IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v16y2023i16p5950-d1215728.html
   My bibliography  Save this article

Investment and Bidding Strategies for Optimal Transmission Management Dynamics: The Italian Case

Author

Listed:
  • Luca Di Persio

    (Department of Computer Science, University of Verona, 37134 Verona, Italy)

  • Nicola Fraccarolo

    (Department of Mathematics, University of Trento, 38123 Trento, Italy)

Abstract

This paper explores the allocation process of Financial Transmission Rights (FTRs) in the Italian electricity market. FTRs are financial instruments allowing market participants to hedge against transmission congestion, also playing a critical role in ensuring the efficient use of the transmission system. We present a linear programming (LP) model that simulates the FTRs allocation process, taking into account the transmission capacity limits of the electric network when the total revenue is considered as the utility function. Obtained results highlight that our solution allows us to develop better investment and bidding strategies for optimal transmission management dynamics. In particular, numerical simulations show good results, with an overall MAPE of approximately 7%, indicating that the model accurately predicts the allocation of transmission rights across the network. Overall, the paper provides insights into the inner workings of the FTR allocation process in Italy, also providing improved market efficiency while increasing revenue for market participants.

Suggested Citation

  • Luca Di Persio & Nicola Fraccarolo, 2023. "Investment and Bidding Strategies for Optimal Transmission Management Dynamics: The Italian Case," Energies, MDPI, vol. 16(16), pages 1-16, August.
    • Handle: RePEc:gam:jeners:v:16:y:2023:i:16:p:5950-:d:1215728
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/16/16/5950/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/16/16/5950/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Panda, Mitali & Nayak, Yogesh Kumar, 2022. "Impact analysis of renewable energy Distributed Generation in deregulated electricity markets: A Context of Transmission Congestion Problem," Energy, Elsevier, vol. 254(PC).
    2. Hogan, William W, 1992. "Contract Networks for Electric Power Transmission," Journal of Regulatory Economics, Springer, vol. 4(3), pages 211-242, September.
    3. An, Jaehyung & Mikhaylov, Alexey & Jung, Sang-Uk, 2021. "A Linear Programming approach for robust network revenue management in the airline industry," Journal of Air Transport Management, Elsevier, vol. 91(C).
    4. Harvey, Scott M. & Hogan, William W. & Pope, Susan L., 1996. "Transmission capacity reservations implemented through a spot market with transmission congestion contracts," The Electricity Journal, Elsevier, vol. 9(9), pages 42-55, November.
    5. C Papahristodoulou & E Dotzauer, 2004. "Optimal portfolios using linear programming models," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 55(11), pages 1169-1177, November.
    6. Izabela Zoltowska & Jeremy Lin, 2021. "Optimal Charging Schedule Planning for Electric Buses Using Aggregated Day-Ahead Auction Bids," Energies, MDPI, vol. 14(16), pages 1-18, August.
    7. Daskalaki, S. & Birbas, T. & Housos, E., 2004. "An integer programming formulation for a case study in university timetabling," European Journal of Operational Research, Elsevier, vol. 153(1), pages 117-135, February.
    8. Chunxia Gao & Zhaoyan Zhang & Peiguang Wang, 2023. "Day-Ahead Scheduling Strategy Optimization of Electric–Thermal Integrated Energy System to Improve the Proportion of New Energy," Energies, MDPI, vol. 16(9), pages 1-30, April.
    9. Hiroshi Konno & Rei Yamamoto, 2005. "Integer programming approaches in mean-risk models," Computational Management Science, Springer, vol. 4(4), pages 339-351, November.
    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. Hui Sun & Tian Jin & Zhengnan Gao & Shubo Hu & Yanan Dou & Xueli Lu, 2024. "A Transmission and Distribution Cooperative Congestion Scheduling Strategy Based on Flexible Load Dynamic Compensation Prices," Energies, MDPI, vol. 17(5), pages 1-24, March.

