Privacy-Preserving Distributed Entropy Filtering for Microgrids With Innovation Decomposition

Yan Liang; Yangkai Chen; Dengfeng Pan; Haifang Song

doi:10.53941/ijndi.2025.100004

Abstract

Data leakage and cyberattacks are usually inevitable due mainly to the vulnerability of deployed communication networks. The paper proposes a distributed privacy-preserving filter based on the maximum correlation criteria for microgrids. An improved distributed structure is first constructed via adding decomposed innovation from neighbors in update steps. Then, an improved version of the maximum correntropy criterion is defined to evaluate the local filtering performance as well as the consensus performance by adding an innovation-related term. In light of fixed-point iterations and the adopted filter structure, the desired filter gains are obtained recursively by optimizing the proposed index. Furthermore, the profound analysis is performed to disclose that the filtering covariance of external eavesdroppers is larger than target-side filters and hence the privacy of the microgrids can be protected. Finally, an example is exploited to verify its effectiveness.

References

1.
Yan, M.Y.; Shahidehpour, M.; Alabdulwahab, A.; et al. Blockchain for transacting energy and carbon allowance in networked microgrids. IEEE Trans. Smart Grid, 2021, 12: 4702-4714. doi: 10.1109/TSG.2021.3109103
2.
Thale, S.S.; Wandhare, R.G.; Agarwal, V. A novel reconfigurable microgrid architecture with renewable energy sources and storage. IEEE Trans. Ind. Appl., 2015, 51: 1805-1816. doi: 10.1109/TIA.2014.2350083
3.
Zhao, P.F.; Ding, D.R.; Dong, H.L.; et al. Secure distributed state estimation for microgrids with eavesdroppers based on variable decomposition. IEEE Trans. Circuits Syst. I: Regul. Pap., 2024, 71: 3307-3316. doi: 10.1109/TCSI.2024.3357523
4.
Su, G.H.; Wang, Z.L. Event-triggered robust integrated observer design for nonlinear interconnected system based on multiple intermediate estimators. IEEE Trans. Circuits Syst. II: Express Briefs, 2024, 71: 3443-3447. doi: 10.1109/TCSII.2024.3362711
5.
Hu, X.H.; Peng, C.; Shen, H.; et al. Extended dissipative scalable control for AC islanded microgrids. IEEE Trans. Circuits Syst. I: Regul. Pap., 2023, 70: 5421-5432. doi: 10.1109/TCSI.2023.3305525
6.
Dai, D.Y.; Li, J.H.; Song, Y.H.; et al. Event-based recursive filtering for nonlinear bias-corrupted systems with amplify-and-forward relays. Syst. Sci. Control Eng., 2024, 12: 2332419. doi: 10.1080/21642583.2024.2332419
7.
Wu, Q.; Song, Q.K. Isolated industrial micro-grid demand response with assembly process based on distributionally robust chance constraint. Int. J. Syst. Sci., 2024, 55: 2211-2223. doi: 10.1080/00207721.2024.2337901
8.
Qu, B.G.; Wang, Z.D.; Shen, B.; et al. Anomaly-resistant decentralized state estimation under minimum error entropy with fiducial points for wide-area power systems. IEEE/CAA J. Autom. Sin., 2024, 11: 74-87. doi: 10.1109/JAS.2023.123795
9.
Wang, Y.; Liu, H.J.; Tan, H.L. An overview of filtering for sampled-data systems under communication constraints. Int. J. Netw. Dyn. Intell., 2023, 2: 100011. doi: 10.53941/ijndi.2023.100011
10.
Rana, M.M.; Li, L.; Su, S.W.; et al. Consensus-based smart grid state estimation algorithm. IEEE Trans. Industr. Inform., 2018, 14: 3368-3375. doi: 10.1109/TII.2017.2782750
11.
Chen, T.P.; Cao, Y.H.; Chen, X.B.; et al. A distributed maximum-likelihood-based state estimation approach for power systems. IEEE Trans. Instrum. Meas., 2021, 70: 1002110. doi: 10.1109/TIM.2020.3024338
12.
Qu, B.G.; Wang, Z.D.; Shen, B.; et al. Outlier-resistant recursive state estimation for renewable-electricity-generation-based microgrids. IEEE Trans. Industr. Inform., 2023, 19: 7133-7144. doi: 10.1109/TII.2022.3205354
13.
Kar, S.; Hug, G.; Mohammadi, J.; et al. Distributed state estimation and energy management in smart grids: A consensus + innovations approach. IEEE J. Sel. Top. Signal Process., 2014, 8: 1022-1038. doi: 10.1109/JSTSP.2014.2364545
14.
