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Volume 11 Issue 5
May  2024

IEEE/CAA Journal of Automatica Sinica

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W. Chen and  G.-P. Liu,  “Privacy-preserving consensus-based distributed economic dispatch of smart grids via state decomposition,” IEEE/CAA J. Autom. Sinica, vol. 11, no. 5, pp. 1250–1261, May 2024. doi: 10.1109/JAS.2023.124122
Citation: W. Chen and  G.-P. Liu,  “Privacy-preserving consensus-based distributed economic dispatch of smart grids via state decomposition,” IEEE/CAA J. Autom. Sinica, vol. 11, no. 5, pp. 1250–1261, May 2024. doi: 10.1109/JAS.2023.124122

Privacy-Preserving Consensus-Based Distributed Economic Dispatch of Smart Grids via State Decomposition

doi: 10.1109/JAS.2023.124122
Funds:  This work was supported in part by Shenzhen Key Laboratory of Control Theory and Intelligent Systems (ZDSYS20220330161800001), the National Natural Science Foundation of China (62303210, 62173255, 62188101), the Guangdong Basic and Applied Basic Research Foundation of China (2022A1515110459), and the Shenzhen Science and Technology Program of China (RCBS20221008093348109)
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  • This paper studies the privacy-preserving distributed economic dispatch (DED) problem of smart grids. An autonomous consensus-based algorithm is developed via local data exchange with neighboring nodes, which covers both the islanded mode and the grid-connected mode of smart grids. To prevent power-sensitive information from being disclosed, a privacy-preserving mechanism is integrated into the proposed DED algorithm by randomly decomposing the state into two parts, where only partial data is transmitted. Our objective is to develop a privacy-preserving DED algorithm to achieve optimal power dispatch with the lowest generation cost under physical constraints while preventing sensitive information from being eavesdropped. To this end, a comprehensive analysis framework is established to ensure that the proposed algorithm can converge to the optimal solution of the concerned optimization problem by means of the consensus theory and the eigenvalue perturbation approach. In particular, the proposed autonomous algorithm can achieve a smooth transition between the islanded mode and the grid-connected mode. Furthermore, rigorous analysis is given to show privacy-preserving performance against internal and external eavesdroppers. Finally, case studies illustrate the feasibility and validity of the developed algorithm.

     

