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.

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

Ferrara, Massimiliano
Supervision
;
Ciano, Tiziana
Methodology
2020-01-01

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.
2020
Energy procurement; Tariff definition; Energy coalition; Stochastic programming; Risk management
File in questo prodotto:
File Dimensione Formato  
Ferrara et al Energy Ec. 2020.pdf

non disponibili

Tipologia: Documento in Post-print
Licenza: Tutti i diritti riservati (All rights reserved)
Dimensione 1.34 MB
Formato Adobe PDF
1.34 MB Adobe PDF   Visualizza/Apri   Richiedi una copia

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.12318/91596
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 7
  • ???jsp.display-item.citation.isi??? 7
social impact