    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. Andreas Ehrenmann & Karsten Neuhoff, 2009. "A Comparison of Electricity Market Designs in Networks," Operations Research, INFORMS, vol. 57(2), pages 274-286, April.
    2. Joskow, Paul L & Tirole, Jean, 1999. "Transmission Rights and Market Power on Electric Power Networks I: Financial Rights," CEPR Discussion Papers 2093, C.E.P.R. Discussion Papers.
    3. Paul L. Joskow, 1997. "Restructuring, Competition and Regulatory Reform in the U.S. Electricity Sector," Journal of Economic Perspectives, American Economic Association, vol. 11(3), pages 119-138, Summer.
    4. Bjørndal, Endre & Bjørndal, Mette & Gribkovskaia, Victoria, 2014. "A Nodal Pricing Model for the Nordic Electricity Market," Discussion Papers 2014/43, Norwegian School of Economics, Department of Business and Management Science.
    5. Bushnell, James B. & Stoft, Steven E., 1997. "Improving private incentives for electric grid investment," Resource and Energy Economics, Elsevier, vol. 19(1-2), pages 85-108, March.
    6. Benjamin F. Hobbs & Fieke A.M. Rijkers & Maroeska G. Boots, 2005. "The More Cooperation, The More Competition? A Cournot Analysis of the Benefits of Electric Market Coupling," The Energy Journal, International Association for Energy Economics, vol. 0(Number 4), pages 69-98.
    7. Karsten Neuhoff, 2002. "Optimal congestion treatment for bilateral electricity trading," Working Papers EP05, Energy Policy Research Group, Cambridge Judge Business School, University of Cambridge.
    8. Glachant, Jean-Michel & Pignon, Virginie, 2005. "Nordic congestion's arrangement as a model for Europe? Physical constraints vs. economic incentives," Utilities Policy, Elsevier, vol. 13(2), pages 153-162, June.
    9. Simshauser, P., 2019. "On the impact of government-initiated CfD’s in Australia’s National Electricity Market," Cambridge Working Papers in Economics 1901, Faculty of Economics, University of Cambridge.
    10. Glanchant, J-M. & Pignon, V., 2003. "Nordic Electricity Congestion's Arrangement as a Model for Europe: Physical Constraints or Operators' Opportunity," Cambridge Working Papers in Economics 0313, Faculty of Economics, University of Cambridge.
    11. Zhang, Ning, 2009. "Market performance and bidders' bidding behavior in the New York Transmission Congestion Contract market," Energy Economics, Elsevier, vol. 31(1), pages 61-68, January.
    12. Thomas-Olivier Léautier & Véronique Thelen, 2009. "Optimal expansion of the power transmission grid: why not?," Journal of Regulatory Economics, Springer, vol. 36(2), pages 127-153, October.
    13. Chen, Yen-Haw & Lu, Su-Ying & Chang, Yung-Ruei & Lee, Ta-Tung & Hu, Ming-Che, 2013. "Economic analysis and optimal energy management models for microgrid systems: A case study in Taiwan," Applied Energy, Elsevier, vol. 103(C), pages 145-154.
    14. Paul L. Joskow, 2001. "California's Electricity Crisis," Oxford Review of Economic Policy, Oxford University Press and Oxford Review of Economic Policy Limited, vol. 17(3), pages 365-388.
    15. Somani, Abhishek, 2012. "Financial risk management and market performance in restructured electric power markets: Theoretical and agent-based test bed studies," ISU General Staff Papers 201201010800003479, Iowa State University, Department of Economics.
    16. Woo, C.K. & Zarnikau, J. & Moore, J. & Horowitz, I., 2011. "Wind generation and zonal-market price divergence: Evidence from Texas," Energy Policy, Elsevier, vol. 39(7), pages 3928-3938, July.
    17. Yin, Linfei & He, Xiaoyu, 2023. "Artificial emotional deep Q learning for real-time smart voltage control of cyber-physical social power systems," Energy, Elsevier, vol. 273(C).
    18. Cristian Zambrano & Yris Olaya, 2017. "An agent-based simulation approach to congestion management for the Colombian electricity market," Annals of Operations Research, Springer, vol. 258(2), pages 217-236, November.
    19. Paul Joskow & Jean Tirole, 2005. "Merchant Transmission Investment," Journal of Industrial Economics, Wiley Blackwell, vol. 53(2), pages 233-264, June.
    20. Brunekreeft, Gert, 2004. "Market-based investment in electricity transmission networks: controllable flow," Utilities Policy, Elsevier, vol. 12(4), pages 269-281, December.

    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:jeners:v:16:y:2023:i:16:p:5950-:d:1215728. 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.