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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
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    References listed on IDEAS

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    Cited by:

    1. Luca Di Persio & Nicola Fraccarolo & Andrea Veronese, 2024. "Wind Energy Production in Italy: A Forecasting Approach Based on Fractional Brownian Motion and Generative Adversarial Networks," Mathematics, MDPI, vol. 12(13), pages 1-16, July.
    2. A. H. Samitha Weerakoon & Mohsen Assadi, 2024. "Micro Gas Turbines in the Global Energy Landscape: Bridging the Techno-Economic Gap with Comparative and Adaptive Insights from Internal Combustion Engines and Renewable Energy Sources," Energies, MDPI, vol. 17(21), pages 1-31, October.
    3. 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.

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