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Decentralized active power management in multi-agent distribution systems considering congestion issue

Tofighi Milani, M ; Sharif University of Technology | 2022

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  1. Type of Document: Article
  2. DOI: 10.1109/TSG.2022.3172757
  3. Publisher: Institute of Electrical and Electronics Engineers Inc , 2022
  4. Abstract:
  5. 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. © 2010-2012 IEEE
  6. Keywords:
  7. Active power management ; Congestion management ; Distribution system ; Energy storage systems ; Multi-agent system ; Renewable energy ; Distributed computer systems ; Electric load flow ; Electric power system control ; Energy management systems ; Energy storage ; Peer to peer networks ; Power management ; Renewable energy resources ; Scheduling ; Active power management ; Congestions managements ; Distribution systems ; Energy storage system ; Flexible resources ; Optimisations ; Peer-to-peer computing ; Peer-to-peer management ; Power system management ; Renewable energies ; Schedule ; Storage systems ; Multi agent systems
  8. Source: IEEE Transactions on Smart Grid ; Volume 13, Issue 5 , 2022 , Pages 3582-3593 ; 19493053 (ISSN)
  9. URL: https://ieeexplore.ieee.org/document/9774361