IDEAS home Printed from https://ideas.repec.org/a/eee/enepol/v158y2021ics0301421521004432.html
   My bibliography  Save this article

Multi-scenario simulation on the impact of China's electricity bidding policy based on complex networks model

Author

Listed:
  • Wang, Di
  • Zhang, Zhiyuan
  • Yang, Xiaodi
  • Zhang, Yanfang
  • Li, Yuman
  • Zhao, Yueying

Abstract

As one of the important measures for China's power system reform, the electricity bidding pricing (EBP) is helpful to realize the effective allocation of power resources. Based on price conduction theory and complex network modeling technology, we construct the price transmission network for the 76 economic sectors in China, identify the critical path of electricity price transmission, and empirically simulate and analyze the economic impact of EBP in different scenarios from the two aspects of whether the CEPL mechanism is implemented or not. The results indicate that the electricity price will be decreased directly by the EBP, and the electricity industry will significantly reduce the impact on other related industries. Particularly, affected by regulatory policies such as electricity price cap, the electricity price caused by EBP cannot be effectively transmitted to the upstream industries. Secondly, with the simultaneous implementation of the coal-electricity price linkage (CEPL) and the EBP, the coal-electricity price transmission will change from one-way conduction style to two-way interaction style, and the impact of electricity price fluctuations on its related industries will be more significant, while the comprehensive impact of the coal industry on its associated industries will be significantly reduced. Thirdly, there are obvious scenario differences in the impact of different intensity of EBP on the macro-economy. The results show that under the mechanism of CEPL, the EBP with 20% of the total power used for bidding pilot has minimal impact on the Chinese economy. Based on the above conclusions, we propose that China should scientifically determine the scale and the pilot regions of electricity bidding under the CEPL, develop more diversified bidding forms and improve more robust supervision system.

