IDEAS home Printed from https://ideas.repec.org/a/eee/energy/v101y2016icp34-51.html
   My bibliography  Save this article

Virtual generation tribe based robust collaborative consensus algorithm for dynamic generation command dispatch optimization of smart grid

Author

Listed:
  • Zhang, Xiaoshun
  • Yu, Tao
  • Yang, Bo
  • Li, Li

Abstract

This paper proposes a decentralized collaborative control framework of autonomous VGT (virtual generation tribe) for smart grid. A VGT-CCA (VGT based collaborative consensus algorithm) is firstly developed to solve the dynamic GCD (generation command dispatch) optimization of the AGC (automatic generation control) under an ideal communication network. Then a novel CCA VGT-RCCA (VGT based robust CCA) is designed by introducing the consensus gain functions and virtual consensus variables, which provides significant robustness to a practical communication network consisted with switching topology, transmission delay and noise. The performance of VGT-CCA and VGT-RCCA has been evaluated on a typical two-area load frequency control model and the China southern power grid model, respectively. Simulation results verify the effectiveness of the proposed algorithms.

Suggested Citation

  • Zhang, Xiaoshun & Yu, Tao & Yang, Bo & Li, Li, 2016. "Virtual generation tribe based robust collaborative consensus algorithm for dynamic generation command dispatch optimization of smart grid," Energy, Elsevier, vol. 101(C), pages 34-51.
    • Handle: RePEc:eee:energy:v:101:y:2016:i:c:p:34-51
    DOI: 10.1016/j.energy.2016.02.009
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0360544216300500
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.energy.2016.02.009?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Lund, Henrik & Andersen, Anders N. & Østergaard, Poul Alberg & Mathiesen, Brian Vad & Connolly, David, 2012. "From electricity smart grids to smart energy systems – A market operation based approach and understanding," Energy, Elsevier, vol. 42(1), pages 96-102.
    2. Personal, Enrique & Guerrero, Juan Ignacio & Garcia, Antonio & Peña, Manuel & Leon, Carlos, 2014. "Key performance indicators: A useful tool to assess Smart Grid goals," Energy, Elsevier, vol. 76(C), pages 976-988.
    3. Coronado Mondragon, Adrian E. & Coronado, Etienne S. & Coronado Mondragon, Christian E., 2015. "Defining a convergence network platform framework for smart grid and intelligent transport systems," Energy, Elsevier, vol. 89(C), pages 402-409.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Zhang, Xiaoshun & Chen, Yixuan & Yu, Tao & Yang, Bo & Qu, Kaiping & Mao, Senmao, 2017. "Equilibrium-inspired multiagent optimizer with extreme transfer learning for decentralized optimal carbon-energy combined-flow of large-scale power systems," Applied Energy, Elsevier, vol. 189(C), pages 157-176.
    2. Qu, Kaiping & Yu, Tao & Huang, Linni & Yang, Bo & Zhang, Xiaoshun, 2018. "Decentralized optimal multi-energy flow of large-scale integrated energy systems in a carbon trading market," Energy, Elsevier, vol. 149(C), pages 779-791.
    3. Yin, Linfei & Yu, Tao & Zhang, Xiaoshun & Yang, Bo, 2018. "Relaxed deep learning for real-time economic generation dispatch and control with unified time scale," Energy, Elsevier, vol. 149(C), pages 11-23.
    4. Wang, Haiyang & Zhang, Chenghui & Li, Ke & Ma, Xin, 2021. "Game theory-based multi-agent capacity optimization for integrated energy systems with compressed air energy storage," Energy, Elsevier, vol. 221(C).
    5. Xianyong Zhang & Yaohong Huang & Li Li & Wei-Chang Yeh, 2018. "Power and Capacity Consensus Tracking of Distributed Battery Storage Systems in Modular Microgrids," Energies, MDPI, vol. 11(6), pages 1-25, June.
    6. Liping Huang & Haisheng Li & Chun Sing Lai & Ahmed F. Zobaa & Bang Zhong & Zhuoli Zhao & Loi Lei Lai, 2024. "Electric Vehicle Cluster Scheduling Model for Distribution Systems Considering Reactive-Power Compensation of Charging Piles," Energies, MDPI, vol. 17(11), pages 1-24, May.
    7. Quan, Yue & Xi, Lei, 2024. "Smart generation system: A decentralized multi-agent control architecture based on improved consensus algorithm for generation command dispatch of sustainable energy systems," Applied Energy, Elsevier, vol. 365(C).
    8. Pengcheng Ni & Zhiyuan Ye & Can Cao & Zhimin Guo & Jian Zhao & Xing He, 2023. "Cooperative Game-Based Collaborative Optimal Regulation-Assisted Digital Twins for Wide-Area Distributed Energy," Energies, MDPI, vol. 16(6), pages 1-17, March.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Fotopoulou, Maria & Rakopoulos, Dimitrios & Petridis, Stefanos & Drosatos, Panagiotis, 2024. "Assessment of smart grid operation under emergency situations," Energy, Elsevier, vol. 287(C).
