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Optimization of China’s provincial renewable energy installation plan for the 13th five-year plan based on renewable portfolio standards

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  • Fan, Jing-Li
  • Wang, Jia-Xing
  • Hu, Jia-Wei
  • Wang, Yu
  • Zhang, Xian

Abstract

Renewable energy (RE) in China has developed rapidly in recent years. Due to an overly aggressive RE installation plan, the country now faces the issue of RE power curtailment. Based on the newly proposed provincial renewable portfolio standards for 2020, an integrated planning model composed of a multi-regression model and linear planning model was established to optimize the RE power installation plan for each province in 2020. The results show that after optimization using the integrated model, nearly 400 TWh of excess RE power (including about 300 TWh of non-hydropower) will be saved. Guangdong, Shanghai, and Jiangsu are the main hydropower transfer provinces, whereas Beijing, Tianjin, Henan, Zhejiang, and Jiangsu are the principal non-hydropower transfer provinces. The research results also show that the newly installed capacity of RE resource-rich areas such as Sichuan, Yunnan, Inner Mongolia, and Xinjiang will account for less than 20% of the existing installed capacity according to China’s current plan. In the future, these provinces must make full use of the power generation capacities of existing installed RE sources. The optimization of RE resource allocation is promoted in this study through the inter-provincial allocation of RE power and the combination of the renewable portfolio standards and the green certificate trading system.