Suggested Citation

  • Wang, Di & Zhang, Zhiyuan & Yang, Xiaodi & Zhang, Yanfang & Li, Yuman & Zhao, Yueying, 2021. "Multi-scenario simulation on the impact of China's electricity bidding policy based on complex networks model," Energy Policy, Elsevier, vol. 158(C).
  • Handle: RePEc:eee:enepol:v:158:y:2021:i:c:s0301421521004432
    DOI: 10.1016/j.enpol.2021.112573
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0301421521004432
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.enpol.2021.112573?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. He, Y.X. & Zhang, S.L. & Yang, L.Y. & Wang, Y.J. & Wang, J., 2010. "Economic analysis of coal price-electricity price adjustment in China based on the CGE model," Energy Policy, Elsevier, vol. 38(11), pages 6629-6637, November.
    2. Wang, Minggang & Chen, Ying & Tian, Lixin & Jiang, Shumin & Tian, Zihao & Du, Ruijin, 2016. "Fluctuation behavior analysis of international crude oil and gasoline price based on complex network perspective," Applied Energy, Elsevier, vol. 175(C), pages 109-127.
    3. Mohammadi, Hassan, 2009. "Electricity prices and fuel costs: Long-run relations and short-run dynamics," Energy Economics, Elsevier, vol. 31(3), pages 503-509, May.
    4. Gao, Xiangyun & Fang, Wei & An, Feng & Wang, Yue, 2017. "Detecting method for crude oil price fluctuation mechanism under different periodic time series," Applied Energy, Elsevier, vol. 192(C), pages 201-212.
    5. Davatgaran, Vahid & Saniei, Mohsen & Mortazavi, Seyed Saeidollah, 2018. "Optimal bidding strategy for an energy hub in energy market," Energy, Elsevier, vol. 148(C), pages 482-493.
    6. Vilim, Michael & Botterud, Audun, 2014. "Wind power bidding in electricity markets with high wind penetration," Applied Energy, Elsevier, vol. 118(C), pages 141-155.
    7. Clemente, G.P. & Grassi, R., 2018. "Directed clustering in weighted networks: A new perspective," Chaos, Solitons & Fractals, Elsevier, vol. 107(C), pages 26-38.
    8. Hagfors, Lars Ivar & Bunn, Derek & Kristoffersen, Eline & Staver, Tiril Toftdahl & Westgaard, Sjur, 2016. "Modeling the UK electricity price distributions using quantile regression," Energy, Elsevier, vol. 102(C), pages 231-243.
    9. Li, Ji Feng & Wang, Xin & Zhang, Ya Xiong & Kou, Qin, 2014. "The economic impact of carbon pricing with regulated electricity prices in China—An application of a computable general equilibrium approach," Energy Policy, Elsevier, vol. 75(C), pages 46-56.
    10. Shi, Wenming & Wang, Ganggang & Zhao, Xu & Feng, Xuehao & Wu, Jun, 2018. "Price determination in the electrolytic aluminum industry: The role of electricity prices," Resources Policy, Elsevier, vol. 59(C), pages 274-281.
    11. 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).
    12. Zhao, Xiaoli & Lyon, Thomas P. & Wang, Feng & Song, Cui, 2012. "Why do electricity utilities cooperate with coal suppliers? A theoretical and empirical analysis from China," Energy Policy, Elsevier, vol. 46(C), pages 520-529.
    13. Alameer, Zakaria & Fathalla, Ahmed & Li, Kenli & Ye, Haiwang & Jianhua, Zhang, 2020. "Multistep-ahead forecasting of coal prices using a hybrid deep learning model," Resources Policy, Elsevier, vol. 65(C).
    14. Tang, Miaohan & Hong, Jingke & Liu, Guiwen & Shen, Geoffrey Qiping, 2019. "Exploring energy flows embodied in China's economy from the regional and sectoral perspectives via combination of multi-regional input–output analysis and a complex network approach," Energy, Elsevier, vol. 170(C), pages 1191-1201.
    15. Steven H. Strogatz, 2001. "Exploring complex networks," Nature, Nature, vol. 410(6825), pages 268-276, March.
