Distributed multi-agent based coordinated power management and control strategy for microgrids with distributed energy resources

M. S. Rahman*, A. M. T. Oo

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

91 Citations (Scopus)

Abstract

In this paper, a distributed peer-to-peer multi-agent framework is proposed for managing the power sharing in microgrids with power electronic inverter-interfaced distributed energy resources (DERs). Recently, the introduction of electric vehicles (EVs) has gained much popularity by offering vehicle-to-home (V2H) technologies to support the sustainable operation of microgrids. Since microgrids often exhibit volatile characteristics due to natural intermittency and uncertainty, it is necessary to maintain the balancing of generation and demand through the proper management of power sharing. Therefore, the main purpose of this paper is to design an agent-based control framework to ensure the coordinated power management within the microgrids through effective utilization of EVs. The required agent communication framework is adhered to the graph theory where the control agents interact with each other using local as well as neighboring information and their distributed coordination effectively steers the proportional sharing of real and reactive powers among the inverter-interfaced EVs to maintain the stability of microgrids. The well known Ziegler-Nichols method is used to tune the proportional-integral (PI) controller of the inner current control loop within each individual control agent to perform necessary shared control tasks. A microgrid with solar photovoltaic (PV) and V2H systems is chosen to illustrate the results and it is seen that the proposed scheme improves the system performance in a smarter way through information exchange. Furthermore, the proposed framework is also validated by a comparison with an existing traditional approach and it is found that, the proposed scheme provides excellent robust and faster performance.

Original languageEnglish
Pages (from-to)20-32
Number of pages13
JournalEnergy Conversion and Management
Volume139
DOIs
Publication statusPublished - 1 May 2017
Externally publishedYes

Keywords

  • Electric vehicles
  • Multi-agent system
  • Distributed control
  • Inverters
  • Graph theory

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