IDEAS home Printed from https://ideas.repec.org/a/eee/rensus/v135y2021ics1364032120307267.html
   My bibliography  Save this article

Carbon-subsidized inter-regional electric power system planning under cost-risk tradeoff and uncertainty: A case study of Inner Mongolia, China

Author

Listed:
  • Yin, J.N.
  • Huang, G.H.
  • Xie, Y.L.
  • An, Y.K.

Abstract

Inter-regional electricity transmission inevitably brings about unbalanced carbon emission and air pollution among different regions. It is vital to compensate for the economic and environmental loss of power output region by taking the carbon subsidy strategy into account. In this study, a risk explicit interval multistage stochastic programming model considering inter-regional carbon subsidy is developed to support an optimal energy system planning in Inner Mongolia, China. This model can not only deal with uncertainties embedded in the complex energy system described as interval values and random variables but also reflect dynamic linkage between multiple stages over a time series. It advanced the existing optimization methods by introducing the cost-risk tradeoff information based on the risk preferences of decision-makers. The obtained crisp solutions are more feasible, effective and optimum for the practical policymaking process. Different scenarios associated with carbon subsidy policy implementation, renewable energy share adjustment and carbon emission reduction strategy are employed to project the optimal power generation scheme, net system cost, installed electricity capacity, carbon intensity and pollution emission in the future. The results indicate that the amount of exported electricity will keep increasing, and the carbon subsidy strategy will prominently promote the economic growth of the electric power sector by 3.05%. The further power supply pattern is going to transform from fossil fuel to renewable energy, by which wind and solar power will occupy around 44% of total power generation capacity in West Inner Mongolia. Raising the share of renewable energy will be the most effective approach to adjust the power generation scheme; meanwhile, reducing carbon intensity will significantly contribute to enlarge green energy capacity, enhance low-carbon emission and mitigate air pollution. These findings will help decision-makers gain insights into a more scientific energy system planning under various uncertainties.

