A journal of IEEE and CAA , publishes high-quality papers in English on original theoretical/experimental research and development in all areas of automation
Advanced Search
Volume 11 Issue 12
Dec.  2024

IEEE/CAA Journal of Automatica Sinica

  • JCR Impact Factor: 15.3, Top 1 (SCI Q1)
    CiteScore: 23.5, Top 2% (Q1)
    Google Scholar h5-index: 77， TOP 5
Turn off MathJax
Article Contents
Article Navigation >  IEEE/CAA Journal of Automatica Sinica  > 2024  >  11(12): 2396-2407
F. Yang, J. Liu, and  X. Guan,  “Distributed fixed-time optimal energy management for microgrids based on a dynamic event-triggered mechanism,” IEEE/CAA J. Autom. Sinica, vol. 11, no. 12, pp. 2396–2407, Dec. 2024. doi: 10.1109/JAS.2024.124686
Citation: F. Yang, J. Liu, and  X. Guan,  “Distributed fixed-time optimal energy management for microgrids based on a dynamic event-triggered mechanism,” IEEE/CAA J. Autom. Sinica, vol. 11, no. 12, pp. 2396–2407, Dec. 2024. doi: 10.1109/JAS.2024.124686
shu

Distributed Fixed-Time Optimal Energy Management for Microgrids Based on a Dynamic Event-Triggered Mechanism

doi: 10.1109/JAS.2024.124686
Funds:  This work was supported by the National Natural Science Foundation of China (62473316, 62073269), the Natural Science Foundation of Chongqing, China (CSTB2022NSCQ-MSX0963), Guangdong Basic and Applied Basic Research Foundation (2023A1515011220), and Aeronautical Science Foundation of China (2020Z034053002)
More Information
    Abstract
  • The article investigates the optimal energy management (OEM) problem for microgrids. To figure out the problem in fixed time and alleviate communication load with limited resources, this article devises a novel fixed-time stability lemma and an event-triggered (ET) fixed-time distributed OEM approach. Using Lyapunov stability theory, the distributed approach has been proven to converge in fixed time and the upper bound on convergence time can be derived without dependence on the initial states. The dynamic ET method is raised to dynamically adjust the triggering threshold and reduce communication redundancy. In addition, Zeno behavior is avoided. Simulations are given to show the effectiveness and advantage of the designed distributed OEM method.

     

