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An MAS based energy management system for a stand-alone microgrid at high altitude

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Listed:
  • Zhao, Bo
  • Xue, Meidong
  • Zhang, Xuesong
  • Wang, Caisheng
  • Zhao, Junhui

Abstract

A multi-agent system based energy management system (EMS) is proposed in this paper for implementing a PV-small hydro hybrid microgrid (MG) at high altitude. Based on local information, the distributed generation (DG) sources in the MG are controlled via the EMS to achieve efficient and stable system operation. Virtual bidding is used to quickly establish the scheduling of system operation and capacity reserve. In addition, real-time power dispatches are carried out through model predictive control to balance load demand and power generation in the MG. The dynamic model and the energy management strategy of the MG have been simulated on a RTDS–PXI joint real-time simulation platform. The simulation results show that the proposed energy management and control strategy can optimally dispatch the DG sources in the MG to achieve economic and secure operations of the whole system.

Suggested Citation

  • Zhao, Bo & Xue, Meidong & Zhang, Xuesong & Wang, Caisheng & Zhao, Junhui, 2015. "An MAS based energy management system for a stand-alone microgrid at high altitude," Applied Energy, Elsevier, vol. 143(C), pages 251-261.
  • Handle: RePEc:eee:appene:v:143:y:2015:i:c:p:251-261
    DOI: 10.1016/j.apenergy.2015.01.016
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    References listed on IDEAS

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    1. Jun, Zeng & Junfeng, Liu & Jie, Wu & Ngan, H.W., 2011. "A multi-agent solution to energy management in hybrid renewable energy generation system," Renewable Energy, Elsevier, vol. 36(5), pages 1352-1363.
    2. Li, Gong & Shi, Jing, 2012. "Agent-based modeling for trading wind power with uncertainty in the day-ahead wholesale electricity markets of single-sided auctions," Applied Energy, Elsevier, vol. 99(C), pages 13-22.
    3. Baziar, Aliasghar & Kavousi-Fard, Abdollah, 2013. "Considering uncertainty in the optimal energy management of renewable micro-grids including storage devices," Renewable Energy, Elsevier, vol. 59(C), pages 158-166.
    4. Chen, Jiayu & Jain, Rishee K. & Taylor, John E., 2013. "Block Configuration Modeling: A novel simulation model to emulate building occupant peer networks and their impact on building energy consumption," Applied Energy, Elsevier, vol. 105(C), pages 358-368.
    5. Kuznetsova, Elizaveta & Li, Yan-Fu & Ruiz, Carlos & Zio, Enrico, 2014. "An integrated framework of agent-based modelling and robust optimization for microgrid energy management," Applied Energy, Elsevier, vol. 129(C), pages 70-88.
    6. Zheng, Menglian & Meinrenken, Christoph J. & Lackner, Klaus S., 2014. "Agent-based model for electricity consumption and storage to evaluate economic viability of tariff arbitrage for residential sector demand response," Applied Energy, Elsevier, vol. 126(C), pages 297-306.
    7. Kyriakarakos, George & Piromalis, Dimitrios D. & Dounis, Anastasios I. & Arvanitis, Konstantinos G. & Papadakis, George, 2013. "Intelligent demand side energy management system for autonomous polygeneration microgrids," Applied Energy, Elsevier, vol. 103(C), pages 39-51.
    8. Lagorse, Jeremy & Paire, Damien & Miraoui, Abdellatif, 2010. "A multi-agent system for energy management of distributed power sources," Renewable Energy, Elsevier, vol. 35(1), pages 174-182.
    9. Roche, Robin & Idoumghar, Lhassane & Suryanarayanan, Siddharth & Daggag, Mounir & Solacolu, Christian-Anghel & Miraoui, Abdellatif, 2013. "A flexible and efficient multi-agent gas turbine power plant energy management system with economic and environmental constraints," Applied Energy, Elsevier, vol. 101(C), pages 644-654.
    10. Zhao, Bo & Zhang, Xuesong & Li, Peng & Wang, Ke & Xue, Meidong & Wang, Caisheng, 2014. "Optimal sizing, operating strategy and operational experience of a stand-alone microgrid on Dongfushan Island," Applied Energy, Elsevier, vol. 113(C), pages 1656-1666.
    11. Wang, Zhu & Wang, Lingfeng & Dounis, Anastasios I. & Yang, Rui, 2012. "Multi-agent control system with information fusion based comfort model for smart buildings," Applied Energy, Elsevier, vol. 99(C), pages 247-254.
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