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  • [1]
    L. Ding, L. Y. Wang, G. Y. Yin, W. X. Zheng, and Q.-L. Han, “Distributed energy management for smart grids with an event-triggered communication scheme,” IEEE Trans. Control Syst. Tech., vol. 27, no. 5, pp. 1950–1961, Sept. 2019. doi: 10.1109/TCST.2018.2842208
    [2]
    Q. Xu, C. Yu, X. Yuan, Z. Fu, and H. Liu, “A privacy-preserving distributed subgradient algorithm for the economic dispatch problem in smart grid,” IEEE/CAA J. Autom. Sinica, vol. 10, no. 7, pp. 1625–1627, 2023. doi: 10.1109/JAS.2022.106028
    [3]
    Y. Chen, C. Li, D. Qi, Z. Li, Z. Wang, and J. Zhang, “Distributed event-triggered secondary control for islanded microgrids with proper trigger condition checking period,” IEEE Trans. Smart Grid, vol. 13, no. 2, pp. 837–848, Mar. 2022. doi: 10.1109/TSG.2021.3115180
    [4]
    W. Chen, Z. Wang, H. Dong, J. Mao, and G.-P. Liu, “Privacy-preserving distributed economic dispatch of microgrids over directed graphs via state decomposition: A fast consensus-based algorithm,” IEEE Trans. Ind. Inform., DOI: 10.1109/TII.2023.3321027.
    [5]
    A. Bidram and A. Davoudi, “Hierarchical structure of microgrids control system,” IEEE Trans. Smart Grid, vol. 3, no. 4, pp. 1963–1976, Dec. 2012. doi: 10.1109/TSG.2012.2197425
    [6]
    J. M. Guerrero, J. C. Vasquez, J. Matas, L. G. de Vicuna, and M. Castilla, “Hierarchical control of droop-controlled AC and DC micro-grids-a general approach toward standardization,” IEEE Trans. Indus. Electron., vol. 58, no. 1, pp. 158–172, Jan. 2011. doi: 10.1109/TIE.2010.2066534
    [7]
    G. Zhang, C. Li, D. Qi, and H. Xin, “Distributed estimation and secondary control of autonomous microgrid,” IEEE Trans. Power Syst., vol. 32, no. 2, pp. 989–998, Mar. 2017. doi: 10.1109/TPWRD.2016.2586963
    [8]
    W. Chen, L. Liu, and G.-P. Liu, “Privacy-preserving distributed economic dispatch of microgrids: A dynamic quantization based consensus scheme with Homomorphic encryption,” IEEE Trans. Smart Grid, vol. 14, no. 1, pp. 701–713, Jan. 2023. doi: 10.1109/TSG.2022.3189665
    [9]
    W. Chen and T. Li, “Distributed economic dispatch for energy internet based on multiagent consensus control,” IEEE Trans. Autom. Control, vol. 66, no. 1, pp. 137–152, Jan. 2021. doi: 10.1109/TAC.2020.2979749
    [10]
    G. Hug, S. Kar, and C. Wu, “Consensus + innovations approach for distributed multiagent coordination in a microgrid,” IEEE Trans. Smart Grid, vol. 6, no. 4, pp. 1893–1903, Jul. 2015. doi: 10.1109/TSG.2015.2409053
    [11]
    R. Wang, Q. Li, B. Zhang, and L. Wang, “Distributed consensus based algorithm for economic dispatch in a microgrid,” IEEE Trans. Smart Grid, vol. 10, no. 4, pp. 3630–3640, Jul. 2019. doi: 10.1109/TSG.2018.2833108
    [12]
    S. Yang, S. Tan, and J.-X. Xu, “Consensus based approach for economic dispatch problem in a smart grid,” IEEE Trans. Power Syst., vol. 28, no. 4, pp. 4416–4426, Nov. 2013. doi: 10.1109/TPWRS.2013.2271640
    [13]
    G. Chen, F. L. Lewis, E. N. Feng, and Y. Song, “Distributed optimal active power control of multiple generation systems,” IEEE Trans. Indus. Electron., vol. 62, no. 11, pp. 7079–7090, Nov. 2015. doi: 10.1109/TIE.2015.2431631
    [14]
    J. Qin, Y. Wan, X. Yu, and Y. Kang, “A Newton method-based distributed algorithm for multi-area economic dispatch,” IEEE Trans. Power Syst., vol. 35, no. 2, pp. 986–996, Mar. 2020. doi: 10.1109/TPWRS.2019.2943344
    [15]
    G. Chen and Q. Yang, “An ADMM-based distributed algorithm for economic dispatch in islanded microgrids,” IEEE Trans. Ind. Informat., vol. 14, no. 9, pp. 3892–3903, Sept. 2018. doi: 10.1109/TII.2017.2785366
