IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v14y2022i15p9487-d878603.html
   My bibliography  Save this article

Price Strategy Analysis of Electricity Retailers Based on Evolutionary Game on Complex Networks

Author

Listed:
  • Xinyi Xie

    (School of Electrical Engineering and Automation, Wuhan University, Wuhan 430072, China)

  • Liming Ying

    (School of Electrical Engineering and Automation, Wuhan University, Wuhan 430072, China)

  • Xue Cui

    (School of Electrical Engineering and Automation, Wuhan University, Wuhan 430072, China)

Abstract

This paper analyzes the price strategy of electricity retailers in different trading scenarios. In our empirical work, we use the evolutionary game model based on the complex network to describe the information interaction relationship and game relationship between electricity retailers, and reflect the user’s switching behavior through the market share function. The purpose of our work is to study the impact of network structure, contract transaction, user’s switching behavior and strategy updating rules on the price strategy of electricity retailers by applying the evolutionary game model on complex network to the retail market. The results show that network scale, contract electricity, user switching degree and overconfidence level have important influence on the price strategy selection of electricity retailers, and these parameters should be maintained within a reasonable range in order to maximize the interests of electricity retailers and achieve the balance of retail bidding. By mapping the results of the game model to the actual policy and retail market, we believe that the evolutionary game model on network is a useful tool to analyze the competition of electricity retailers. More importantly, the conclusions can provide a reference for electricity retailers when choosing a retail price strategy and for future works which aim to analyze the development of the retail electricity market.

