IDEAS home Printed from https://ideas.repec.org/a/eee/energy/v278y2023ics0360544223011714.html
   My bibliography  Save this article

Ex-ante market power evaluation and mitigation in day-ahead electricity market considering market maturity levels

Author

Listed:
  • Lin, Xueshan
  • Huang, Tao
  • Bompard, Ettore
  • Wang, Beibei
  • Zheng, Yaxian

Abstract

Market power is detrimental to the fair operation of the spot market, thus many market power evaluation and mitigation approaches have been put forward. However, due to the market maturity levels and the approaches themselves, excessive/deficient mitigation or high computational burden for a more accurate evaluation in practice are not rare. Therefore, in this paper, we propose a combined market power evaluation and mitigation framework, based on the emerging electricity day-ahead markets, in which the market power mitigation can be achieved ex-ante to the market clearing and can be flexibly adopted according to the market maturity levels during the development of the markets. More specifically, an ex-ante Customized Market Operation (CMO) indicator is first proposed to evaluate the market power of individual generators. Secondly, based on the CMO and the maturity of the market levels, an optimal CMO threshold is derived through the Best and Worst Method (BWM)-Entropy approach to mitigate the market power via limiting individual generators’ offer coefficients. Finally, the proposed CMO-BWM-Entropy approach is applied to the Chinese electricity markets under different maturity levels. Our results indicate that the accuracy of market power mitigation, quantified by the Lerner index, is 10 times higher than other existing ex-ante market power mitigation approaches, and the computational efficiency is 50 times faster than the compared ones.

