Response hierarchical control strategy of communication data disturbance in micro-grid under the concept of cyber physical system

Response hierarchical control strategy of communication data disturbance in micro-grid under the concept of cyber physical system

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Communication data in the communication network of the islanded micro-grid can be disturbed in many ways, such as data attack or packet loss. To improve the control effect on the voltages and frequencies obtained by droop control of distributed energy resources (DERs) facing communication data disturbance (CDD), a response hierarchical control strategy is proposed in this study. Based on the concept of the cyber physical system, the control structure is divided into two layers: the cyber layer and physical layer. In the cyber layer, firstly, the effect of the CDD on the micro-grid system is analysed and then, an event-triggered data compensation method combining the back-propagation neural network and extreme learning machine is proposed in this layer to solve the problem of the CDD. In the physical layer, firstly, the droop control is used as the primary control to control the voltages and frequencies of DERs and then, a novel virtual leader-following consensus control method considering time-delay is proposed in this layer. Also, it is used to complete the secondary control of the voltage and frequency obtained by primary control. In the end, the simulation results confirm the effectiveness of the proposed hierarchical control strategy under CDD.


    1. 1)
      • 1. Kim, K.D., Kumar, P.R.: ‘Cyber-physical systems: a perspective at the centennial’, Proc. IEEE, 2012, 100, pp. 12871308.
    2. 2)
      • 2. Facchinetti, T., Vedova, M.L.D.: ‘Real-time modeling for direct load control in cyber-physical power systems’, IEEE Trans. Ind. Inf., 2011, 7, (4), pp. 689698.
    3. 3)
      • 3. Mo, Y., Kim, H.J., Brancik, K., et al: ‘Cyber-physical security of a smart grid infrastructure’, Proc. IEEE, 2012, 100, (1), pp. 195209.
    4. 4)
      • 4. Siddharth, S., Adam, H., Manimaran, G.: ‘Cyber-physical system security for the electric power grid’, Proc. IEEE, 2012, 100, (1), pp. 210224.
    5. 5)
      • 5. Flick, T., Morehouse, J.: ‘Securing the smart grid: next generation power grid security’ (Elsevier, Amsterdam, 2011), pp. 6769.
    6. 6)
      • 6. Nagi, J., Yap, K.S., Tiong, S.K., et al: ‘Improving SVM-based nontechnical loss detection in power utility using fuzzy inference system’, IEEE Trans. Power Deliv., 2011, 26, (2), pp. 12841285.
    7. 7)
      • 7. Angelos, E.W.S., Saavedra, O., Cortes, O., et al: ‘Detection and identification of abnormalities in customer consumptions in power distribution systems’, IEEE Trans. Power Deliv., 2011, 26, (4), pp. 24362442.
    8. 8)
      • 8. Xie, L., Mo, Y.L., Sinopoli, B.: ‘Integrity data attacks in power market operations’, IEEE Trans. Smart Grid, 2011, 2, (4), pp. 659666.
    9. 9)
      • 9. Kosut, O., Jia, L., Thomas, R.J., et al: ‘Malicious data attacks on the smart grid’, IEEE Trans. Smart Grid, 2011, 2, (4), pp. 645658.
    10. 10)
      • 10. Vahidreza, N., Ali, D., Frank, L., et al: ‘Distributed adaptive droop control for DC distribution systems’, IEEE Trans. Energy Convers., 2014, 29, (4), pp. 944956.
    11. 11)
      • 11. Dou, C.X., Zhang, Z.Q., Yue, D., et al: ‘Improved droop control based on virtual impedance and virtual power source in low-voltage microgrid’, IET Gener. Transm. Distrib., 2017, 11, (4), pp. 10461054.
    12. 12)
      • 12. Wu, T., Liu, Z., Liu, J., et al: ‘A unified virtual power decoupling method for droop-controlled parallel inverters in microgrids’, IEEE Trans. Power Electron., 2016, 31, (8), pp. 55875603.
