IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v14y2021i7p1814-d523548.html
   My bibliography  Save this article

Grid Parity Analysis of China’s Centralized Photovoltaic Generation under Multiple Uncertainties

Author

Listed:
  • Libo Zhang

    (College of Economics and Management, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, China
    Research Centre for Soft Energy Science, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, China)

  • Qian Du

    (College of Economics and Management, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, China
    Research Centre for Soft Energy Science, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, China)

  • Dequn Zhou

    (College of Economics and Management, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, China
    Research Centre for Soft Energy Science, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, China)

Abstract

The cost of centralized photovoltaic (CPV) power generation has been decreasing rapidly in China. However, the achievement of grid parity is full of uncertainties due to changes in policies and the industry environment. In order to explore the time, price, and external conditions in which grid parity can be achieved, we create the improved grey GM (1, 1) model to estimate the installed capacity over the next 10 years, and apply a learning curve to predict the cost of CPV generation. In the analysis of grid parity, we compare the benchmark price of coal power and the price under the market-oriented mechanism with CPV. The results show that China’s CPV industry will enter the early stage of maturity from 2020 onwards; with the help of benchmark investment, the grid parity of CPV may be achieved in 2022 at the earliest and 2025 at the latest. After 2025, the photovoltaic electricity price will be generally lower than the coal electricity price under marketization. By 2030, CPV power generation costs will reach US $0.05/kWh, the accumulative installed capacity will exceed 370 GW, and the uncertainties will lead to a cumulative installed gap of nearly 100 GW.

