Decentralized Active Power Management in Multi-Agent Distribution Systems Considering Congestion Issue

Mahyar Tofighi-Milani, Sajjad Fattaheian-Dehkordi, Mahmud Fotuhi-Firuzabad, Matti Lehtonen

Research output: Contribution to journalArticleScientificpeer-review

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Abstract

Recently, due to the restructuring of power systems and the high penetration level of local renewables, distribution systems have encountered with the complexity of power management. Therefore, the modern systems would be operated in a multi-agent structure which facilitates the power management as well as privacy protections of independent entities. In this structure, the distribution system is assumed to compose of several agents who independently schedule their local resources in order to maximize their own profits. Consequently, this paper provides an efficient peer-to-peer (P2P) active power management framework in a multi-agent distribution system while considering network constraints (i.e., line loadings and losses). In this context, in the proposed P2P scheme, the distribution system operator (DSO) model the network constraints in the form of line-usage costs within the transactive signals. Respectively, the developed transactive control signals enable the DSO to model the power loss as well as alleviate the congestion in the grid. Therefore, the agents automatically consider the network constraints in their power transactions management procedure without any direct interferences of the DSO in their resource scheduling. Finally, the proposed model is implemented on the modified-IEEE-37-bus-test system in order to investigate its effectiveness in the energy management of multi-agent systems.

Original languageEnglish
Pages (from-to)3582-3593
Number of pages12
JournalIEEE Transactions on Smart Grid
Volume13
Issue number5
Early online date2022
DOIs
Publication statusPublished - Sep 2022
MoE publication typeA1 Journal article-refereed

Keywords

  • Active power management
  • congestion management
  • Costs
  • distribution system
  • energy storage systems.
  • flexible resources
  • Loading
  • multi-agent system
  • Optimization
  • Peer-to-peer computing
  • peer-to-peer management
  • Power markets
  • Power system management
  • renewable energy
  • Schedules

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