    • FullText(HTML)
  • loading
    • References(36)
  • [1]
    J. Qin, Y. Wan, X. Yu, F. Li, and C. Li, “Consensus-based distributed coordination between economic dispatch and demand response,” IEEE Trans. Smart Grid, vol. 10, no. 4, pp. 3709–3719, 2019. doi: 10.1109/TSG.2018.2834368
    [2]
    Y. Song, J. Cao, and L. Rutkowski, “A fixed-time distributed optimization algorithm based on event-triggered strategy,” IEEE Trans. Network Science and Engineering, vol. 9, no. 3, pp. 1154–1162, 2022. doi: 10.1109/TNSE.2021.3133541
    [3]
    J. Peng, B. Fan, Z. Tu, W. Zhang, and W. Liu, “Distributed periodic event-triggered optimal control of DC microgrids based on virtual incremental cost,” IEEE/CAA J. Autom. Sinica, vol. 9, no. 4, pp. 624–634, 2022. doi: 10.1109/JAS.2022.105452
    [4]
    X. Liu, T. Zhao, H. Deng, P. Wang, J. Liu, and F. Blaabjerg, “Microgrid energy management with energy storage systems: A review,” CSEE J. Power and Energy Systems, vol. 9, no. 2, pp. 483–504, 2023.
    [5]
    S. Yang, S. Tan, and J.-X. Xu, “Consensus based approach for economic dispatch problem in a smart grid,” IEEE Trans. Power Systems, vol. 28, no. 4, pp. 4416–4426, 2013. doi: 10.1109/TPWRS.2013.2271640
    [6]
    Y. Xu and Z. Li, “Distributed optimal resource management based on the consensus algorithm in a microgrid,” IEEE Trans. Industrial Electronics, vol. 62, no. 4, pp. 2584–2592, 2015. doi: 10.1109/TIE.2014.2356171
    [7]
    Y. Yan, Z. Chen, V. Varadharajan, M. J. Hossain, and G. E. Town, “Distributed consensus-based economic dispatch in power grids using the paillier cryptosystem,” IEEE Trans. Smart Grid, vol. 12, no. 4, pp. 3493–3502, 2021. doi: 10.1109/TSG.2021.3063712
    [8]
    H. Tu, Y. Du, H. Yu, S. Meena, X. Lu, and S. Lukic, “Distributed economic dispatch for microgrids tracking ramp power commands,” IEEE Trans. Smart Grid, vol. 14, no. 1, pp. 94–111, 2023. doi: 10.1109/TSG.2022.3189534
    [9]
    M. Firouzbahrami and A. Nobakhti, “Finite-time distributed economic dispatch over network systems with coupled local costs,” IEEE Control Systems Letters, vol. 7, pp. 325–330, 2023. doi: 10.1109/LCSYS.2022.3188743
    [10]
    L. Ding, L. Wang, G. Yin, W. Zheng, and Q.-L. Han, “Distributed energy management for smart grids with an event-triggered communication scheme,” IEEE Trans. Control Systems Technology, vol. 27, no. 5, pp. 1950–1961, 2019. doi: 10.1109/TCST.2018.2842208
    [11]
    Y. Li, H. Zhang, X. Liang, and B. Huang, “Event-triggered-based distributed cooperative energy management for multienergy systems,” IEEE Trans. Industrial Informatics, vol. 15, no. 4, pp. 2008–2022, 2019. doi: 10.1109/TII.2018.2862436
    [12]
    T. Zhao, Z. Li, and Z. Ding, “Consensus-based distributed optimal energy management with less communication in a microgrid,” IEEE Trans. Industrial Informatics, vol. 15, no. 6, pp. 3356–3367, 2019. doi: 10.1109/TII.2018.2871562
    [13]
    H. Huang, M. Shi, and Q. Xu, “Consensus-based economic dispatch algorithm in a microgrid via distributed event-triggered control,” Int. J. Systems Science, vol. 51, no. 15, pp. 3044–3054, 2020. doi: 10.1080/00207721.2020.1808110
    [14]
    A. Girard, “Dynamic triggering mechanisms for event-triggered control,” IEEE Trans. Automatic Control, vol. 60, no. 7, pp. 1992–1997, 2015. doi: 10.1109/TAC.2014.2366855
    [15]
    W. He, B. Xu, Q.-L. Han, and F. Qian, “Adaptive consensus control of linear multiagent systems with dynamic event-triggered strategies,” IEEE Trans. Cybern., vol. 50, no. 7, pp. 2996–3008, 2020. doi: 10.1109/TCYB.2019.2920093
    [16]
    Y. Li, D. W. Gao, W. Gao, H. Zhang, and J. Zhou, “Double-mode energy management for multi-energy system via distributed dynamic event-triggered Newton-Raphson algorithm,” IEEE Trans. Smart Grid, vol. 11, no. 6, pp. 5339–5356, 2020. doi: 10.1109/TSG.2020.3005179
    [17]
    G. Wang, X. Yang, W. Cai, and Y. Zhang, “Event-triggered online energy flow control strategy for regional integrated energy system using Lyapunov optimization,” Int. J. Electrical Power & Energy Systems, vol. 125, p. 106451, 2021.
    [18]
    W. Kang, M. Chen, Y. Guan, L. Tang, J. C. Vasquez, and J. M. Guerrero, “Distributed event-triggered optimal control method for heterogeneous energy storage systems in smart grid,” IEEE Trans. Sustainable Energy, vol. 13, no. 4, pp. 1944–1956, 2022. doi: 10.1109/TSTE.2022.3176741
    [19]
    N. Zhang, Q. Sun, L. Yang, and Y. Li, “Event-triggered distributed hybrid control scheme for the integrated energy system,” IEEE Trans. Industrial Informatics, vol. 18, no. 2, pp. 835–846, 2022. doi: 10.1109/TII.2021.3075718
    [20]
    Z. Dong, S. Mao, M. Perc, W. Du, and Y. Tang, “A distributed dynamic event-triggered algorithm with linear convergence rate for the economic dispatch problem,” IEEE Trans. Network Science and Engineering, vol. 10, no. 1, pp. 500–513, 2023. doi: 10.1109/TNSE.2022.3216572
