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A Decentralized Market Mechanism for Energy Communities Under Operating Envelopes

  • Ahmed S. Alahmed*
  • , Guido Cavraro
  • , Andrey Bernstein
  • , Lang Tong
  • *Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

Abstract

We propose an operating envelopes (OEs) aware energy community market mechanism that dynamically charges/rewards its members based on two-part pricing. The OEs are imposed exogenously by a regulated distribution system operator (DSO) on the energy community's revenue meter and are subject to a generalized net energy metering tariff design. By formulating the interaction of the community operator and its members as a Stackelberg game, we show that the proposed two-part pricing achieves a Nash equilibrium and maximizes the community's social welfare in a decentralized fashion while ensuring that the community's operation abides by the OEs. The market mechanism conforms with the cost-causation principle and guarantees community members a surplus level no less than their maximum surplus when they autonomously face the DSO. The dynamic and uniform community price is a monotonically decreasing function of the community's aggregate renewable generation. We also analyze the impact of exogenous parameters, such as NEM rates and OEs, on the value of joining the community. Lastly, through numerical studies, we showcase the community's welfare and pricing, and compare its members' surplus to customers under the DSO's regime.

Original languageEnglish
Pages (from-to)313-324
Number of pages12
JournalIEEE Transactions on Control of Network Systems
Volume12
Issue number1
DOIs
StatePublished - 2025
Externally publishedYes

Bibliographical note

Publisher Copyright:
© 2014 IEEE.

Keywords

  • Dynamic pricing
  • Stackelberg game
  • energy community
  • net metering
  • operating envelopes (OEs)
  • transactive energy system
  • two-part pricing

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Signal Processing
  • Computer Networks and Communications
  • Control and Optimization

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