Suggested Citation

  • 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).
    • Handle: RePEc:eee:appene:v:254:y:2019:i:c:s0306261919314448
    DOI: 10.1016/j.apenergy.2019.113757
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    1. Moura, Pedro S. & de Almeida, Aníbal T., 2010. "Multi-objective optimization of a mixed renewable system with demand-side management," Renewable and Sustainable Energy Reviews, Elsevier, vol. 14(5), pages 1461-1468, June.
    2. Chen, Hao & Tang, Bao-Jun & Liao, Hua & Wei, Yi-Ming, 2016. "A multi-period power generation planning model incorporating the non-carbon external costs: A case study of China," Applied Energy, Elsevier, vol. 183(C), pages 1333-1345.
    3. Thellufsen, Jakob Zinck & Lund, Henrik, 2016. "Roles of local and national energy systems in the integration of renewable energy," Applied Energy, Elsevier, vol. 183(C), pages 419-429.
    4. Rentizelas, Athanasios & Georgakellos, Dimitrios, 2014. "Incorporating life cycle external cost in optimization of the electricity generation mix," Energy Policy, Elsevier, vol. 65(C), pages 134-149.
    5. Hong, Lixuan & Zhou, Nan & Fridley, David & Raczkowski, Chris, 2013. "Assessment of China's renewable energy contribution during the 12th Five Year Plan," Energy Policy, Elsevier, vol. 62(C), pages 1533-1543.
    6. Madlener, Reinhard & Kumbaroglu, Gurkan & Ediger, Volkan S., 2005. "Modeling technology adoption as an irreversible investment under uncertainty: the case of the Turkish electricity supply industry," Energy Economics, Elsevier, vol. 27(1), pages 139-163, January.
    7. Abdin, Islam F. & Zio, Enrico, 2018. "An integrated framework for operational flexibility assessment in multi-period power system planning with renewable energy production," Applied Energy, Elsevier, vol. 222(C), pages 898-914.
    8. Zhou, Y. & Li, Y.P. & Huang, G.H., 2015. "Planning sustainable electric-power system with carbon emission abatement through CDM under uncertainty," Applied Energy, Elsevier, vol. 140(C), pages 350-364.
    9. Koltsaklis, Nikolaos E. & Georgiadis, Michael C., 2015. "A multi-period, multi-regional generation expansion planning model incorporating unit commitment constraints," Applied Energy, Elsevier, vol. 158(C), pages 310-331.
    10. Gitizadeh, Mohsen & Kaji, Mahdi & Aghaei, Jamshid, 2013. "Risk based multiobjective generation expansion planning considering renewable energy sources," Energy, Elsevier, vol. 50(C), pages 74-82.
    11. Wang, Sarah & Tarroja, Brian & Schell, Lori Smith & Shaffer, Brendan & Samuelsen, Scott, 2019. "Prioritizing among the end uses of excess renewable energy for cost-effective greenhouse gas emission reductions," Applied Energy, Elsevier, vol. 235(C), pages 284-298.
    12. Khanna, Nina & Fridley, David & Zhou, Nan & Karali, Nihan & Zhang, Jingjing & Feng, Wei, 2019. "Energy and CO2 implications of decarbonization strategies for China beyond efficiency: Modeling 2050 maximum renewable resources and accelerated electrification impacts," Applied Energy, Elsevier, vol. 242(C), pages 12-26.
    13. Heinrich, G. & Howells, M. & Basson, L. & Petrie, J., 2007. "Electricity supply industry modelling for multiple objectives under demand growth uncertainty," Energy, Elsevier, vol. 32(11), pages 2210-2229.
    14. Zhou, Nan & Price, Lynn & Yande, Dai & Creyts, Jon & Khanna, Nina & Fridley, David & Lu, Hongyou & Feng, Wei & Liu, Xu & Hasanbeigi, Ali & Tian, Zhiyu & Yang, Hongwei & Bai, Quan & Zhu, Yuezhong & Xio, 2019. "A roadmap for China to peak carbon dioxide emissions and achieve a 20% share of non-fossil fuels in primary energy by 2030," Applied Energy, Elsevier, vol. 239(C), pages 793-819.
    15. Luz, Thiago & Moura, Pedro & de Almeida, Aníbal, 2018. "Multi-objective power generation expansion planning with high penetration of renewables," Renewable and Sustainable Energy Reviews, Elsevier, vol. 81(P2), pages 2637-2643.
    16. Lin, Boqiang & Wu, Wei, 2017. "Cost of long distance electricity transmission in China," Energy Policy, Elsevier, vol. 109(C), pages 132-140.
    17. Ioannou, Anastasia & Fuzuli, Gulistiani & Brennan, Feargal & Yudha, Satya Widya & Angus, Andrew, 2019. "Multi-stage stochastic optimization framework for power generation system planning integrating hybrid uncertainty modelling," Energy Economics, Elsevier, vol. 80(C), pages 760-776.
    18. Heuberger, Clara F. & Rubin, Edward S. & Staffell, Iain & Shah, Nilay & Mac Dowell, Niall, 2017. "Power capacity expansion planning considering endogenous technology cost learning," Applied Energy, Elsevier, vol. 204(C), pages 831-845.
    19. Hu, Kang & Chen, Lei & Chen, Qun & Wang, Xiao-Hai & Qi, Jun & Xu, Fei & Min, Yong, 2017. "Phase-change heat storage installation in combined heat and power plants for integration of renewable energy sources into power system," Energy, Elsevier, vol. 124(C), pages 640-651.
    20. Zhao, Zhen-Yu & Chen, Yu-Long & Chang, Rui-Dong, 2016. "How to stimulate renewable energy power generation effectively? – China's incentive approaches and lessons," Renewable Energy, Elsevier, vol. 92(C), pages 147-156.
    21. Gioutsos, Dean Marcus & Blok, Kornelis & van Velzen, Leonore & Moorman, Sjoerd, 2018. "Cost-optimal electricity systems with increasing renewable energy penetration for islands across the globe," Applied Energy, Elsevier, vol. 226(C), pages 437-449.
    22. Hansen, Kenneth & Mathiesen, Brian Vad & Skov, Iva Ridjan, 2019. "Full energy system transition towards 100% renewable energy in Germany in 2050," Renewable and Sustainable Energy Reviews, Elsevier, vol. 102(C), pages 1-13.
    23. Guo, Hongye & Chen, Qixin & Xia, Qing & Kang, Chongqing, 2018. "Market equilibrium analysis with high penetration of renewables and gas-fired generation: An empirical case of the Beijing-Tianjin-Tangshan power system," Applied Energy, Elsevier, vol. 227(C), pages 384-392.
    24. Delarue, Erik & De Jonghe, Cedric & Belmans, Ronnie & D'haeseleer, William, 2011. "Applying portfolio theory to the electricity sector: Energy versus power," Energy Economics, Elsevier, vol. 33(1), pages 12-23, January.
    25. Fang, Debin & Zhao, Chaoyang & Yu, Qian, 2018. "Government regulation of renewable energy generation and transmission in China’s electricity market," Renewable and Sustainable Energy Reviews, Elsevier, vol. 93(C), pages 775-793.
    26. Jenkins, J.D. & Zhou, Z. & Ponciroli, R. & Vilim, R.B. & Ganda, F. & de Sisternes, F. & Botterud, A., 2018. "The benefits of nuclear flexibility in power system operations with renewable energy," Applied Energy, Elsevier, vol. 222(C), pages 872-884.
    27. Koltsaklis, Nikolaos E. & Dagoumas, Athanasios S. & Kopanos, Georgios M. & Pistikopoulos, Efstratios N. & Georgiadis, Michael C., 2014. "A spatial multi-period long-term energy planning model: A case study of the Greek power system," Applied Energy, Elsevier, vol. 115(C), pages 456-482.
    28. Cai, Y.P. & Huang, G.H. & Yang, Z.F. & Tan, Q., 2009. "Identification of optimal strategies for energy management systems planning under multiple uncertainties," Applied Energy, Elsevier, vol. 86(4), pages 480-495, April.
    29. Esteban, Miguel & Portugal-Pereira, Joana & Mclellan, Benjamin C. & Bricker, Jeremy & Farzaneh, Hooman & Djalilova, Nigora & Ishihara, Keiichi N. & Takagi, Hiroshi & Roeber, Volker, 2018. "100% renewable energy system in Japan: Smoothening and ancillary services," Applied Energy, Elsevier, vol. 224(C), pages 698-707.
    30. Li, Xin & Chen, Hsing Hung & Tao, Xiangnan, 2016. "Pricing and capacity allocation in renewable energy," Applied Energy, Elsevier, vol. 179(C), pages 1097-1105.
    31. Cheng, Rui & Xu, Zhaofeng & Liu, Pei & Wang, Zhe & Li, Zheng & Jones, Ian, 2015. "A multi-region optimization planning model for China’s power sector," Applied Energy, Elsevier, vol. 137(C), pages 413-426.
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