Suggested Citation

  • Lin, Xueshan & Huang, Tao & Bompard, Ettore & Wang, Beibei & Zheng, Yaxian, 2023. "Ex-ante market power evaluation and mitigation in day-ahead electricity market considering market maturity levels," Energy, Elsevier, vol. 278(C).
    • Handle: RePEc:eee:energy:v:278:y:2023:i:c:s0360544223011714
    DOI: 10.1016/j.energy.2023.127777
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0360544223011714
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.energy.2023.127777?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. Sun, Bo & Deng, Ruilin & Ren, Bin & Teng, Minmin & Cheng, Siyuan & Wang, Fan, 2022. "Identification method of market power abuse of generators based on lasso-logit model in spot market," Energy, Elsevier, vol. 238(PA).
    2. Wu, Zhibin & Xu, Jiuping, 2016. "Managing consistency and consensus in group decision making with hesitant fuzzy linguistic preference relations," Omega, Elsevier, vol. 65(C), pages 28-40.
    3. Agarwal, Deepika & Singh, Pitam & El Sayed, M.A., 2023. "The Karush–Kuhn–Tucker (KKT) optimality conditions for fuzzy-valued fractional optimization problems," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 205(C), pages 861-877.
    4. Fan, Siyuan & Wang, Yu & Cao, Shengxian & Sun, Tianyi & Liu, Peng, 2021. "A novel method for analyzing the effect of dust accumulation on energy efficiency loss in photovoltaic (PV) system," Energy, Elsevier, vol. 234(C).
    5. Simic, Vladimir & Gokasar, Ilgin & Deveci, Muhammet & Karakurt, Ahmet, 2022. "An integrated CRITIC and MABAC based type-2 neutrosophic model for public transportation pricing system selection," Socio-Economic Planning Sciences, Elsevier, vol. 80(C).
    6. Helman, Udi, 2006. "Market power monitoring and mitigation in the US wholesale power markets," Energy, Elsevier, vol. 31(6), pages 877-904.
    7. Compte, Olivier & Jenny, Frederic & Rey, Patrick, 2002. "Capacity constraints, mergers and collusion," European Economic Review, Elsevier, vol. 46(1), pages 1-29, January.
    8. Yan, Hong-Bin & Ma, Tieju & Huynh, Van-Nam, 2017. "On qualitative multi-attribute group decision making and its consensus measure: A probability based perspective," Omega, Elsevier, vol. 70(C), pages 94-117.
    9. Dongdong Hu & Hasanjan Sayit & Frederi Viens, 2023. "Pricing basket options with the first three moments of the basket: log-normal models and beyond," Papers 2302.08041, arXiv.org, revised Feb 2023.
    10. Li, Songrui & Zhang, Lihui & Nie, Lei & Wang, Jianing, 2022. "Trading strategy and benefit optimization of load aggregators in integrated energy systems considering integrated demand response: A hierarchical Stackelberg game," Energy, Elsevier, vol. 249(C).
    11. Hesamzadeh, Mohammad R. & Biggar, Darryl R. & Hosseinzadeh, Nasser, 2011. "The TC-PSI indicator for forecasting the potential for market power in wholesale electricity markets," Energy Policy, Elsevier, vol. 39(10), pages 5988-5998, October.
    12. Mohammadi, Majid & Rezaei, Jafar, 2020. "Bayesian best-worst method: A probabilistic group decision making model," Omega, Elsevier, vol. 96(C).
    13. Koomson, Isaac & Danquah, Michael, 2021. "Financial inclusion and energy poverty: Empirical evidence from Ghana," Energy Economics, Elsevier, vol. 94(C).
    14. Rezaei, Jafar, 2016. "Best-worst multi-criteria decision-making method: Some properties and a linear model," Omega, Elsevier, vol. 64(C), pages 126-130.
    15. Rezaei, Jafar, 2015. "Best-worst multi-criteria decision-making method," Omega, Elsevier, vol. 53(C), pages 49-57.
    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. Cheng, Xiong & Lv, Xin & Li, Xianshan & Zhong, Hao & Feng, Jia, 2023. "Market power evaluation in the electricity market based on the weighted maintenance object," Energy, Elsevier, vol. 284(C).
    2. Hu, Fei & Zhao, Yong & Huang, Cheng & Cui, Shichang & Ding, Qiang & Li, Yuanzheng, 2024. "Market power detection and mitigation measures for the spot electricity market based on bidding equilibrium," Energy, Elsevier, vol. 305(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. Mohammadi, Majid & Rezaei, Jafar, 2020. "Bayesian best-worst method: A probabilistic group decision making model," Omega, Elsevier, vol. 96(C).
    2. Vieira, Fabiana C. & Ferreira, Fernando A.F. & Govindan, Kannan & Ferreira, Neuza C.M.Q.F. & Banaitis, Audrius, 2022. "Measuring urban digitalization using cognitive mapping and the best worst method (BWM)," Technology in Society, Elsevier, vol. 71(C).
    3. Wu, Qun & Liu, Xinwang & Zhou, Ligang & Qin, Jindong & Rezaei, Jafar, 2024. "An analytical framework for the best–worst method," Omega, Elsevier, vol. 123(C).