Suggested Citation

  • Libo Zhang & Qian Du & Dequn Zhou, 2021. "Grid Parity Analysis of China’s Centralized Photovoltaic Generation under Multiple Uncertainties," Energies, MDPI, vol. 14(7), pages 1-19, March.
    • Handle: RePEc:gam:jeners:v:14:y:2021:i:7:p:1814-:d:523548
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/14/7/1814/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/14/7/1814/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. García-Álvarez, María Teresa & Cabeza-García, Laura & Soares, Isabel, 2017. "Analysis of the promotion of onshore wind energy in the EU: Feed-in tariff or renewable portfolio standard?," Renewable Energy, Elsevier, vol. 111(C), pages 256-264.
    2. Jinyue Yan & Ying Yang & Pietro Elia Campana & Jijiang He, 2019. "City-level analysis of subsidy-free solar photovoltaic electricity price, profits and grid parity in China," Nature Energy, Nature, vol. 4(8), pages 709-717, August.
    3. Pineda, Salvador & Bock, Andreas, 2016. "Renewable-based generation expansion under a green certificate market," Renewable Energy, Elsevier, vol. 91(C), pages 53-63.
    4. Wand, Robert & Leuthold, Florian, 2011. "Feed-in tariffs for photovoltaics: Learning by doing in Germany?," Applied Energy, Elsevier, vol. 88(12), pages 4387-4399.
    5. Özdemir, Özge & Hobbs, Benjamin F. & van Hout, Marit & Koutstaal, Paul R., 2020. "Capacity vs energy subsidies for promoting renewable investment: Benefits and costs for the EU power market," Energy Policy, Elsevier, vol. 137(C).
    6. Reindl, K. & Palm, J., 2021. "Installing PV: Barriers and enablers experienced by non-residential property owners," Renewable and Sustainable Energy Reviews, Elsevier, vol. 141(C).
    7. Zhang, Minhui & Zhang, Qin, 2020. "Grid parity analysis of distributed photovoltaic power generation in China," Energy, Elsevier, vol. 206(C).
    8. Ahmad, Salman & Tahar, Razman Mat & Muhammad-Sukki, Firdaus & Munir, Abu Bakar & Rahim, Ruzairi Abdul, 2015. "Role of feed-in tariff policy in promoting solar photovoltaic investments in Malaysia: A system dynamics approach," Energy, Elsevier, vol. 84(C), pages 808-815.
    9. Ding, Song & Hipel, Keith W. & Dang, Yao-guo, 2018. "Forecasting China's electricity consumption using a new grey prediction model," Energy, Elsevier, vol. 149(C), pages 314-328.
    10. Argote, L. & Epple, D., 1990. "Learning Curves In Manufacturing," GSIA Working Papers 89-90-02, Carnegie Mellon University, Tepper School of Business.
    11. Alberto Benato & Alarico Macor, 2019. "Italian Biogas Plants: Trend, Subsidies, Cost, Biogas Composition and Engine Emissions," Energies, MDPI, vol. 12(6), pages 1-31, March.
    12. Liu, Shiyu & Bie, Zhaohong & Lin, Jiang & Wang, Xifan, 2018. "Curtailment of renewable energy in Northwest China and market-based solutions," Energy Policy, Elsevier, vol. 123(C), pages 494-502.
    13. Ragwitz, Mario & Miola, Apollonia, 2005. "Evidence from RD&D spending for renewable energy sources in the EU," Renewable Energy, Elsevier, vol. 30(11), pages 1635-1647.
    14. Zheng, Cheng & Kammen, Daniel M., 2014. "An innovation-focused roadmap for a sustainable global photovoltaic industry," Energy Policy, Elsevier, vol. 67(C), pages 159-169.
    15. de La Tour, Arnaud & Glachant, Matthieu & Ménière, Yann, 2013. "Predicting the costs of photovoltaic solar modules in 2020 using experience curve models," Energy, Elsevier, vol. 62(C), pages 341-348.
    16. Baur, Lucia & Uriona M., Mauricio, 2018. "Diffusion of photovoltaic technology in Germany: A sustainable success or an illusion driven by guaranteed feed-in tariffs?," Energy, Elsevier, vol. 150(C), pages 289-298.
    17. Guo, Xiaodan & Guo, Xiaopeng, 2015. "China's photovoltaic power development under policy incentives: A system dynamics analysis," Energy, Elsevier, vol. 93(P1), pages 589-598.
    18. Sun, Peng & Nie, Pu-yan, 2015. "A comparative study of feed-in tariff and renewable portfolio standard policy in renewable energy industry," Renewable Energy, Elsevier, vol. 74(C), pages 255-262.
    19. Yu, C.F. & van Sark, W.G.J.H.M. & Alsema, E.A., 2011. "Unraveling the photovoltaic technology learning curve by incorporation of input price changes and scale effects," Renewable and Sustainable Energy Reviews, Elsevier, vol. 15(1), pages 324-337, January.
    20. Peters, Michael & Schneider, Malte & Griesshaber, Tobias & Hoffmann, Volker H., 2012. "The impact of technology-push and demand-pull policies on technical change – Does the locus of policies matter?," Research Policy, Elsevier, vol. 41(8), pages 1296-1308.
    21. Kim, Kyunam & Kim, Yeonbae, 2015. "Role of policy in innovation and international trade of renewable energy technology: Empirical study of solar PV and wind power technology," Renewable and Sustainable Energy Reviews, Elsevier, vol. 44(C), pages 717-727.