    13. 13)
      • 13. Liu, W., Gu, W., Sheng, W.X., et al: ‘Decentralized multi-agent system based cooperative frequency control for autonomous microgrids with communication constraints’, IEEE Trans. Sustain. Energy, 2014, 5, (2), pp. 446456.
    14. 14)
      • 14. Wang, Z.G., Wu, W.C., Zhang, B.M.: ‘A fully distributed power dispatch method for fast frequency recovery and minimal generation cost in autonomous microgrids’, IEEE Trans. Smart Grid, 2016, 7, (1), pp. 1931.
    15. 15)
      • 15. Wang, P.B., Lu, X.N., Yang, X., et al: ‘An improved distributed secondary control method for DC microgrids with enhanced dynamic current sharing performance’, IEEE Trans. Power Electron., 2016, 31, (9), pp. 66586673.
    16. 16)
      • 16. Bidram, A., Davoudi, A., Lewis, F.L., et al: ‘Secondary control of microgrids based on distributed cooperative control of multi-agent systems’, IET Gener. Transm. Distrib., 2013, 7, (8), pp. 822831.
    17. 17)
      • 17. Cameron, A.: ‘Secondary control strategies for frequency restoration in islanded microgrids with consideration of communication delays’, IEEE Trans. Smart Grid, 2016, 7, (3), pp. 14301441.
    18. 18)
      • 18. Shafiee, Q., Nasirian, V., Vasquez, J.C., et al: ‘A multi-functional fully distributed control framework for AC microgrids’, IEEE Trans. Smart Grid, 2018, 9, (4), pp. 32473258.
    19. 19)
      • 19. Rezaei, M.M., Soltani, J.: ‘Robust control of an islanded multi-bus microgrid based on input-output feedback linearisation and sliding mode control’, IET Gener. Transm. Distrib., 2015, 9, (15), pp. 24472454.
    20. 20)
      • 20. Baghaee, H.R., Mirsalim, M., Gharehpetian, G.B., et al: ‘A decentralized power management and sliding mode control strategy for hybrid AC/DC microgrids including renewable energy resources’, IEEE Trans. Ind. Inf., 2017, doi: 10.1109/TII.2017.2677943.
    21. 21)
      • 21. Ren, C.E., Chen, L., Chen, C.L.P.: ‘Adaptive fuzzy leader-following consensus control for stochastic multiagent systems with heterogeneous nonlinear dynamics’, IEEE Trans. Fuzzy Syst., 2017, 25, (1), pp. 181190.
    22. 22)
      • 22. You, X., Hua, C.C., Peng, D., et al: ‘Leader–following consensus for multi-agent systems subject to actuator saturation with switching topologies and time-varying delays’, IET Control Theory Applic., 2016, 10, (2), pp. 144150.
    23. 23)
      • 23. Hosseinzadeh, M., Salmasi, F.R.: ‘Power management of an isolated hybrid AC/DC micro-grid with fuzzy control of battery banks’, IET Renew. Power Gener., 2015, 9, (5), pp. 484493.
    24. 24)
      • 24. Hosseinzadeh, M., Salmasi, F.R.: ‘Robust optimal power management system for a hybrid AC/DC micro-grid’, IEEE Trans. Sustain. Energy, 2015, 6, (3), pp. 675687.
    25. 25)
      • 25. Xia, Y., Wei, W., Yu, M., et al: ‘Power management for a hybrid AC/DC microgrid with multiple subgrids’, IEEE Trans. Power Electron., 2017, 33, (4), pp. 35203533.
    26. 26)
      • 26. Hosseinzadeh, M., Salmasi, F.R.: ‘Fault-tolerant supervisory controller for a hybrid AC/DC micro-grid’, IEEE Trans. Smart Grid, 2018, 9, (4), pp. 28092823.
    27. 27)
      • 27. Zhang, Y., Wang, L., Sun, W., et al: ‘Distributed intrusion detection system in a multi-layer network architecture of smart grids’, IEEE Trans. Smart Grid, 2011, 2, (4), pp. 796808.
    28. 28)
      • 28. Huang, G.B., Zhu, Q.Y., Siew, C.K.: ‘Extreme learning machine: theory and applications’, Neurocomputing, 2006, 70, (1), pp. 489501.
    29. 29)
      • 29. Coelho, E.A.A., Wu, D., Guerrero, J.M., et al: ‘Small-signal analysis of the microgrid secondary control considering a communication time delay view document’, IEEE Trans. Ind. Electron., 2016, 63, (10), pp. 62576269.

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