    4. Burak Can Altay & Abdullah Erdem Boztas & Abdullah Okumuş & Muhammet Gul & Erkan Çelik, 2023. "How Will Autonomous Vehicles Decide in Case of an Accident? An Interval Type-2 Fuzzy Best–Worst Method for Weighting the Criteria from Moral Values Point of View," Sustainability, MDPI, vol. 15(11), pages 1-20, June.
    5. Wu, Qun & Liu, Xinwang & Qin, Jindong & Zhou, Ligang & Mardani, Abbas & Deveci, Muhammet, 2022. "An integrated multi-criteria decision-making and multi-objective optimization model for socially responsible portfolio selection," Technological Forecasting and Social Change, Elsevier, vol. 184(C).
    6. Corrente, Salvatore & Greco, Salvatore & Rezaei, Jafar, 2024. "Better decisions with less cognitive load: The Parsimonious BWM," Omega, Elsevier, vol. 126(C).
    7. Göçmen Polat, Elifcan & Yücesan, Melih & Gül, Muhammet, 2023. "A comparative framework for criticality assessment of strategic raw materials in Turkey," Resources Policy, Elsevier, vol. 82(C).
    8. Vineet Kaushik & Shobha Tewari, 2023. "Modeling Opportunity Indicators Fostering Social Entrepreneurship: A Hybrid Delphi and Best-Worst Approach," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 168(1), pages 667-698, August.
    9. Jian Wang & Jin-Chun Huang & Shan-Lin Huang & Gwo-Hshiung Tzeng & Ting Zhu, 2021. "Improvement Path for Resource-Constrained Cities Identified Using an Environmental Co-Governance Assessment Framework Based on BWM-mV Model," IJERPH, MDPI, vol. 18(9), pages 1-30, May.
    10. Murad, C.A. & Bellinello, M.M. & Silva, A.J. & Netto, A. Caminada & de Souza, G.F.M. & Nabeta, S.I., 2022. "A novel methodology employed for ranking and consolidating performance indicators in holding companies with multiple power plants based on multi-criteria decision-making method," Operations Research Perspectives, Elsevier, vol. 9(C).
    11. Zeyu Lin & Hamdi Ayed & Belgacem Bouallegue & Hana Tomaskova & Saeid Jafarzadeh Ghoushchi & Gholamreza Haseli, 2021. "An Integrated Mathematical Attitude Utilizing Fully Fuzzy BWM and Fuzzy WASPAS for Risk Evaluation in a SOFC," Mathematics, MDPI, vol. 9(18), pages 1-18, September.
    12. James J. H. Liou & Perry C. Y. Liu & Huai-Wei Lo, 2020. "A Failure Mode Assessment Model Based on Neutrosophic Logic for Switched-Mode Power Supply Risk Analysis," Mathematics, MDPI, vol. 8(12), pages 1-19, December.
    13. Sarfaraz Hashemkhani Zolfani & Ramin Bazrafshan & Fatih Ecer & Çağlar Karamaşa, 2022. "The Suitability-Feasibility-Acceptability Strategy Integrated with Bayesian BWM-MARCOS Methods to Determine the Optimal Lithium Battery Plant Located in South America," Mathematics, MDPI, vol. 10(14), pages 1-18, July.
    14. Liang, Fuqi & Brunelli, Matteo & Rezaei, Jafar, 2020. "Consistency issues in the best worst method: Measurements and thresholds," Omega, Elsevier, vol. 96(C).
    15. Salimi, Negin & Rezaei, Jafar, 2018. "Evaluating firms’ R&D performance using best worst method," Evaluation and Program Planning, Elsevier, vol. 66(C), pages 147-155.
    16. Ravindra Singh Saluja & Varinder Singh, 2023. "Attribute-based characterization, coding, and selection of joining processes using a novel MADM approach," OPSEARCH, Springer;Operational Research Society of India, vol. 60(2), pages 616-655, June.
    17. Junli Zhang & Guoteng Wang & Zheng Xu & Zheren Zhang, 2022. "A Comprehensive Evaluation Method and Strengthening Measures for AC/DC Hybrid Power Grids," Energies, MDPI, vol. 15(12), pages 1-20, June.
    18. Hamzeh Soltanali & Mehdi Khojastehpour & Siamak Kheybari, 2023. "Evaluating the critical success factors for maintenance management in agro-industries using multi-criteria decision-making techniques," Operations Management Research, Springer, vol. 16(2), pages 949-968, June.
    19. Yossi Hadad & Baruch Keren & Dima Alberg, 2023. "An Expert System for Ranking and Matching Electric Vehicles to Customer Specifications and Requirements," Energies, MDPI, vol. 16(11), pages 1-18, May.
    20. Besharati Fard, Moein & Moradian, Parisa & Emarati, Mohammadreza & Ebadi, Mehdi & Gholamzadeh Chofreh, Abdoulmohammad & Klemeŝ, Jiří Jaromír, 2022. "Ground-mounted photovoltaic power station site selection and economic analysis based on a hybrid fuzzy best-worst method and geographic information system: A case study Guilan province," Renewable and Sustainable Energy Reviews, Elsevier, vol. 169(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:energy:v:278:y:2023:i:c:s0360544223011714. 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.journals.elsevier.com/energy .

    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.