    22. Wei, Max & Smith, Sarah Josephine & Sohn, Michael D., 2017. "Non-constant learning rates in retrospective experience curve analyses and their correlation to deployment programs," Energy Policy, Elsevier, vol. 107(C), pages 356-369.
    23. Xin-gang Zhao & Yu-zhuo Zhang, 2018. "The System Dynamics (SD) Analysis of the Government and Power Producers’ Evolutionary Game Strategies Based on Carbon Trading (CT) Mechanism: A Case of China," Sustainability, MDPI, vol. 10(4), pages 1-18, April.
    24. Xin-gang, Zhao & Zhen, Wang, 2019. "Technology, cost, economic performance of distributed photovoltaic industry in China," Renewable and Sustainable Energy Reviews, Elsevier, vol. 110(C), pages 53-64.
    25. Wu, Wenqing & Ma, Xin & Zeng, Bo & Wang, Yong & Cai, Wei, 2019. "Forecasting short-term renewable energy consumption of China using a novel fractional nonlinear grey Bernoulli model," Renewable Energy, Elsevier, vol. 140(C), pages 70-87.
    26. Isoard, Stephane & Soria, Antonio, 2001. "Technical change dynamics: evidence from the emerging renewable energy technologies," Energy Economics, Elsevier, vol. 23(6), pages 619-636, November.
    27. Ding, H. & Zhou, D.Q. & Liu, G.Q. & Zhou, P., 2020. "Cost reduction or electricity penetration: Government R&D-induced PV development and future policy schemes," Renewable and Sustainable Energy Reviews, Elsevier, vol. 124(C).
    28. Castaneda, Monica & Zapata, Sebastian & Cherni, Judith & Aristizabal, Andres J. & Dyner, Isaac, 2020. "The long-term effects of cautious feed-in tariff reductions on photovoltaic generation in the UK residential sector," Renewable Energy, Elsevier, vol. 155(C), pages 1432-1443.
    29. Chul-Yong Lee & Jaekyun Ahn, 2020. "Stochastic Modeling of the Levelized Cost of Electricity for Solar PV," Energies, MDPI, vol. 13(11), pages 1-18, June.
    30. Alberto Benato & Anna Stoppato, 2019. "An Experimental Investigation of a Novel Low-Cost Photovoltaic Panel Active Cooling System," Energies, MDPI, vol. 12(8), pages 1-24, April.
    31. Leepa, Claudia & Unfried, Matthias, 2013. "Effects of a cut-off in feed-in tariffs on photovoltaic capacity: Evidence fromGermany," Energy Policy, Elsevier, vol. 56(C), pages 536-542.
    32. Xin-gang Zhao & Yu-zhuo Zhang & Yan-bin Li, 2018. "The Evolution of Renewable Energy Price Policies Based on Improved Bass Model: A System Dynamics (SD) Analysis," Sustainability, MDPI, vol. 10(6), pages 1-20, May.
    33. Fan, Jing-Li & Wang, Jia-Xing & Hu, Jia-Wei & Wang, Yu & Zhang, Xian, 2019. "Optimization of China’s provincial renewable energy installation plan for the 13th five-year plan based on renewable portfolio standards," Applied Energy, Elsevier, vol. 254(C).
    34. Dusonchet, L. & Telaretti, E., 2015. "Comparative economic analysis of support policies for solar PV in the most representative EU countries," Renewable and Sustainable Energy Reviews, Elsevier, vol. 42(C), pages 986-998.
    35. Liu, Cengceng & Li, Nan & Zha, Donglan, 2016. "On the impact of FIT policies on renewable energy investment: Based on the solar power support policies in China's power market," Renewable Energy, Elsevier, vol. 94(C), pages 251-267.
    36. Saad Ahmed Javed & Sifeng Liu, 2018. "Predicting the research output/growth of selected countries: application of Even GM (1, 1) and NDGM models," Scientometrics, Springer;Akadémiai Kiadó, vol. 115(1), pages 395-413, April.
    37. Yuzhuo Zhang & Xingang Zhao & Yi Zuo & Lingzhi Ren & Ling Wang, 2017. "The Development of the Renewable Energy Power Industry under Feed-In Tariff and Renewable Portfolio Standard: A Case Study of China’s Photovoltaic Power Industry," Sustainability, MDPI, vol. 9(4), pages 1-23, March.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Ludwik Wicki & Robert Pietrzykowski & Dariusz Kusz, 2022. "Factors Determining the Development of Prosumer Photovoltaic Installations in Poland," Energies, MDPI, vol. 15(16), pages 1-19, August.
    2. Wang, Rong & Hasanefendic, Sandra & Von Hauff, Elizabeth & Bossink, Bart, 2022. "The cost of photovoltaics: Re-evaluating grid parity for PV systems in China," Renewable Energy, Elsevier, vol. 194(C), pages 469-481.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Zhang, Libo & Chen, Changqi & Wang, Qunwei & Zhou, Dequn, 2021. "The impact of feed-in tariff reduction and renewable portfolio standard on the development of distributed photovoltaic generation in China," Energy, Elsevier, vol. 232(C).
    2. Ding, H. & Zhou, D.Q. & Liu, G.Q. & Zhou, P., 2020. "Cost reduction or electricity penetration: Government R&D-induced PV development and future policy schemes," Renewable and Sustainable Energy Reviews, Elsevier, vol. 124(C).
