Distributed Agent-Based Coordinated Control for Microgrid Management



Due to the ever-growing global concerns of climate changes and environmental issues, renewable energies along with the distributed energy resources (DERs) are becoming popular day by day for the sustainable operation of microgrids. Since a number of energy sources are connected to microgrids, multiple power electronic devices, such as inverters, are interfaced with those sources to support the DC–AC and AC–DC conversion. Multiple inverters installed with DERs are very effective in order to deliver adequate amount of energy from different sources to the end users. However, the control and management of multiple inverters adversely suffer from limited system stability due to the lack of proper coordination among different components of microgrids. Moreover, due to the requirements of sustainable operation of microgrids and intermittent characteristics of renewable energy, efficient coordinated control is still quite difficult to maintain the balance between the generations and demands. In order to deliver a reliable energy supply to microgrids, inverters need to be controlled in a more efficient way. Moreover, the integration of battery energy storage systems (BESSs) adds a new dimension to the reliable operation of microgrids which also possesses a difficulty to manage power sharing during the change in network configurations. In this chapter, a communication-assisted distributed multi-agent system (MAS)-based control scheme is proposed to effectively control and manage the inverter-dominated microgrids with solar photovoltaic (PV) systems and BESSs. The MAS establishes the coordination between the power sharing and energy management through agent communication and further ensures the sustainable operation of microgrids by effectively controlling the inverters.


