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Real-time pricing for aggregates energy resources in the Italian energy market

Author

Listed:
  • Favuzza, S.
  • Galioto, G.
  • Ippolito, M.G.
  • Massaro, F.
  • Milazzo, F.
  • Pecoraro, G.
  • Riva Sanseverino, E.
  • Telaretti, E.

Abstract

Over the last decade, the architecture of the energy market has radically changed. In many countries end-users are now able to directly access the market, which has given rise to the question of how they can actively participate in that market. End-users can comprise a critical mass through aggregation that is carried out by a third party – to wit the “loads aggregator.” This paper proposes a new framework for generating feasible real-time price curves for those end-users in a demand-response management process. The underlying algorithm generates output curves as the solution to a constrained optimization problem whose objective function is the aggregator's economic benefit. A case simulation study of the Italian market, with various parameter options, illustrates the procedure.

Suggested Citation

  • Favuzza, S. & Galioto, G. & Ippolito, M.G. & Massaro, F. & Milazzo, F. & Pecoraro, G. & Riva Sanseverino, E. & Telaretti, E., 2015. "Real-time pricing for aggregates energy resources in the Italian energy market," Energy, Elsevier, vol. 87(C), pages 251-258.
    • Handle: RePEc:eee:energy:v:87:y:2015:i:c:p:251-258
    DOI: 10.1016/j.energy.2015.04.105
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    References listed on IDEAS

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    1. Cosentino, Valentina & Favuzza, Salvatore & Graditi, Giorgio & Ippolito, Mariano Giuseppe & Massaro, Fabio & Riva Sanseverino, Eleonora & Zizzo, Gaetano, 2012. "Smart renewable generation for an islanded system. Technical and economic issues of future scenarios," Energy, Elsevier, vol. 39(1), pages 196-204.
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    Cited by:

    1. Salvatore Favuzza & Mariano Giuseppe Ippolito & Fabio Massaro & Rossano Musca & Eleonora Riva Sanseverino & Giuseppe Schillaci & Gaetano Zizzo, 2018. "Building Automation and Control Systems and Electrical Distribution Grids: A Study on the Effects of Loads Control Logics on Power Losses and Peaks," Energies, MDPI, vol. 11(3), pages 1-15, March.
    2. Telaretti, E. & Graditi, G. & Ippolito, M.G. & Zizzo, G., 2016. "Economic feasibility of stationary electrochemical storages for electric bill management applications: The Italian scenario," Energy Policy, Elsevier, vol. 94(C), pages 126-137.
    3. Nykyri, Mikko & Kärkkäinen, Tommi J. & Levikari, Saku & Honkapuro, Samuli & Annala, Salla & Silventoinen, Pertti, 2022. "Blockchain-based balance settlement ledger for energy communities in open electricity markets," Energy, Elsevier, vol. 253(C).
    4. Zhang, Li & Gao, Yan & Zhu, Hongbo & Tao, Li, 2022. "Bi-level stochastic real-time pricing model in multi-energy generation system: A reinforcement learning approach," Energy, Elsevier, vol. 239(PA).
    5. Feng, Wenxiu & Ruiz, Carlos, 2023. "Risk management of energy communities with hydrogen production and storage technologies," Applied Energy, Elsevier, vol. 348(C).

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