    [21]
    X. Li, C. Dong, W. Jiang, and X. Wu, “Distributed dynamic event-triggered power management strategy for global economic operation in high-power hybrid AC/DC microgrids,” IEEE Trans. Sustainable Energy, vol. 13, no. 3, pp. 1830–1842, 2022. doi: 10.1109/TSTE.2022.3172703
    [22]
    Y. Yuan, W. He, Y.-C. Tian, W. Du, and F. Qian, “Distributed discrete-time optimization over directed networks: A dynamic event-triggered algorithm,” Information Sciences, vol. 642, p. 119168, 2023. doi: 10.1016/j.ins.2023.119168
    [23]
    J. Liu, C. Wang, J. Liu, and P. Xie, “Event-triggered distributed control strategy for multi-energy systems based on multi-objective dispatch,” Energy, vol. 263, p. 125980, 2023. doi: 10.1016/j.energy.2022.125980
    [24]
    G. Chen, J. Ren, and E. N. Feng, “Distributed finite-time economic dispatch of a network of energy resources,” IEEE Trans. Smart Grid, vol. 8, no. 2, pp. 822–832, 2016.
    [25]
    L.-N. Liu and G.-H. Yang, “Distributed fixed-time optimal resource management for microgrids,” IEEE Trans. Automation Science and Engineering, vol. 20, no. 1, pp. 404–412, 2023. doi: 10.1109/TASE.2022.3155163
    [26]
    H. Dai, J. Jia, L. Yan, X. Fang, and W. Chen, “Distributed fixed-time optimization in economic dispatch over directed networks,” IEEE Trans. Industrial Informatics, vol. 17, no. 5, pp. 3011–3019, 2021. doi: 10.1109/TII.2020.3010282
    [27]
    Z. Li and G. Chen, “Fixed-time consensus based distributed economic generation control in a smart grid,” Int. J. Electrical Power & Energy Systems, vol. 134, p. 107437, 2022.
    [28]
    G. Chen and Z. Guo, “Initialization-free distributed fixed-time convergent algorithms for optimal resource allocation,” IEEE Trans. Systems, Man, and Cybern.: Systems, vol. 52, no. 2, pp. 845–854, 2022. doi: 10.1109/TSMC.2020.3005169
    [29]
    F. Yang, J. Liu, and M. Wang, “Fixed-time distributed economic dispatch based on event-triggered strategy,” in Proc. 7th Int. Conf. Automation, Control and Robotics Engineering, 2022, pp. 364–368.
    [30]
    H. Liu, H. Fan, B. Wang, L. Liu, and S. Lei, “Event-triggered scheme for finite-time distributed economic dispatch in smart grids,” J. Franklin Institute, vol. 359, no. 18, pp. 10602–10627, 2022. doi: 10.1016/j.jfranklin.2022.10.031
    [31]
    J. Liu, F. Yang, and M. Wang, “Distributed fixed-time optimal resource management for microgrids based on event-triggered mechanism,” in Proc. 42nd Chinese Control Conf., 2023, pp. 20927−2097.
    [32]
    B. Huang, Y. Liu, L. Glielmo, and W. Gui, “Fixed-time distributed robust optimization for economic dispatch with event-triggered intermittent control,” Science China Technological Sciences, vol. 66, no. 5, pp. 1385–1396, 2023. doi: 10.1007/s11431-022-2352-9
    [33]
    L.-N. Liu, G.-H. Yang, and S. Wasly, “Distributed predefined-time dual-mode energy management for a microgrid over event-triggered communication,” IEEE Trans. Industrial Informatics, vol. 20, no. 3, pp. 3295–3305, 2024. doi: 10.1109/TII.2023.3304025
    [34]
    A. Polyakov, “Nonlinear feedback design for fixed-time stabilization of linear control systems,” IEEE Trans. Autom. Control, vol. 57, no. 8, pp. 2106–2110, 2012. doi: 10.1109/TAC.2011.2179869
    [35]
    C. Chen, L. Li, H. Peng, Y. Yang, L. Mi, and H. Zhao, “A new fixed-time stability theorem and its application to the fixed-time synchronization of neural networks,” Neural Networks, vol. 123, pp. 412–419, 2020. doi: 10.1016/j.neunet.2019.12.028
    [36]
    R. Olfati-Saber and R. M. Murray, “Consensus problems in networks of agents with switching topology and time-delays,” IEEE Trans. Autom. Control, vol. 49, no. 9, pp. 1520–1533, 2004. doi: 10.1109/TAC.2004.834113
    • Related Articles
    • Supplements(0)

Catalog

    通讯作者: 陈斌, bchen63@163.com
    • 1. 

      沈阳化工大学材料科学与工程学院 沈阳 110142

    1. 本站搜索
    2. 百度学术搜索
    3. 万方数据库搜索
    4. CNKI搜索

    Figures(10)  / Tables(2)

    Get Citation
    PDF
    XML

    Article Metrics

    Article views (429) PDF downloads(88) Cited by()

    Highlights

    • By generalizing the existing fixed-time stability theory, a new fixed-time lemma is raised and a novel settling time upper bound is obtained, which helps accelerate algorithm convergence
    • A dynamic ET communication scheme for a fixed-time distributed OEM method is devised, in which the static ET threshold is replaced with an internal dynamic variable that can change with measurement errors. It has advantages over static ET schemes in terms of reducing triggering times
    • In contrast to the finite-time optimization algorithm, the proposed fixed-time distributed optimization approach can solve the OEM problem in fixed time, of which convergence time on the presented distributed OEM algorithm can be estimated independent of any initial states

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return