    [16]
    D. Zhao, C. Zhang, X. Cao, C. Peng, B. Sun, K. Li, and Y. Li, “Differential privacy energy management for islanded microgrids with distributed consensus-based ADMM algorithm,” IEEE Trans. Control Syst. Tech., vol. 31, no. 3, pp. 1018–1031, May 2023. doi: 10.1109/TCST.2022.3208456
    [17]
    C. Li, X. Yu, W. Yu, T. Huang, and Z.-W. Liu, “Distributed event-triggered scheme for economic dispatch in smart grids,” IEEE Trans. Indus. Informat., vol. 12, no. 5, pp. 1775–1785, Oct. 2016. doi: 10.1109/TII.2015.2479558
    [18]
    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, Jul. 2019. doi: 10.1109/TSG.2018.2834368
    [19]
    W. Chen, Z. Wang, D. Ding, X. Yi, and Q.-L. Han, “Distributed state estimation over wireless sensor networks with energy harvesting sensors,” IEEE Trans. Cybern., vol. 53, no. 5, pp. 3311–3324, May 2023. doi: 10.1109/TCYB.2022.3179280
    [20]
    J. Wu, T. Yang, D. Wu, K. Kalsi, and K. H. Johansson, “Distributed optimal dispatch of distributed energy resources over lossy communication networks,” IEEE Trans. Smart Grid, vol. 8, no. 6, pp. 3125–3137, Nov. 2017. doi: 10.1109/TSG.2017.2720761
    [21]
    C. Zhao, J. He, P. Cheng, and J. Chen, “Analysis of consensus-based distributed economic dispatch under stealthy attacks,” IEEE Trans. Indus. Electron., vol. 64, no. 6, pp. 5107–5117, Jun. 2017. doi: 10.1109/TIE.2016.2638400
    [22]
    C. Zhao, J. He, P. Cheng, and J. Chen, “Consensus-based energy management in smart grid with transmission losses and directed communication,” IEEE Trans. Smart Grid, vol. 8, no. 5, pp. 2049–2061, Sept. 2017. doi: 10.1109/TSG.2015.2513772
    [23]
    A. Mandal, “Privacy preserving consensus-based economic dispatch in smart grid systems,” in Proc. Int. Conf. Future Netw. Syst. Security, 2016, pp. 98–110.
    [24]
    Z. Wang, M. Ma, Q. Zhou, L. Xiong, L. Wang, J. Wang, and J. Wang, “A privacy-preserving distributed control strategy in islanded AC microgrids,” IEEE Trans. Smart Grid, vol. 13, no. 5, Sept. 2022.
    [25]
    A. Wang, W. Liu, T. Dong, X. Liao, and T. Huang, “DisEHPPC: Enabling heterogeneous privacy-preserving consensus-based scheme for economic dispatch in smart grids,” IEEE Trans. Cybern., vol. 52, no. 6, pp. 5124–5135, Jun. 2022. doi: 10.1109/TCYB.2020.3027572
    [26]
    W. Chen, Z. Wang, J. Hu, and G.-P. Liu, “Differentially private average consensus with logarithmic dynamic encoding-decoding scheme,” IEEE Trans. Cybern., vol. 53, no. 10, pp. 6725–6736, Oct. 2023. doi: 10.1109/TCYB.2022.3233296
    [27]
    C. Zhao, J. Chen, J. He, and P. Cheng, “Privacy-preserving consensus-based energy management in smart grids,” IEEE Trans. Signal Process., vol. 66, no. 23, pp. 6162–6176, Dec. 2018. doi: 10.1109/TSP.2018.2872817
    [28]
    S. Mao, Y. Tang, Z. Dong, K. Dong, K. Meng, Z. Y. Dong, and F. Qian, “A privacy preserving distributed optimization algorithm for economic dispatch over time-varying directed networks,” IEEE Trans. Indus. Informat., vol. 17, no. 3, pp. 1689–1701, Mar. 2021. doi: 10.1109/TII.2020.2996198
    [29]
    D. Zhao, D. Liu, and L. Liu, “Distributed privacy preserving algorithm for economic dispatch over time-varying communication,” IEEE Trans. Power Syst., DOI: 10.1109/TPWRS.2023.3246998.
    [30]
    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, Jul. 2021. doi: 10.1109/TSG.2021.3063712
    [31]
    M. Ruan, H. Gao, and Y. Wang, “Secure and privacy-preserving consensus,” IEEE Trans. Autom. Control, vol. 64, no. 10, pp. 4035–4049, Oct. 2019. doi: 10.1109/TAC.2019.2890887
    [32]