    16. An, Haizhong & Gao, Xiangyun & Fang, Wei & Ding, Yinghui & Zhong, Weiqiong, 2014. "Research on patterns in the fluctuation of the co-movement between crude oil futures and spot prices: A complex network approach," Applied Energy, Elsevier, vol. 136(C), pages 1067-1075.
    17. Niu, Dong-xiao & Song, Zong-yun & Xiao, Xin-li, 2017. "Electric power substitution for coal in China: Status quo and SWOT analysis," Renewable and Sustainable Energy Reviews, Elsevier, vol. 70(C), pages 610-622.
    18. Liu, Yanxin & Li, Huajiao & Guan, Jianhe & Liu, Xueyong & Guan, Qing & Sun, Qingru, 2019. "Influence of different factors on prices of upstream, middle and downstream products in China's whole steel industry chain: Based on Adaptive Neural Fuzzy Inference System," Resources Policy, Elsevier, vol. 60(C), pages 134-142.
    19. Akkemik, K. Ali & Oğuz, Fuat, 2011. "Regulation, efficiency and equilibrium: A general equilibrium analysis of liberalization in the Turkish electricity market," Energy, Elsevier, vol. 36(5), pages 3282-3292.
    20. Yang, Chi-Jen & Xuan, Xiaowei & Jackson, Robert B., 2012. "China's coal price disturbances: Observations, explanations, and implications for global energy economies," Energy Policy, Elsevier, vol. 51(C), pages 720-727.
    21. Cui, Herui & Wei, Pengbang, 2017. "Analysis of thermal coal pricing and the coal price distortion in China from the perspective of market forces," Energy Policy, Elsevier, vol. 106(C), pages 148-154.
    22. Wang, Chao & Zhang, Xinyi & Wang, Minggang & Lim, Ming K. & Ghadimi, Pezhman, 2019. "Predictive analytics of the copper spot price by utilizing complex network and artificial neural network techniques," Resources Policy, Elsevier, vol. 63(C), pages 1-1.
    23. Mou, Dunguo, 2014. "Understanding China’s electricity market reform from the perspective of the coal-fired power disparity," Energy Policy, Elsevier, vol. 74(C), pages 224-234.
    24. Zhou, Dequn & Chong, Zhaotian & Wang, Qunwei, 2020. "What is the future policy for photovoltaic power applications in China? Lessons from the past," Resources Policy, Elsevier, vol. 65(C).
    25. Cai, Ning & Cao, Jun-Wei & Khan, M. Junaid, 2015. "Almost decouplability of any directed weighted network topology," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 436(C), pages 637-645.
    26. Lim, Seul-Ye & Yoo, Seung-Hoon, 2013. "The impact of electricity price changes on industrial prices and the general price level in Korea," Energy Policy, Elsevier, vol. 61(C), pages 1551-1555.
    27. Kwon, Sanguk & Cho, Seong-Hoon & Roberts, Roland K. & Kim, Hyun Jae & Park, Kihyun & Edward Yu, T., 2016. "Effects of electricity-price policy on electricity demand and manufacturing output," Energy, Elsevier, vol. 102(C), pages 324-334.
    28. Wang, Qiang & Chen, Xi, 2012. "China's electricity market-oriented reform: From an absolute to a relative monopoly," Energy Policy, Elsevier, vol. 51(C), pages 143-148.
    29. Du, Ruijin & Wang, Ya & Dong, Gaogao & Tian, Lixin & Liu, Yixiao & Wang, Minggang & Fang, Guochang, 2017. "A complex network perspective on interrelations and evolution features of international oil trade, 2002–2013," Applied Energy, Elsevier, vol. 196(C), pages 142-151.
    30. Bublitz, Andreas & Keles, Dogan & Fichtner, Wolf, 2017. "An analysis of the decline of electricity spot prices in Europe: Who is to blame?," Energy Policy, Elsevier, vol. 107(C), pages 323-336.
    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. Jun Dong & Dongran Liu & Xihao Dou & Bo Li & Shiyao Lv & Yuzheng Jiang & Tongtao Ma, 2021. "Key Issues and Technical Applications in the Study of Power Markets as the System Adapts to the New Power System in China," Sustainability, MDPI, vol. 13(23), pages 1-29, December.

