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A Distributed Control Strategy for Frequency Regulation in Smart Grids Based on the Consensus Protocol

Author

Listed:
  • Rong Fu

    (College of Automation, Nanjing University of Posts and Telecommunications, Nanjing 210023, China)

  • Yingjun Wu

    (College of Automation, Nanjing University of Posts and Telecommunications, Nanjing 210023, China)

  • Hailong Wang

    (College of Automation, Nanjing University of Posts and Telecommunications, Nanjing 210023, China)

  • Jun Xie

    (College of Automation, Nanjing University of Posts and Telecommunications, Nanjing 210023, China)

Abstract

This paper considers the problem of distributed frequency regulation based on the consensus control protocol in smart grids. In this problem, each system component is coordinated to collectively provide active power for the provision of ancillary frequency regulation service. Firstly, an approximate model is proposed for the frequency dynamic process. A distributed control algorithm is investigated, while each agent exchanges information with neighboring agents and performs behaviors based on communication interactions. The objective of each agent is to converge to a common state considering different dynamic load characteristics, and distributed frequency control strategy is developed to enable the agents to provide active power support. Then, the distributed proportional integral controllers with the state feedback are designed considering the consensus protocol with topology . The theory of distributed consensus protocol isfurther developed to prove the stability of the proposed control algorithm. Whenproperly controlled, the controllers can provide grid support services in a distributed manner that turn out the grid balanced globally. Finally, simulations of the proposed distributed control algorithm are tested to validate the availability of the proposed approach and the performance in the electrical networks.

Suggested Citation

  • Rong Fu & Yingjun Wu & Hailong Wang & Jun Xie, 2015. "A Distributed Control Strategy for Frequency Regulation in Smart Grids Based on the Consensus Protocol," Energies, MDPI, vol. 8(8), pages 1-15, July.
    • Handle: RePEc:gam:jeners:v:8:y:2015:i:8:p:7930-7944:d:53487
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    Citations

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    Cited by:

    1. Kaveh Dehghanpour & Christopher Colson & Hashem Nehrir, 2017. "A Survey on Smart Agent-Based Microgrids for Resilient/Self-Healing Grids," Energies, MDPI, vol. 10(5), pages 1-25, May.
    2. Woon-Gyu Lee & Thai-Thanh Nguyen & Hak-Man Kim, 2022. "Multiagent-Based Distributed Coordination of Inverter-Based Resources for Optimal Operation of Microgrids Considering Communication Failures," Energies, MDPI, vol. 15(10), pages 1-19, May.
    3. Timur Yunusov & Maximilian J. Zangs & William Holderbaum, 2017. "Control of Energy Storage," Energies, MDPI, vol. 10(7), pages 1-5, July.
    4. Su-Been Hong & Thai-Thanh Nguyen & Jinhong Jeon & Hak-Man Kim, 2020. "Distributed Operation of Microgrids Considering Secondary Frequency Restoration Based on the Diffusion Algorithm," Energies, MDPI, vol. 13(12), pages 1-14, June.

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