Suggested Citation

  • Xinyi Xie & Liming Ying & Xue Cui, 2022. "Price Strategy Analysis of Electricity Retailers Based on Evolutionary Game on Complex Networks," Sustainability, MDPI, vol. 14(15), pages 1-17, August.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:15:p:9487-:d:878603
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/14/15/9487/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/14/15/9487/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Kharrati, Saeed & Kazemi, Mostafa & Ehsan, Mehdi, 2016. "Equilibria in the competitive retail electricity market considering uncertainty and risk management," Energy, Elsevier, vol. 106(C), pages 315-328.
    2. Ndebele, Tom & Marsh, Dan & Scarpa, Riccardo, 2019. "Consumer switching in retail electricity markets: Is price all that matters?," Energy Economics, Elsevier, vol. 83(C), pages 88-103.
    3. David Pozo & Enzo Sauma & Javier Contreras, 2017. "Basic theoretical foundations and insights on bilevel models and their applications to power systems," Annals of Operations Research, Springer, vol. 254(1), pages 303-334, July.
    4. Ryle S. Perera, 2018. "An Evolutionary Game Theory Strategy for Carbon Emission Reduction in the Electricity Market," International Game Theory Review (IGTR), World Scientific Publishing Co. Pte. Ltd., vol. 20(04), pages 1-20, December.
    5. Peng, Yu & Lu, Qian & Xiao, Yue, 2016. "A dynamic Stackelberg duopoly model with different strategies," Chaos, Solitons & Fractals, Elsevier, vol. 85(C), pages 128-134.
    6. Guo, Hongye & Chen, Qixin & Shahidehpour, Mohammad & Xia, Qing & Kang, Chongqing, 2022. "Bidding behaviors of GENCOs under bounded rationality with renewable energy," Energy, Elsevier, vol. 250(C).
    7. repec:wsi:jeapmx:v:20:y:2018:i:04:n:s0219198918500081 is not listed on IDEAS
    8. Jiang, Yanni & Zhou, Kaile & Lu, Xinhui & Yang, Shanlin, 2020. "Electricity trading pricing among prosumers with game theory-based model in energy blockchain environment," Applied Energy, Elsevier, vol. 271(C).
    9. Manitra A. Rakotoarisoa, 2016. "Trade with Endogenous Market Power Under Asymmetric and Incomplete Information," Journal of Industry, Competition and Trade, Springer, vol. 16(4), pages 423-440, December.
    10. Fotouhi Ghazvini, Mohammad Ali & Ramos, Sergio & Soares, João & Castro, Rui & Vale, Zita, 2019. "Liberalization and customer behavior in the Portuguese residential retail electricity market," Utilities Policy, Elsevier, vol. 59(C), pages 1-1.
    11. Andrew A. Goett & Kathleen Hudson & Kenneth E. Train, 2000. "Customers' Choice Among Retail Energy Suppliers: The Willingness-to-Pay for Service Attributes," The Energy Journal, International Association for Energy Economics, vol. 0(Number 4), pages 1-28.
    12. Yang, Peiwen & Dong, Jun & Lin, Jin & Liu, Yao & Fang, Debin, 2021. "Analysis of offering behavior of generation-side integrated energy aggregator in electricity market:A Bayesian evolutionary approach," Energy, Elsevier, vol. 228(C).
    13. Lin, Zhiqi & Xu, Hedong & Fan, Suohai, 2020. "Evolutionary accumulated temptation game on small world networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 553(C).
    14. Yang, Yingkui, 2014. "Understanding household switching behavior in the retail electricity market," Energy Policy, Elsevier, vol. 69(C), pages 406-414.
    15. Barazza, Elsa & Strachan, Neil, 2020. "The impact of heterogeneous market players with bounded-rationality on the electricity sector low-carbon transition," Energy Policy, Elsevier, vol. 138(C).
    16. Barati, Ali Akbar & Azadi, Hossein & Scheffran, Jürgen, 2021. "Agricultural land fragmentation in Iran: Application of game theory," Land Use Policy, Elsevier, vol. 100(C).
    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. Massimo Dragotto & Marco Magnani & Paola Valbonesi, 2021. "Consumer inertia and firm incumbency in liberalised retail electricity markets: an empirical investigation," "Marco Fanno" Working Papers 0277, Dipartimento di Scienze Economiche "Marco Fanno".
    2. Erdogan, Murside Rabia & Camgoz, Selin Metin & Karan, Mehmet Baha & Berument, M. Hakan, 2022. "The switching behavior of large-scale electricity consumers in The Turkish electricity retail market," Energy Policy, Elsevier, vol. 160(C).
    3. Bedggood, Rowan & Russell-Bennett, Rebekah & McAndrew, Ryan & Glavas, Charmaine & Dulleck, Uwe, 2023. "Challenging the social-power paradigm: Moving beyond consumer empowerment to an energy ecosystem of shared value," Energy Policy, Elsevier, vol. 173(C).
    4. Nogata, Daisuke, 2022. "Determinants of household switching between natural gas suppliers: Evidence from Japan," Utilities Policy, Elsevier, vol. 76(C).
    5. Esplin, Ryan & Best, Rohan & Scranton, Jessica & Chai, Andreas, 2022. "Who pays the loyalty tax? The relationship between socioeconomic status and switching in Australia's retail electricity markets," Energy Policy, Elsevier, vol. 164(C).
    6. Vesterberg, Mattias, 2018. "The effect of price on electricity contract choice," Energy Economics, Elsevier, vol. 69(C), pages 59-70.
    7. Guo, Hongye & Chen, Qixin & Shahidehpour, Mohammad & Xia, Qing & Kang, Chongqing, 2022. "Bidding behaviors of GENCOs under bounded rationality with renewable energy," Energy, Elsevier, vol. 250(C).
    8. Vesterberg, Mattias, 2017. "The effect of price on electricity contract choice," Umeå Economic Studies 941, Umeå University, Department of Economics.
    9. Amenta, Carlo & Aronica, Martina & Stagnaro, Carlo, 2022. "Is more competition better? Retail electricity prices and switching rates in the European Union," Utilities Policy, Elsevier, vol. 78(C).
    10. Widha Kusumaningdyah & Tetsuo Tezuka & Benjamin C. McLellan, 2021. "Investigating Preconditions for Sustainable Renewable Energy Product–Service Systems in Retail Electricity Markets," Energies, MDPI, vol. 14(7), pages 1-21, March.
    11. Gauthier Lanot & Mattias Vesterberg, 2019. "An empirical model of the decision to switch between electricity price contracts," Journal of Business Analytics, Taylor & Francis Journals, vol. 2(1), pages 24-46, January.
    12. Gauthier Lanot & Mattias Vesterberg, 2019. "An empirical model of the decision to switch between electricity price contracts," Journal of Business Analytics, Taylor & Francis Journals, vol. 2(1), pages 24-46, January.
    13. Ndebele, Tom & Marsh, Dan & Scarpa, Riccardo, 2019. "Consumer switching in retail electricity markets: Is price all that matters?," Energy Economics, Elsevier, vol. 83(C), pages 88-103.
    14. Janez Dolšak & Nevenka Hrovatin & Jelena Zorić, 2020. "Analysing Consumer Preferences, Characteristics, and Behaviour to Identify Energy-Efficient Consumers," Sustainability, MDPI, vol. 12(23), pages 1-19, November.
    15. Bernadeta Gołębiowska, 2020. "Preferences for demand side management—a review of choice experiment studies," Working Papers 2020-05, Faculty of Economic Sciences, University of Warsaw.
    16. Kruse, Tobias & Atkinson, Giles, 2022. "Understanding public support for international climate adaptation payments: Evidence from a choice experiment," Ecological Economics, Elsevier, vol. 194(C).
    17. Hartley, Peter R. & Medlock, Kenneth B. & Jankovska, Olivera, 2019. "Electricity reform and retail pricing in Texas," Energy Economics, Elsevier, vol. 80(C), pages 1-11.
    18. Chaikaew, Pasicha & Hodges, Alan W. & Grunwald, Sabine, 2017. "Estimating the value of ecosystem services in a mixed-use watershed: A choice experiment approach," Ecosystem Services, Elsevier, vol. 23(C), pages 228-237.
    19. Fang, Debin & Wang, Pengyu, 2023. "Optimal real-time pricing and electricity package by retail electric providers based on social learning," Energy Economics, Elsevier, vol. 117(C).
    20. Tian, Yi & Ma, Junhai & Xie, Lei & Koivumäki, Timo & Seppänen, Veikko, 2020. "Coordination and control of multi-channel supply chain driven by consumers’ channel preference and sales effort," Chaos, Solitons & Fractals, Elsevier, vol. 132(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:gam:jsusta:v:14:y:2022:i:15:p:9487-:d:878603. 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.