    J. Hu, Q. Sun, R. Wang, B. Wang, M. Zhai, and H. Zhang, “Privacy-preserving sliding mode control for voltage restoration of AC microgrids based on output mask approach,” IEEE Trans. Indus. Infort., vol. 18, no. 10, pp. 6818–6827, Oct. 2022. doi: 10.1109/TII.2022.3141428
    [33]
    J. Hu, Q. Sun, M. Zhai, and B. Wang, “Privacy-preserving consensus strategy for secondary control in microgrids against multilink false data injection attacks,” IEEE Trans. Indus. Informat., vol. 19, no. 10, pp. 10334–10343, Oct. 2023. doi: 10.1109/TII.2023.3240878
    [34]
    Y. Wang, “Privacy-preserving average consensus via state decomposition,” IEEE Trans. Autom. Control, vol. 54, no. 11, pp. 4711–4716, Nov. 2019.
    [35]
    K. Zhang, Z. Li, Y. Wang, A. Louati, and J. Chen, “Privacy-preserving dynamic average consensus via state decomposition: Case study on multi-robot formation control,” Automatica, vol. 139, Feb. 2021, Art. no. 110182.
    [36]
    H. Tu, Y. Du, H. Yu, X. Lu, and S. Lukic, “Privacy-preserving robust consensus for distributed microgrid control applications,” IEEE Trans. Indus. Electron., vol. 71, no. 4, pp. 3684–3697, 2024.
    [37]
    J. Hu, Q. Sun, R. Wang, and Y. Wang, “An improved privacy-preserving consensus strategy for AC microgrids based on output mask approach and node decomposition mechanism,” IEEE Trans. Autom. Sci. Eng., DOI: 10.1109/TASE.2022.3217677.
    [38]
    A. J. Wood, B. F. Wollenberg, and G. B. Sheblé, Power Generation, Operation, and Control. Hoboken, NJ, USA: Wiley, 2013.
    [39]
    Y. Xiong and Z. Li, “Privacy preserving discrete-time average consensus by injecting edge-based perturbations,” in Proc. 40th Chinese Control Conf., 2021, pp. 5413–5418.
    [40]
    Z. Meng, R. Wei, and Y. Zheng, “Distributed finite-time attitude containment control for multiple rigid bodies,” Automatica, vol. 46, no. 12, pp. 2092–2099, Dec. 2010. doi: 10.1016/j.automatica.2010.09.005
    [41]
    W. Ren and R. W. Beard, Distributed Consensus in Multi-Vehicle Cooperative Control: Theory and Applications. Berlin, Germany: Springer-Verlag, 2008.
    [42]
    A. P. Seyranian and A. A. Mailybaev, Multiparameter Stability Theory With Mechanical Applications, ser. Stability, Vibration and Control of Systems. Singapore: World Scientific, 2004.
    [43]
    K. Cai and H. Ishii, “Average consensus on general digraph,” in Proc. IEEE Conf. Dec. Control, Orlando, FL, USA, 2010, pp. 1956–1961.
    [44]
    C. Ying, N. Zheng, Y. Wu, M. Xu, and W.-A. Zhang, “Privacy-preserving adaptive resilient consensus for multi-agent systems under cyber attacks,” IEEE Trans Indus. Informat., DOI: 10.1109/TII.2023.3280318.
    [45]
    M. H. Ullah, B. Babaiahgari, A. Alseyat, and J.-D. Park, “A computationally efficient consensus-based multiagent distributed EMS for DC microgrids,” IEEE Trans. Indus. Electron., vol. 68, no. 6, pp. 5425–5435, Jun. 2021. doi: 10.1109/TIE.2020.2992015
    [46]
    X. Chen, L. Huang, K. Ding, S. Dey, and L. Shi, “Privacy-preserving push-sum average consensus via state decomposition,” IEEE Trans. Autom. Control, vol. 68, no. 12, pp. 7974–7981, 2023.

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    Highlights

    • An autonomous consensus-based DED algorithm with a constant step size is developed, which can realize smooth transitions between the grid-connected and islanded modes of smart grids
    • A state-decomposition-based scheme is incorporated into the framework of the proposed DED algorithm, which is privacy-preserving against internal and external eavesdroppers
    • A comprehensive analysis is provided in terms of the convergence and the optimality of the proposed DED algorithm with and without state decomposition

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