IDEAS home Printed from https://ideas.repec.org/a/eee/appene/v254y2019ics0306261919314448.html
   My bibliography  Save this article

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

Author

Listed:
  • 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
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0306261919314448
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.apenergy.2019.113757?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. 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.
    2. 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.
    3. 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.
    4. 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.
    5. 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.
    6. 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.
    7. 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.
    8. 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.
    9. 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.
    10. 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.
    11. 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.
    12. 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.
    13. 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.
    14. 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.
    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. 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.
    17. 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.
    18. 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.
    19. 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.
    20. 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.
    21. 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.
    22. Lin, Boqiang & Wu, Wei, 2017. "Cost of long distance electricity transmission in China," Energy Policy, Elsevier, vol. 109(C), pages 132-140.
    23. 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.
    24. 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.
    25. 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.
    26. 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.
    27. 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.
    28. 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.
    29. 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.
    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.
    Full references (including those not matched with items on IDEAS)

    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. 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.
    2. Tang, Bao-Jun & Li, Ru & Li, Xiao-Yi & Chen, Hao, 2017. "An optimal production planning model of coal-fired power industry in China: Considering the process of closing down inefficient units and developing CCS technologies," Applied Energy, Elsevier, vol. 206(C), pages 519-530.
    3. Fitiwi, Desta & Lynch, Muireann Á. & Bertsch, Valentin, 2019. "Optimal development of electricity generation mix considering fossil fuel phase-out and strategic multi-area interconnection," Papers WP616, Economic and Social Research Institute (ESRI).
    4. Østergaard, P.A. & Lund, H. & Thellufsen, J.Z. & Sorknæs, P. & Mathiesen, B.V., 2022. "Review and validation of EnergyPLAN," Renewable and Sustainable Energy Reviews, Elsevier, vol. 168(C).
    5. Cui, Qi & He, Ling & Han, Guoyi & Chen, Hao & Cao, Juanjuan, 2020. "Review on climate and water resource implications of reducing renewable power curtailment in China: A nexus perspective," Applied Energy, Elsevier, vol. 267(C).
    6. Afful-Dadzie, Anthony & Afful-Dadzie, Eric & Awudu, Iddrisu & Banuro, Joseph Kwaku, 2017. "Power generation capacity planning under budget constraint in developing countries," Applied Energy, Elsevier, vol. 188(C), pages 71-82.
    7. Constantino Dário Justo & José Eduardo Tafula & Pedro Moura, 2022. "Planning Sustainable Energy Systems in the Southern African Development Community: A Review of Power Systems Planning Approaches," Energies, MDPI, vol. 15(21), pages 1-28, October.
    8. Koltsaklis, Nikolaos E. & Dagoumas, Athanasios S., 2018. "State-of-the-art generation expansion planning: A review," Applied Energy, Elsevier, vol. 230(C), pages 563-589.
    9. Chen, Siyuan & Liu, Pei & Li, Zheng, 2019. "Multi-regional power generation expansion planning with air pollutants emission constraints," Renewable and Sustainable Energy Reviews, Elsevier, vol. 112(C), pages 382-394.
    10. Chandra Ade Irawan & Peter S. Hofman & Hing Kai Chan & Antony Paulraj, 2022. "A stochastic programming model for an energy planning problem: formulation, solution method and application," Annals of Operations Research, Springer, vol. 311(2), pages 695-730, April.
    11. Peng Wang & Chunsheng Wang & Yukun Hu & Liz Varga & Wei Wang, 2018. "Power Generation Expansion Optimization Model Considering Multi-Scenario Electricity Demand Constraints: A Case Study of Zhejiang Province, China," Energies, MDPI, vol. 11(6), pages 1-15, June.
    12. Liang, Yuanyuan & Yu, Biying & Wang, Lu, 2019. "Costs and benefits of renewable energy development in China's power industry," Renewable Energy, Elsevier, vol. 131(C), pages 700-712.
    13. Tong Koecklin, Manuel & Fitiwi, Desta & de Carolis, Joseph F. & Curtis, John, 2020. "Renewable electricity generation and transmission network developments in light of public opposition: Insights from Ireland," Papers WP653, Economic and Social Research Institute (ESRI).
    14. Zhang, Ning & Hu, Zhaoguang & Shen, Bo & Dang, Shuping & Zhang, Jian & Zhou, Yuhui, 2016. "A source–grid–load coordinated power planning model considering the integration of wind power generation," Applied Energy, Elsevier, vol. 168(C), pages 13-24.
    15. Guangxiao Hu & Xiaoming Ma & Junping Ji, 2017. "A Stochastic Optimization Model for Carbon Mitigation Path under Demand Uncertainty of the Power Sector in Shenzhen, China," Sustainability, MDPI, vol. 9(11), pages 1-12, October.
    16. Oree, Vishwamitra & Sayed Hassen, Sayed Z. & Fleming, Peter J., 2019. "A multi-objective framework for long-term generation expansion planning with variable renewables," Applied Energy, Elsevier, vol. 253(C), pages 1-1.
    17. Zhang, Shuang & Zhao, Tao & Xie, Bai-Chen, 2018. "What is the optimal power generation mix of China? An empirical analysis using portfolio theory," Applied Energy, Elsevier, vol. 229(C), pages 522-536.
    18. Pratama, Yoga Wienda & Purwanto, Widodo Wahyu & Tezuka, Tetsuo & McLellan, Benjamin Craig & Hartono, Djoni & Hidayatno, Akhmad & Daud, Yunus, 2017. "Multi-objective optimization of a multiregional electricity system in an archipelagic state: The role of renewable energy in energy system sustainability," Renewable and Sustainable Energy Reviews, Elsevier, vol. 77(C), pages 423-439.
    19. Wang, Hongye & Su, Bin & Mu, Hailin & Li, Nan & Jiang, Bo & Kong, Xue, 2019. "Optimization of electricity generation and interprovincial trading strategies in Southern China," Energy, Elsevier, vol. 174(C), pages 696-707.
    20. Fitiwi, Desta Z. & Lynch, Muireann & Bertsch, Valentin, 2020. "Enhanced network effects and stochastic modelling in generation expansion planning: Insights from an insular power system," Socio-Economic Planning Sciences, Elsevier, vol. 71(C).

    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:eee:appene:v:254:y:2019:i:c:s0306261919314448. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/405891/description#description .

    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.