    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. Ding, Lili & Zhao, Zhongchao & Han, Meng, 2021. "Probability density forecasts for steam coal prices in China: The role of high-frequency factors," Energy, Elsevier, vol. 220(C).
    2. Lijing Zhang & Shuke Fu & Jiali Tian & Jiachao Peng, 2022. "A Review of Energy Industry Chain and Energy Supply Chain," Energies, MDPI, vol. 15(23), pages 1-21, December.
    3. Jieting Yin & Qingyou Yan & Kaijie Lei & Tomas Baležentis & Dalia Streimikiene, 2019. "Economic and Efficiency Analysis of China Electricity Market Reform Using Computable General Equilibrium Model," Sustainability, MDPI, vol. 11(2), pages 1-22, January.
    4. Chen, Weidong & Xiong, Shi & Chen, Quanyu, 2022. "Characterizing the dynamic evolutionary behavior of multivariate price movement fluctuation in the carbon-fuel energy markets system from complex network perspective," Energy, Elsevier, vol. 239(PA).
    5. Guangyong Zhang & Lixin Tian & Wenbin Zhang & Xu Yan & Bingyue Wan & Zaili Zhen, 2020. "A Study on the Similarities and Differences of the Conventional Gasoline Spot Price Fluctuation Network between Different Harbors," Sustainability, MDPI, vol. 12(2), pages 1-25, January.
    6. Wang, Minggang & Zhao, Longfeng & Du, Ruijin & Wang, Chao & Chen, Lin & Tian, Lixin & Eugene Stanley, H., 2018. "A novel hybrid method of forecasting crude oil prices using complex network science and artificial intelligence algorithms," Applied Energy, Elsevier, vol. 220(C), pages 480-495.
    7. Kılıç Depren, Serpil & Kartal, Mustafa Tevfik & Ertuğrul, Hasan Murat & Depren, Özer, 2022. "The role of data frequency and method selection in electricity price estimation: Comparative evidence from Turkey in pre-pandemic and pandemic periods," Renewable Energy, Elsevier, vol. 186(C), pages 217-225.
    8. Xi, Xian & Zhou, Jinsheng & Gao, Xiangyun & Liu, Donghui & Zheng, Huiling & Sun, Qingru, 2019. "Impact of changes in crude oil trade network patterns on national economy," Energy Economics, Elsevier, vol. 84(C).
    9. Wang, Minggang & Xu, Hua & Tian, Lixin & Eugene Stanley, H., 2018. "Degree distributions and motif profiles of limited penetrable horizontal visibility graphs," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 509(C), pages 620-634.
    10. Peng Ou & Ruting Huang & Xin Yao, 2016. "Economic Impacts of Power Shortage," Sustainability, MDPI, vol. 8(7), pages 1-21, July.
    11. He, Yongxiu & Wang, Bing & Wang, Jianhui & Xiong, Wei & Xia, Tian, 2013. "Correlation between Chinese and international energy prices based on a HP filter and time difference analysis," Energy Policy, Elsevier, vol. 62(C), pages 898-909.
    12. Renato Agurto & Fernando Fuentes & Carlos Garcia & Esteban Skoknic, 2013. "Power Generation and the Business Cycle: The Impact of Delaying Investment," ILADES-UAH Working Papers inv290, Universidad Alberto Hurtado/School of Economics and Business.
    13. Drachal, Krzysztof, 2018. "Comparison between Bayesian and information-theoretic model averaging: Fossil fuels prices example," Energy Economics, Elsevier, vol. 74(C), pages 208-251.
    14. Guangyong Zhang & Lixin Tian & Min Fu & Bingyue Wan & Wenbin Zhang, 2020. "Research on the Transmission Ability of China’s Thermal Coal Price Information Based on Directed Limited Penetrable Interdependent Network," Sustainability, MDPI, vol. 12(18), pages 1-23, September.
    15. He, Yongda & Lin, Boqiang, 2017. "The impact of natural gas price control in China: A computable general equilibrium approach," Energy Policy, Elsevier, vol. 107(C), pages 524-531.
    16. Sumei Chen & Lingyun He, 2013. "Deregulation or Governmental Intervention? A Counterfactual Perspective on China's Electricity Market Reform," China & World Economy, Institute of World Economics and Politics, Chinese Academy of Social Sciences, vol. 21(4), pages 101-120, July.
    17. Cui, Herui & Wei, Pengbang, 2017. "Analysis of thermal coal pricing and the coal price distortion in China from the perspective of market forces," Energy Policy, Elsevier, vol. 106(C), pages 148-154.
    18. Wang, Xiaofei & Liu, Chuangeng & Chen, Shaojie & Chen, Lei & Li, Ke & Liu, Na, 2020. "Impact of coal sector’s de-capacity policy on coal price," Applied Energy, Elsevier, vol. 265(C).
    19. Guan, Qing & An, Haizhong, 2017. "The exploration on the trade preferences of cooperation partners in four energy commodities’ international trade: Crude oil, coal, natural gas and photovoltaic," Applied Energy, Elsevier, vol. 203(C), pages 154-163.
    20. Ewees, Ahmed A. & Elaziz, Mohamed Abd & Alameer, Zakaria & Ye, Haiwang & Jianhua, Zhang, 2020. "Improving multilayer perceptron neural network using chaotic grasshopper optimization algorithm to forecast iron ore price volatility," Resources Policy, Elsevier, vol. 65(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:enepol:v:158:y:2021:i:c:s0301421521004432. 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/locate/enpol .

    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.