023. "Performance evaluation of aquavoltaics in China: Retrospect and prospect," Renewable and Sustainable Energy Reviews, Elsevier, vol. 173(C).
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    13. Santos, Marllen & González, Mario, 2019. "Factors that influence the performance of wind farms," Renewable Energy, Elsevier, vol. 135(C), pages 643-651.
    14. Li, Jiaxin & Peng, Jiachao & Shuai, Chuanmin & Wang, Zihan & Huang, Fubin & Khayyam, Muhammad, 2022. "Does the solar PV program enhance the social empowerment of China's rural poor?," Energy, Elsevier, vol. 253(C).
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    17. Ronewa Collen Nemalili & Lordwell Jhamba & Joseph Kiprono Kirui & Caston Sigauke, 2023. "Nowcasting Hourly-Averaged Tilt Angles of Acceptance for Solar Collector Applications Using Machine Learning Models," Energies, MDPI, vol. 16(2), pages 1-19, January.

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    More about this item

    Keywords

    Solar PV power plants; Environmental factors; Data envelopment analysis; Slacks; Stochastic frontier analysis;
    All these keywords.

    JEL classification:

    • Q54 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Climate; Natural Disasters and their Management; Global Warming
    • Q40 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - General

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