Microgrid Multi-agent system Inverter PV system BESS Distributed control 


  1. 1.
    M. Mahmud, H. Pota, and M. Hossain, “Nonlinear current control scheme for a single-phase grid-connected photovoltaic system,” IEEE Trans. on Sustainable Energy 5(1):218–227, 2014.Google Scholar
  2. 2.
    A. Zahedi, “Development of an economical model to determine an appropriate feed-in tariff for grid-connected solar PV electricity in all states of Australia,” Renewable and Sustainable Energy Reviews 13(4):871–878, 2009.Google Scholar
  3. 3.
    J. Yang, Z. Zeng, Y. Tang, J. Yan, H. He, and Y. Wu, “Load frequency control in isolated micro-grids with electrical vehicles based on multivariable generalized predictive theory,” Energies 8(3):21–45, 2015.Google Scholar
  4. 4.
    J. Schiffer, R. Ortega, A. Astolfi, J. Raisch, and T. Sezi, “Conditions for stability of droop-controlled inverter-based microgrids,” Automatica 50(10):2457–2469, 2014.Google Scholar
  5. 5.
    Y. Mou, H. Xing, Z. Lin, and M. Fu, “Decentralized optimal demand-side management for PHEV charging in a smart grid,” IEEE Trans. on Smart Grid 6(2):726–736, 2015.Google Scholar
  6. 6.
    A. Arancibia, K. Strunz, and F. Mancilla-David, “A supervisory energy management control strategy in a battery/ultracapacitor hybrid energy storage system,” IEEE Trans. on Transportation Electrification 1(3):223–231, 2015.Google Scholar
  7. 7.
    T. Caldognetto, P. Tenti, A. Costabeber, and P. Mattavelli, “Improving microgrid performance by cooperative control of distributed energy sources,” IEEE Trans. on Industry Applications 50(6):3921–3930, 2014.Google Scholar
  8. 8.
    W. Liu,W. Gu, W. Sheng, X. Meng, Z.Wu, and W. Chen, “Decentralized multi-agent system-based cooperative frequency control for autonomous microgrids with communication constraints,” IEEE Trans. on Sustainable Energy 5(2):446–456, 2014.Google Scholar
  9. 9.
    C. Colson and M. Nehrir, “Comprehensive real-time microgrid power management and control with distributed agents,” IEEE Trans. on Smart Grid 4(1):617–627, 2013.Google Scholar
  10. 10.
    T. Tsuji, T. Oyama, T. Hashiguchi, T. Goda, K. Horiuchi, S. Tange, T. Shinji, and S. Tsujita, Autonomous Decentralized Voltage Profile Control Method in Future Distribution Network using Distributed Generators. InTech, 2011, ch. 11:193–220.Google Scholar
  11. 11.
    Q. Sun, R. Han, H. Zhang, J. Zhou, and J. Guerrero, “A multiagent-based consensus algorithm for distributed coordinated control of distributed generators in the energy internet,” IEEE Trans. on Smart Grid 6(6):3006–3019, 2015.Google Scholar
  12. 12.
    C.-H. Yoo, I.-Y. Chung, H.-J. Lee, and S.-S. Hong, “Intelligent control of battery energy storage for multi-agent based microgrid energy management,” Energies 6(10):4956–4979, 2013.Google Scholar
  13. 13.
    E. Polymeneas and M. Benosman, “Multi-agent coordination of DG inverters for improving the voltage profile of the distribution grid,” in IEEE PES General Meeting 2014:1–5.Google Scholar
  14. 14.
    M. Kouluri and R. Pandey, “Intelligent agent based micro grid control,” in International Conference on Intelligent Agent and Multi-Agent Systems (IAMA) 2011:62–66.Google Scholar
  15. 15.
    A. Bidram, A. Davoudi, F. Lewis, and J. Guerrero, “Distributed cooperative secondary control of microgrids using feedback linearization,” IEEE Trans. on Power Systems 28(3):3462–3470, 2013.Google Scholar
  16. 16.
    M.-T. Kuo and S.-D. Lu, “Design and implementation of real-time intelligent control and structure based on multi-agent systems in microgrids,” Energies 6(11): 6045–6059, 2013.Google Scholar
  17. 17.
    A. Werth, N. Kitamura, and K. Tanaka, “Conceptual study for open energy systems: Distributed energy network using interconnected DC nanogrids,” IEEE Trans. on Smart Grid 6(4):1621–1630, 2015.Google Scholar
  18. 18.
    M. D. Galus, R. A. Waraich, and G. Andersson, “Predictive, distributed, hierarchical charging control of PHEVs in the distribution system of a large urban area incorporating a multi agent transportation simulation,” in Power Systems Computations Conference (PSCC) 2011:1–7.Google Scholar
  19. 19.
    L. Herrera, E. Inoa, F. Guo, J. Wang, and H. Tang, “Small-signal modeling and networked control of a PHEV charging facility,” IEEE Trans. on Industry Applications 50(2):1121–1130, 2014.Google Scholar
  20. 20.
    J. Oyarzabal, J. Jimeno, J. Ruela, A. Engler, and C. Hardt, “Agent based micro grid management system,” in International Conference on Future Power Systems 2005:1–6.Google Scholar
  21. 21.
    Z. Xiaoyan, L. Tianqi, and L. Xueping, “Multi-agent based microgrid coordinated control,” Energy Procedia 14:154–159, 2012.Google Scholar
  22. 22.
    M. Ceraolo, “New dynamical models of lead-acid batteries,” IEEE Trans. on Power Systems 15(4)1184–1190, 2000.Google Scholar
  23. 23.
    M. S. Rahman, M. A. Mahmud, H. R. Pota, and M. J. Hossain, “Distributed multi-agent scheme for reactive power management with renewable energy,” Energy Conversion and Management 88:573–581, 2014.Google Scholar
  24. 24.
    T. Aziz, T. K. Saha, and N. Mithulanathan, “Distributed generators placement for loadability enhancement based on reactive power margin,” 9th International Power & Energy Conference (IPEC) 2010: 740–745.Google Scholar
  25. 25.
    M. S. Rahman, “Distributed Multi-Agent Approach for Enhancing Stability and Security of Emerging Smart Grids,” PhD Thesis, The University of new South Wales, 2014.Google Scholar
  26. 26.
    W. M. and W. G., Intelligent agents. MIT press, Cambridge, 1999, ch. Multiagent systems, pp. 3–51.Google Scholar
  27. 27.
    S. D. J. McArthur, E. Davidson, J. Hossack, and J. McDonald, “Automating power system fault diagnosis through multi-agent system technology,” in 37th Annual Hawaii International Conference on System Sciences 2004: 1–8.Google Scholar
  28. 28.
    F. LN, “Entertaining agents: a sociological case study” in 1st international conference on autonomous agents, 1997: 122–129.Google Scholar
  29. 29.
    M. Rahman, M. Mahmud, H. Pota, M. Hossain, and T. Orchi, “Distributed Multi-Agent-Based Protection Scheme for Transient Stability Enhancement in Power Systems,” Int. Journal of Emerging Electric Power Systems 16 (2):117–129, 2015.Google Scholar
  30. 30.
    S. McArthur, E. Davidson, V. Catterson, A. Dimeas, N. Hatziargyriou, F. Ponci, and T. Funabashi, “Multi-agent systems for power engineering applications part I: Concepts, approaches, and technical challenges,” IEEE Trans. on Power System 22:1743–1752, 2007.Google Scholar
  31. 31.
    M. S. Rahman, M. A. Mahmud, A. M. T. Oo, and T. F. Orchi, “Distributed agent-based control scheme for single-phase parallel inverters in microgrids with photovoltaic systems,” Australasian Universities Power Engineering Conference (AUPEC) 2015: 1–6.Google Scholar
  32. 32.
    M. Rahman, M. Mahmud, H. Pota, and M. Hossain, “A multi-agent approach for enhancing transient stability of smart grids,” Int. Journal of Electrical Power & Energy Systems 67:488–500, 2015.Google Scholar
  33. 33.
    D. Zammit, C. Spiteri Staines, M. Apap, “Comparison between PI and PR Current Controllers in Grid Connected PV Inverters”, Int. Journal of Electrical, Computer, Energetic, Electronic and Communication Engineering 8(2):221–226, 2014.Google Scholar

Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  1. 1.Faculty of Science, Engineering and Built Environment, School of EngineeringDeakin UniversityGeelongAustralia

Personalised recommendations