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Are Regions Conducive to Photovoltaic Power Generation Demonstrating Significant Potential for Harnessing Solar Energy via Photovoltaic Systems?

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  • Jiayu Bao

    (Faculty of Land Resources Engineering, Kunming University of Science and Technology, Kunming 650093, China
    Key Laboratory of Ecological Safety and Sustainable Development in Arid Lands, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi 830011, China
    Advanced Blasting Technology Engineering Research Center of Yunnan Provincial Department of Education, Kunming 650093, China)

  • Xianglong Li

    (Faculty of Land Resources Engineering, Kunming University of Science and Technology, Kunming 650093, China
    Advanced Blasting Technology Engineering Research Center of Yunnan Provincial Department of Education, Kunming 650093, China)

  • Tao Yu

    (Key Laboratory of Ecological Safety and Sustainable Development in Arid Lands, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi 830011, China)

  • Liangliang Jiang

    (School of Geography and Tourism, Chongqing Normal University, Chongqing 401331, China)

  • Jialin Zhang

    (Faculty of Land Resources Engineering, Kunming University of Science and Technology, Kunming 650093, China)

  • Fengjiao Song

    (Key Laboratory of Ecological Safety and Sustainable Development in Arid Lands, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi 830011, China)

  • Wenqiang Xu

    (Key Laboratory of Ecological Safety and Sustainable Development in Arid Lands, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi 830011, China)

Abstract

To achieve the goals of carbon peak and carbon neutrality, Xinjiang, as an autonomous region in China with large energy reserves, should adjust its energy development and vigorously develop new energy sources, such as photovoltaic (PV) power. This study utilized data spatiotemporal variation in solar radiation from 1984 to 2016 to verify that Xinjiang is suitable for the development of PV power generation. Then, the averages of the solar radiation, sunshine duration, and other data in the period after 2000 were used to assess the suitability of Xinjiang, based on spatial principal component analysis (SPCA). Finally, the theoretical power generation potential, fossil fuel reduction, and CO 2 emissions reduction were estimated. The results are as follows: (1) In terms of temporal variation, the solar radiation in Xinjiang decreased (1984–2002), increased (2002–2009), and decreased again (2009–2016), but the fluctuations were not statistically significant. In terms of spatial distribution, the Kunlun Mountains in southern Xinjiang had the highest solar radiation during the span of the study period. Hami and Turpan, in eastern Xinjiang, had sufficiently high and stable solar radiation. (2) The area in Xinjiang classed as highly suitable for solar PV power generation is about 87,837 km 2 , which is mainly concentrated in eastern Xinjiang. (3) In the situation where the construction of PV power plants in Xinjiang is fully developed, the theoretical potential of annual solar PV power generation in Xinjiang is approximately 8.57 × 10 6 GWh. This is equivalent to 2.59 × 10 9 tce of coal. Furthermore, 6.58 × 10 9 t of CO 2 emissions can be reduced. PV power generation potential is approximately 27 times the energy consumption of Xinjiang in 2020. Through the suitability assessment and calculations, we found that Xinjiang has significant potential for PV systems.

Suggested Citation

  • Jiayu Bao & Xianglong Li & Tao Yu & Liangliang Jiang & Jialin Zhang & Fengjiao Song & Wenqiang Xu, 2024. "Are Regions Conducive to Photovoltaic Power Generation Demonstrating Significant Potential for Harnessing Solar Energy via Photovoltaic Systems?," Sustainability, MDPI, vol. 16(8), pages 1-19, April.
  • Handle: RePEc:gam:jsusta:v:16:y:2024:i:8:p:3281-:d:1375835
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    1. Madjid Tavana & Mehdi Soltanifar & Francisco J. Santos-Arteaga, 2023. "Analytical hierarchy process: revolution and evolution," Annals of Operations Research, Springer, vol. 326(2), pages 879-907, July.
    2. Gastli, Adel & Charabi, Yassine, 2010. "Solar electricity prospects in Oman using GIS-based solar radiation maps," Renewable and Sustainable Energy Reviews, Elsevier, vol. 14(2), pages 790-797, February.
    3. Perpiña Castillo, Carolina & Batista e Silva, Filipe & Lavalle, Carlo, 2016. "An assessment of the regional potential for solar power generation in EU-28," Energy Policy, Elsevier, vol. 88(C), pages 86-99.
    4. Yang, Qing & Huang, Tianyue & Wang, Saige & Li, Jiashuo & Dai, Shaoqing & Wright, Sebastian & Wang, Yuxuan & Peng, Huaiwu, 2019. "A GIS-based high spatial resolution assessment of large-scale PV generation potential in China," Applied Energy, Elsevier, vol. 247(C), pages 254-269.
    5. Desideri, U. & Zepparelli, F. & Morettini, V. & Garroni, E., 2013. "Comparative analysis of concentrating solar power and photovoltaic technologies: Technical and environmental evaluations," Applied Energy, Elsevier, vol. 102(C), pages 765-784.
    6. Liu, Jian & Cheng, Cheng & Yang, Xianglin & Yan, Lizhao & Lai, Yongzeng, 2019. "Analysis of the efficiency of Hong Kong REITs market based on Hurst exponent," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 534(C).
    7. Laibao Liu & Gang He & Mengxi Wu & Gang Liu & Haoran Zhang & Ying Chen & Jiashu Shen & Shuangcheng Li, 2023. "Climate change impacts on planned supply–demand match in global wind and solar energy systems," Nature Energy, Nature, vol. 8(8), pages 870-880, August.
    8. Clifton, Julian & Boruff, Bryan J., 2010. "Assessing the potential for concentrated solar power development in rural Australia," Energy Policy, Elsevier, vol. 38(9), pages 5272-5280, September.
    9. Alami Merrouni, Ahmed & Elwali Elalaoui, Fakhreddine & Mezrhab, Ahmed & Mezrhab, Abdelhamid & Ghennioui, Abdellatif, 2018. "Large scale PV sites selection by combining GIS and Analytical Hierarchy Process. Case study: Eastern Morocco," Renewable Energy, Elsevier, vol. 119(C), pages 863-873.
    10. Charabi, Yassine & Gastli, Adel, 2011. "PV site suitability analysis using GIS-based spatial fuzzy multi-criteria evaluation," Renewable Energy, Elsevier, vol. 36(9), pages 2554-2561.
    11. Zhixin Zhang & Min Chen & Teng Zhong & Rui Zhu & Zhen Qian & Fan Zhang & Yue Yang & Kai Zhang & Paolo Santi & Kaicun Wang & Yingxia Pu & Lixin Tian & Guonian Lü & Jinyue Yan, 2023. "Carbon mitigation potential afforded by rooftop photovoltaic in China," Nature Communications, Nature, vol. 14(1), pages 1-12, December.
    12. Sun, Yan-wei & Hof, Angela & Wang, Run & Liu, Jian & Lin, Yan-jie & Yang, De-wei, 2013. "GIS-based approach for potential analysis of solar PV generation at the regional scale: A case study of Fujian Province," Energy Policy, Elsevier, vol. 58(C), pages 248-259.
    13. Yijing Wang & Rong Wang & Katsumasa Tanaka & Philippe Ciais & Josep Penuelas & Yves Balkanski & Jordi Sardans & Didier Hauglustaine & Wang Liu & Xiaofan Xing & Jiarong Li & Siqing Xu & Yuankang Xiong , 2023. "Accelerating the energy transition towards photovoltaic and wind in China," Nature, Nature, vol. 619(7971), pages 761-767, July.
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