Suggested Citation

  • Yin, J.N. & Huang, G.H. & Xie, Y.L. & An, Y.K., 2021. "Carbon-subsidized inter-regional electric power system planning under cost-risk tradeoff and uncertainty: A case study of Inner Mongolia, China," Renewable and Sustainable Energy Reviews, Elsevier, vol. 135(C).
    • Handle: RePEc:eee:rensus:v:135:y:2021:i:c:s1364032120307267
    DOI: 10.1016/j.rser.2020.110439
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S1364032120307267
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.rser.2020.110439?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. Ming, Zeng & Lilin, Peng & Qiannan, Fan & Yingjie, Zhang, 2016. "Trans-regional electricity transmission in China: Status, issues and strategies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 66(C), pages 572-583.
    2. Xie, Y.L. & Xia, D.H. & Ji, L. & Zhou, W.N. & Huang, G.H., 2017. "An inexact cost-risk balanced model for regional energy structure adjustment management and resources environmental effect analysis-a case study of Shandong province, China," Energy, Elsevier, vol. 126(C), pages 374-391.
    3. Xin, Li & Feng, Kuishuang & Siu, Yim Ling & Hubacek, Klaus, 2015. "Challenges faced when energy meets water: CO2 and water implications of power generation in inner Mongolia of China," Renewable and Sustainable Energy Reviews, Elsevier, vol. 45(C), pages 419-430.
    4. Lin, Boqiang & Wu, Wei, 2017. "Cost of long distance electricity transmission in China," Energy Policy, Elsevier, vol. 109(C), pages 132-140.
    5. 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.
    6. Zhai, Mengyu & Huang, Guohe & Liu, Lirong & Zheng, Boyue & Guan, Yuru, 2020. "Inter-regional carbon flows embodied in electricity transmission: network simulation for energy-carbon nexus," Renewable and Sustainable Energy Reviews, Elsevier, vol. 118(C).
    7. Chen, C. & Li, Y.P. & Huang, G.H., 2013. "An inexact robust optimization method for supporting carbon dioxide emissions management in regional electric-power systems," Energy Economics, Elsevier, vol. 40(C), pages 441-456.
    8. Yi, Bo-Wen & Xu, Jin-Hua & Fan, Ying, 2016. "Inter-regional power grid planning up to 2030 in China considering renewable energy development and regional pollutant control: A multi-region bottom-up optimization model," Applied Energy, Elsevier, vol. 184(C), pages 641-658.
    9. Zeng, Bo & Zeng, Ming & Xue, Song & Cheng, Min & Wang, Yuejin & Feng, Junjie, 2014. "Overall review of wind power development in Inner Mongolia: Status quo, barriers and solutions," Renewable and Sustainable Energy Reviews, Elsevier, vol. 29(C), pages 614-624.
    10. Xie, Y.L. & Huang, G.H. & Li, W. & Ji, L., 2014. "Carbon and air pollutants constrained energy planning for clean power generation with a robust optimization model—A case study of Jining City, China," Applied Energy, Elsevier, vol. 136(C), pages 150-167.
    11. Zhu, Y. & Li, Y.P. & Huang, G.H., 2013. "Planning carbon emission trading for Beijing's electric power systems under dual uncertainties," Renewable and Sustainable Energy Reviews, Elsevier, vol. 23(C), pages 113-128.
    12. Chen, F. & Huang, G.H. & Fan, Y.R. & Chen, J.P., 2017. "A copula-based fuzzy chance-constrained programming model and its application to electric power generation systems planning," Applied Energy, Elsevier, vol. 187(C), pages 291-309.
    13. Ji, Ling & Huang, Guo-He & Xie, Yu-Lei & Niu, Dong-Xiao & Song, Yi-Hang, 2017. "Explicit cost-risk tradeoff for renewable portfolio standard constrained regional power system expansion: A case study of Guangdong Province, China," Energy, Elsevier, vol. 131(C), pages 125-136.
    14. Ji, Ling & Zhang, Bei-Bei & Huang, Guo-He & Xie, Yu-Lei & Niu, Dong-Xiao, 2018. "Explicit cost-risk tradeoff for optimal energy management in CCHP microgrid system under fuzzy-risk preferences," Energy Economics, Elsevier, vol. 70(C), pages 525-535.
    15. Wu, C.B. & Huang, G.H. & Li, W. & Xie, Y.L. & Xu, Y., 2015. "Multistage stochastic inexact chance-constraint programming for an integrated biomass-municipal solid waste power supply management under uncertainty," Renewable and Sustainable Energy Reviews, Elsevier, vol. 41(C), pages 1244-1254.
    16. Yao, Yao & Huang, Gordon & An, Chunjiang & Chen, Xiujuan & Zhang, Peng & Xin, Xiaying & Jian Shen, & Agnew, Joy, 2020. "Anaerobic digestion of livestock manure in cold regions: Technological advancements and global impacts," Renewable and Sustainable Energy Reviews, Elsevier, vol. 119(C).
    17. Yu, L. & Li, Y.P. & Huang, G.H. & Fan, Y.R. & Yin, S., 2018. "Planning regional-scale electric power systems under uncertainty: A case study of Jing-Jin-Ji region, China," Applied Energy, Elsevier, vol. 212(C), pages 834-849.
    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. Kang, Jidong & Wu, Zhuochun & Ng, Tsan Sheng & Su, Bin, 2023. "A stochastic-robust optimization model for inter-regional power system planning," European Journal of Operational Research, Elsevier, vol. 310(3), pages 1234-1248.
    2. Tian, Chuyin & Huang, Guohe & Lu, Chen & Zhou, Xiong & Duan, Ruixin, 2021. "Development of enthalpy-based climate indicators for characterizing building cooling and heating energy demand under climate change," Renewable and Sustainable Energy Reviews, Elsevier, vol. 143(C).
    3. Zhang, Xiaoyue & Huang, Guohe & Xie, Yulei & Liu, Lirong & Song, Tangnyu, 2022. "A coupled non-deterministic optimization and mixed-level factorial analysis model for power generation expansion planning – A case study of Jing-Jin-Ji metropolitan region, China," Applied Energy, Elsevier, vol. 311(C).
    4. Zhang, Xiaoyue & Huang, Guohe & Liu, Lirong & Li, Kailong, 2022. "Development of a stochastic multistage lifecycle programming model for electric power system planning – A case study for the Province of Saskatchewan, Canada," Renewable and Sustainable Energy Reviews, Elsevier, vol. 158(C).
    5. Wang, Ni & Verzijlbergh, Remco A. & Heijnen, Petra W. & Herder, Paulien M., 2023. "Incorporating indirect costs into energy system optimization models: Application to the Dutch national program Regional Energy Strategies," Energy, Elsevier, vol. 276(C).
    6. Ma, Ning & Fan, Lurong, 2023. "Double recovery strategy of carbon for coal-to-power based on a multi-energy system with tradable green certificates," Energy, Elsevier, vol. 273(C).
    7. Saberi-Beglar, Kasra & Zare, Kazem & Seyedi, Heresh & Marzband, Mousa & Nojavan, Sayyad, 2023. "Risk-embedded scheduling of a CCHP integrated with electric vehicle parking lot in a residential energy hub considering flexible thermal and electrical loads," Applied Energy, Elsevier, vol. 329(C).
    8. Jixian Cui & Chenghao Liao & Ling Ji & Yulei Xie & Yangping Yu & Jianguang Yin, 2021. "A Short-Term Hybrid Energy System Robust Optimization Model for Regional Electric-Power Capacity Development Planning under Different Pollutant Control Pressures," Sustainability, MDPI, vol. 13(20), pages 1-20, October.
    9. Govindan, Kannan, 2023. "Pathways to low carbon energy transition through multi criteria assessment of offshore wind energy barriers," Technological Forecasting and Social Change, Elsevier, vol. 187(C).