    3. Hong, Soonpa & Yang, Taeyong & Chang, Hyun Joon & Hong, Sungjun, 2020. "The effect of switching renewable energy support systems on grid parity for photovoltaics: Analysis using a learning curve model," Energy Policy, Elsevier, vol. 138(C).
    4. Gan, Peck Yean & Li, ZhiDong, 2015. "Quantitative study on long term global solar photovoltaic market," Renewable and Sustainable Energy Reviews, Elsevier, vol. 46(C), pages 88-99.
    5. Wang, Rong & Hasanefendic, Sandra & Von Hauff, Elizabeth & Bossink, Bart, 2022. "The cost of photovoltaics: Re-evaluating grid parity for PV systems in China," Renewable Energy, Elsevier, vol. 194(C), pages 469-481.
    6. Dong, Zhuojia & Yu, Xianyu & Chang, Ching-Ter & Zhou, Dequn & Sang, Xiuzhi, 2022. "How does feed-in tariff and renewable portfolio standard evolve synergistically? An integrated approach of tripartite evolutionary game and system dynamics," Renewable Energy, Elsevier, vol. 186(C), pages 864-877.
    7. Xin-gang, Zhao & Wei, Wang & Ling, Wu, 2021. "A dynamic analysis of research and development incentive on China's photovoltaic industry based on system dynamics model," Energy, Elsevier, vol. 233(C).
    8. Nuñez-Jimenez, Alejandro & Knoeri, Christof & Rottmann, Fabian & Hoffmann, Volker H., 2020. "The role of responsiveness in deployment policies: A quantitative, cross-country assessment using agent-based modelling," Applied Energy, Elsevier, vol. 275(C).
    9. Lafond, François & Bailey, Aimee Gotway & Bakker, Jan David & Rebois, Dylan & Zadourian, Rubina & McSharry, Patrick & Farmer, J. Doyne, 2018. "How well do experience curves predict technological progress? A method for making distributional forecasts," Technological Forecasting and Social Change, Elsevier, vol. 128(C), pages 104-117.
    10. Grafström, Jonas & Poudineh, Rahmat, 2023. "No evidence of counteracting policy effects on European solar power invention and diffusion," Energy Policy, Elsevier, vol. 172(C).
    11. Samadi, Sascha, 2018. "The experience curve theory and its application in the field of electricity generation technologies – A literature review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 82(P3), pages 2346-2364.
    12. Xu, Jie & Lv, Tao & Hou, Xiaoran & Deng, Xu & Liu, Feng, 2021. "Provincial allocation of renewable portfolio standard in China based on efficiency and fairness principles," Renewable Energy, Elsevier, vol. 179(C), pages 1233-1245.
    13. Nuñez-Jimenez, Alejandro & Knoeri, Christof & Hoppmann, Joern & Hoffmann, Volker H., 2022. "Beyond innovation and deployment: Modeling the impact of technology-push and demand-pull policies in Germany's solar policy mix," Research Policy, Elsevier, vol. 51(10).
    14. Hengtian Wang & Xiaolong Yang & Xinxin Xu & Liu Fei, 2021. "Exploring Opportunities and Challenges of Solar PV Power under Carbon Peak Scenario in China: A PEST Analysis," Energies, MDPI, vol. 14(11), pages 1-28, May.
    15. Daniel Lugo-Laguna & Angel Arcos-Vargas & Fernando Nuñez-Hernandez, 2021. "A European Assessment of the Solar Energy Cost: Key Factors and Optimal Technology," Sustainability, MDPI, vol. 13(6), pages 1-25, March.
    16. Milad Mousavian, H. & Hamed Shakouri, G. & Mashayekhi, Ali-Naghi & Kazemi, Aliyeh, 2020. "Does the short-term boost of renewable energies guarantee their stable long-term growth? Assessment of the dynamics of feed-in tariff policy," Renewable Energy, Elsevier, vol. 159(C), pages 1252-1268.
    17. Wang, Bing & Wei, Yi-Ming & Yuan, Xiao-Chen, 2018. "Possible design with equity and responsibility in China’s renewable portfolio standards," Applied Energy, Elsevier, vol. 232(C), pages 685-694.
    18. Punda, Luka & Capuder, Tomislav & Pandžić, Hrvoje & Delimar, Marko, 2017. "Integration of renewable energy sources in southeast Europe: A review of incentive mechanisms and feasibility of investments," Renewable and Sustainable Energy Reviews, Elsevier, vol. 71(C), pages 77-88.
    19. Shangjia Wang & Wenhui Zhao & Shuwen Fan & Lei Xue & Zijuan Huang & Zhigang Liu, 2022. "Is the Renewable Portfolio Standard in China Effective? Research on RPS Allocation Efficiency in Chinese Provinces Based on the Zero-Sum DEA Model," Energies, MDPI, vol. 15(11), pages 1-18, May.
    20. Kyunam Kim & Eunnyeong Heo & Yeonbae Kim, 2017. "Dynamic Policy Impacts on a Technological-Change System of Renewable Energy: An Empirical Analysis," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 66(2), pages 205-236, February.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jeners:v:14:y:2021:i:7:p:1814-:d:523548. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.