    2. Durmaz, Tunç, 2016. "Precautionary Storage in Electricity Markets," Discussion Papers 2016/5, Norwegian School of Economics, Department of Business and Management Science.
    3. Østergaard, P.A. & Lund, H. & Thellufsen, J.Z. & Sorknæs, P. & Mathiesen, B.V., 2022. "Review and validation of EnergyPLAN," Renewable and Sustainable Energy Reviews, Elsevier, vol. 168(C).
    4. Sayegh, M.A. & Danielewicz, J. & Nannou, T. & Miniewicz, M. & Jadwiszczak, P. & Piekarska, K. & Jouhara, H., 2017. "Trends of European research and development in district heating technologies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 68(P2), pages 1183-1192.
    5. Lund, Henrik & Thellufsen, Jakob Zinck & Sorknæs, Peter & Mathiesen, Brian Vad & Chang, Miguel & Madsen, Poul Thøis & Kany, Mikkel Strunge & Skov, Iva Ridjan, 2022. "Smart energy Denmark. A consistent and detailed strategy for a fully decarbonized society," Renewable and Sustainable Energy Reviews, Elsevier, vol. 168(C).
    6. Göransson, Lisa & Goop, Joel & Unger, Thomas & Odenberger, Mikael & Johnsson, Filip, 2014. "Linkages between demand-side management and congestion in the European electricity transmission system," Energy, Elsevier, vol. 69(C), pages 860-872.
    7. Persson, Urban & Wiechers, Eva & Möller, Bernd & Werner, Sven, 2019. "Heat Roadmap Europe: Heat distribution costs," Energy, Elsevier, vol. 176(C), pages 604-622.
    8. Funcke, Simon & Bauknecht, Dierk, 2016. "Typology of centralised and decentralised visions for electricity infrastructure," Utilities Policy, Elsevier, vol. 40(C), pages 67-74.
    9. Østergaard, Poul Alberg & Werner, Sven & Dyrelund, Anders & Lund, Henrik & Arabkoohsar, Ahmad & Sorknæs, Peter & Gudmundsson, Oddgeir & Thorsen, Jan Eric & Mathiesen, Brian Vad, 2022. "The four generations of district cooling - A categorization of the development in district cooling from origin to future prospect," Energy, Elsevier, vol. 253(C).
    10. David Drysdale & Brian Vad Mathiesen & Henrik Lund, 2019. "From Carbon Calculators to Energy System Analysis in Cities," Energies, MDPI, vol. 12(12), pages 1-21, June.
    11. Kovacic, Zora & Giampietro, Mario, 2015. "Empty promises or promising futures? The case of smart grids," Energy, Elsevier, vol. 93(P1), pages 67-74.
    12. Grundahl, Lars & Nielsen, Steffen & Lund, Henrik & Möller, Bernd, 2016. "Comparison of district heating expansion potential based on consumer-economy or socio-economy," Energy, Elsevier, vol. 115(P3), pages 1771-1778.
    13. Behnam Zakeri & Samuli Rinne & Sanna Syri, 2015. "Wind Integration into Energy Systems with a High Share of Nuclear Power—What Are the Compromises?," Energies, MDPI, vol. 8(4), pages 1-35, March.
    14. Biegel, Benjamin & Hansen, Lars Henrik & Stoustrup, Jakob & Andersen, Palle & Harbo, Silas, 2014. "Value of flexible consumption in the electricity markets," Energy, Elsevier, vol. 66(C), pages 354-362.
    15. Bertolini, Marina & D'Alpaos, Chiara & Moretto, Michele, 2018. "Do Smart Grids boost investments in domestic PV plants? Evidence from the Italian electricity market," Energy, Elsevier, vol. 149(C), pages 890-902.
    16. Bossink, Bart A.G., 2017. "Demonstrating sustainable energy: A review based model of sustainable energy demonstration projects," Renewable and Sustainable Energy Reviews, Elsevier, vol. 77(C), pages 1349-1362.
    17. Moreno, Blanca & López, Ana J. & García-Álvarez, María Teresa, 2012. "The electricity prices in the European Union. The role of renewable energies and regulatory electric market reforms," Energy, Elsevier, vol. 48(1), pages 307-313.
    18. Zhou, Kaile & Yang, Changhui & Shen, Jianxin, 2017. "Discovering residential electricity consumption patterns through smart-meter data mining: A case study from China," Utilities Policy, Elsevier, vol. 44(C), pages 73-84.
    19. Li, Ruonan & Mahalec, Vladimir, 2022. "Integrated design and operation of energy systems for residential buildings, commercial buildings, and light industries," Applied Energy, Elsevier, vol. 305(C).
    20. Xue, Puning & Zhou, Zhigang & Fang, Xiumu & Chen, Xin & Liu, Lin & Liu, Yaowen & Liu, Jing, 2017. "Fault detection and operation optimization in district heating substations based on data mining techniques," Applied Energy, Elsevier, vol. 205(C), pages 926-940.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:energy:v:101:y:2016:i:c:p:34-51. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/energy .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.