    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. Liu, Hailiang & Brown, Tom & Andresen, Gorm Bruun & Schlachtberger, David P. & Greiner, Martin, 2019. "The role of hydro power, storage and transmission in the decarbonization of the Chinese power system," Applied Energy, Elsevier, vol. 239(C), pages 1308-1321.
    2. Yulei Xie & Linrui Wang & Guohe Huang & Dehong Xia & Ling Ji, 2018. "A Stochastic Inexact Robust Model for Regional Energy System Management and Emission Reduction Potential Analysis—A Case Study of Zibo City, China," Energies, MDPI, vol. 11(8), pages 1-24, August.
    3. 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.
    4. Hailin Mu & Zhewen Pei & Hongye Wang & Nan Li & Ye Duan, 2022. "Optimal Strategy for Low-Carbon Development of Power Industry in Northeast China Considering the ‘Dual Carbon’ Goal," Energies, MDPI, vol. 15(17), pages 1-22, September.
    5. 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.
    6. Cao, R. & Huang, G.H. & Chen, J.P. & Li, Y.P. & He, C.Y., 2021. "A chance-constrained urban agglomeration energy model for cooperative carbon emission management," Energy, Elsevier, vol. 223(C).
    7. Chen, C. & Li, Y.P. & Huang, G.H., 2016. "Interval-fuzzy municipal-scale energy model for identification of optimal strategies for energy management – A case study of Tianjin, China," Renewable Energy, Elsevier, vol. 86(C), pages 1161-1177.
    8. Ji, Ling & Zhang, Bei-Bei & Huang, Guo-He & Xie, Yu-Lei & Niu, Dong-Xiao, 2018. "Explicit cost-risk tradeoff for optimal energy management in CCHP microgrid system under fuzzy-risk preferences," Energy Economics, Elsevier, vol. 70(C), pages 525-535.
    9. Zhai, Mengyu & Huang, Guohe & Liu, Lirong & Guo, Zhengquan & Su, Shuai, 2021. "Segmented carbon tax may significantly affect the regional and national economy and environment-a CGE-based analysis for Guangdong Province," Energy, Elsevier, vol. 231(C).
    10. Nie, Yan & Zhang, Guoxing & Duan, Hongbo, 2020. "An interconnected panorama of future cross-regional power grid: A complex network approach," Resources Policy, Elsevier, vol. 67(C).
    11. Ji, Ling & Zhang, Beibei & Huang, Guohe & Wang, Peng, 2020. "A novel multi-stage fuzzy stochastic programming for electricity system structure optimization and planning with energy-water nexus - A case study of Tianjin, China," Energy, Elsevier, vol. 190(C).
    12. Yu, L. & Li, Y.P. & Huang, G.H. & Fan, Y.R. & Yin, S., 2018. "Planning regional-scale electric power systems under uncertainty: A case study of Jing-Jin-Ji region, China," Applied Energy, Elsevier, vol. 212(C), pages 834-849.
    13. Xu, Jiuping & Yang, Xin & Tao, Zhimiao, 2015. "A tripartite equilibrium for carbon emission allowance allocation in the power-supply industry," Energy Policy, Elsevier, vol. 82(C), pages 62-80.
    14. Zhang, Shenxi & Cheng, Haozhong & Li, Ke & Tai, Nengling & Wang, Dan & Li, Furong, 2018. "Multi-objective distributed generation planning in distribution network considering correlations among uncertainties," Applied Energy, Elsevier, vol. 226(C), pages 743-755.
    15. Lu, W.T. & Dai, C. & Fu, Z.H. & Liang, Z.Y. & Guo, H.C., 2018. "An interval-fuzzy possibilistic programming model to optimize China energy management system with CO2 emission constraint," Energy, Elsevier, vol. 142(C), pages 1023-1039.
    16. Shuangshuang Zhou & Juan Yang & Shiwei Yu, 2022. "A Stochastic Multi-Objective Model for China’s Provincial Generation-Mix Planning: Considering Variable Renewable and Transmission Capacity," Energies, MDPI, vol. 15(8), pages 1-26, April.
    17. Xiao Zhao & Xuhui Xia & Guodong Yu, 2019. "Primal-Dual Learning Based Risk-Averse Optimal Integrated Allocation of Hybrid Energy Generation Plants under Uncertainty," Energies, MDPI, vol. 12(12), pages 1-15, June.
    18. Deng, Xu & Lv, Tao & Xu, Jie & Hou, Xiaoran & Liu, Feng, 2022. "Assessing the integration effect of inter-regional transmission on variable power generation under renewable energy consumption policy in China," Energy Policy, Elsevier, vol. 170(C).
    19. Khishtandar, Soheila, 2019. "Simulation based evolutionary algorithms for fuzzy chance-constrained biogas supply chain design," Applied Energy, Elsevier, vol. 236(C), pages 183-195.
    20. Zhang, Qiang & Chen, Wenying, 2020. "Modeling China’s interprovincial electricity transmission under low carbon transition," Applied Energy, Elsevier, vol. 279(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:rensus:v:135:y:2021:i:c:s1364032120307267. 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/600126/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.