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An integrated decision approach for energy procurement and tariff definition for prosumers aggregations

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  • Ferrara, Massimiliano
  • Violi, Antonio
  • Beraldi, Patrizia
  • Carrozzino, Gianluca
  • Ciano, Tiziana

Abstract

The paper deals with the energy procurement and economic management problem for an aggregation of prosumers at a strategic/tactical level. This decision process, usually in charge of the “aggregator”, the entity which coordinates market operations and resource management for the entire coalition, consists into the definition of the optimal mix of energy to procure from the available sources (bilateral contracts, self-production, day-ahead market) and the tariff scheme to offer to the members of the coalition for buying and selling energy. This problem is made more complex by the presence of several sources of uncertainty, like market prices, overall demand of the coalition and production from renewable systems. To the best of our knowledge, even if several contributions have been proposed to deal with the energy procurement and tariff definition problems separately, none of them has addressed the decision process as a whole. In this paper, we propose a multiperiod 2-stage stochastic programming approach, which models the strict relations between the decisions to be made and controls risk exposure by a mean-risk objective function with the Conditional Value at Risk as risk measure. Moreover, the proposed approach aims at defining 2-components tariffs, with a variable part that is related to the random evolution of market prices, in order to enhance prosumers' responsiveness. Preliminary computational results show the effectiveness of the proposed approach as a decision support tool to guarantee the economic sustainability of the coalition and the convenience of single prosumers.

Suggested Citation

  • Ferrara, Massimiliano & Violi, Antonio & Beraldi, Patrizia & Carrozzino, Gianluca & Ciano, Tiziana, 2021. "An integrated decision approach for energy procurement and tariff definition for prosumers aggregations," Energy Economics, Elsevier, vol. 97(C).
    • Handle: RePEc:eee:eneeco:v:97:y:2021:i:c:s0140988320303741
    DOI: 10.1016/j.eneco.2020.105034
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    References listed on IDEAS

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    1. Zare, Kazem & Moghaddam, Mohsen Parsa & Sheikh El Eslami, Mohammad Kazem, 2010. "Electricity procurement for large consumers based on Information Gap Decision Theory," Energy Policy, Elsevier, vol. 38(1), pages 234-242, January.
    2. Fridgen, Gilbert & Kahlen, Micha & Ketter, Wolfgang & Rieger, Alexander & Thimmel, Markus, 2018. "One rate does not fit all: An empirical analysis of electricity tariffs for residential microgrids," Applied Energy, Elsevier, vol. 210(C), pages 800-814.
    3. Mohammad Ali Fotouhi Ghazvini & João Soares & Hugo Morais & Rui Castro & Zita Vale, 2017. "Dynamic Pricing for Demand Response Considering Market Price Uncertainty," Energies, MDPI, vol. 10(9), pages 1-20, August.
    4. Patrizia Beraldi & Antonio Violi & Maria Elena Bruni & Gianluca Carrozzino, 2017. "A Probabilistically Constrained Approach for the Energy Procurement Problem," Energies, MDPI, vol. 10(12), pages 1-17, December.
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    Cited by:

    1. Silva, Rodolfo Rodrigues Barrionuevo & Martins, André Christóvão Pio & Soler, Edilaine Martins & Baptista, Edméa Cássia & Balbo, Antonio Roberto & Nepomuceno, Leonardo, 2022. "Two-stage stochastic energy procurement model for a large consumer in hydrothermal systems," Energy Economics, Elsevier, vol. 107(C).
    2. Beraldi, Patrizia & Khodaparasti, Sara, 2023. "Designing electricity tariffs in the retail market: A stochastic bi-level approach," International Journal of Production Economics, Elsevier, vol. 257(C).

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