Zhao, H.Q.; Long, X.Q.; Hou, X.Y.; et al. Simplified set-membership augmented affine projection generalized maximum complex correntropy criterion algorithm. IEEE Trans. Circuits Syst. II: Express Briefs, 2024, 71: 3623-3627. doi: 10.1109/TCSII.2024.3365212
15.
Song, W.H.; Wang, Z.D.; Li, Z.K.; et al. Maximum correntropy filtering for complex networks with uncertain dynamical bias: Enabling component-wise event-triggered transmission. IEEE Trans. Neural. Netw. Learn. Syst., 2024, 35: 17330-17343. doi: 10.1109/TNNLS.2023.3302190
16.
Chen, B.D.; Liu, X.; Zhao, H.Q.; et al. Maximum correntropy Kalman filter. Automatica, 2017, 76: 70-77. doi: 10.1016/j.automatica.2016.10.004
17.
Yin, X.; Zhang, Q.C.; Wang, H.; et al. RBFNN-based minimum entropy filtering for a class of stochastic nonlinear systems. IEEE Trans. Automat. Contr., 2020, 65: 376-381. doi: 10.1109/TAC.2019.2914257
18.
Feng, Z.Y.; Wang, G.; Peng, B.; et al. Distributed minimum error entropy Kalman filter. Inf. Fusion, 2023, 91: 556-565. doi: 10.1016/j.inffus.2022.11.016
19.
Dang, L.J.; Chen, B.D.; Xia, Y.L.; et al. Dual extended Kalman filter under minimum error entropy with fiducial points. IEEE Trans. Syst., Man, Cybern.: Syst., 2022, 52: 7588-7599. doi: 10.1109/TSMC.2022.3161412
20.
Song, H.F.; Ding, D.R.; Shen, B.; et al. Jointly distributed filtering based on generalized maximum correntropy criterion: Memory-based event-triggered cases. IEEE Trans. Industr. Inform., 2023, 19: 10024-10033. doi: 10.1109/TII.2022.3231429
21.
Chen, B.D.; Xing, L.; Zhao, H.Q.; et al. Effects of outliers on the maximum correntropy estimation: A robustness analysis. IEEE Trans. Syst., Man, Cybern.: Syst., 2021, 51: 4007-4012. doi: 10.1109/TSMC.2019.2931403
22.
Chen, B.D.; Dang, L.J.; Gu, Y.T.; et al. Minimum error entropy Kalman filter. IEEE Trans. Syst., Man, Cybern.: Syst., 2021, 51: 5819-5829. doi: 10.1109/TSMC.2019.2957269
23.
Lin, C.H.; Wu, W.C.; Guo, Y. Decentralized robust state estimation of active distribution grids incorporating microgrids based on PMU measurements. IEEE Trans. Smart Grid, 2020, 11: 810-820. doi: 10.1109/TSG.2019.2937162
24.
Ao, W.; Song, Y.D.; Wen, C.Y. Distributed secure state estimation and control for CPSs under sensor attacks. IEEE Trans. Cybern., 2020, 50: 259-269. doi: 10.1109/TCYB.2018.2868781
25.
Wang, W.; Ma, L.F.; Rui, Q.Q.; et al. A survey on privacy-preserving control and filtering of networked control systems. Int. J. Syst. Sci., 2024, 55: 2269-2288. doi: 10.1080/00207721.2024.2343734
26.
Ma, S.Z.; Wen, G.H.; Luan, M.; et al. Privacy-preserving distributed optimal economic-emission dispatch over directed graphs. IEEE Trans. Circuits Syst. II: Express Briefs, 2024, 71: 3418-3422. doi: 10.1109/TCSII.2024.3361085
27.
Zhang, L.X.; Zhang, K.; Jiang, H.Y. Attack-free protocols design for leader-following consensus of discrete-time multi-agent systems with multiple input delays. Int. J. Syst. Sci., 2024, 55: 407-425. doi: 10.1080/00207721.2023.2272301
28.
Zhou, J.Y.; Yang, W.; Ding, W.J.; et al. Watermarking-based protection strategy against stealthy integrity attack on distributed state estimation. IEEE Trans. Automat. Contr., 2023, 68: 628-635. doi: 10.1109/TAC.2022.3171422
29.
Fan, B.; Wang, X.F. Distributed privacy-preserving active power sharing and frequency regulation in microgrids. IEEE Trans. Smart Grid, 2021, 12: 3665-3668. doi: 10.1109/TSG.2021.3067142
30.
Riverso, S.; Sarzo, F.; Ferrari-Trecate, G. Plug-and-play voltage and frequency control of islanded microgrids with meshed topology. IEEE Trans. Smart Grid, 2015, 6: 1176-1184. doi: 10.1109/TSG.2014.2381093
31.
Kennedy, J.M.; Ford, J.J.; Quevedo, D.E.; et al. Innovation-based remote state estimation secrecy with no acknowledgments. IEEE Trans. Automat. Contr., 2024, 69: 7433-7448. doi: 10.1109/TAC.2024.3385315
32.
Zou, J.Y.; Liu, H.X.; Liu, C.; et al. Optimal privacy-preserving transmission schedule against eavesdropping attacks on remote state estimation. IEEE Control Syst. Lett., 2024, 8: 538-543. doi: 10.1109/LCSYS.2024.3398200
33.
Das, N.; Bhattacharya, R. Privacy and utility aware data sharing for space situational awareness from ensemble and unscented Kalman filtering perspective. IEEE Trans. Aerosp. Electron. Syst., 2021, 57: 1162-1176. doi: 10.1109/TAES.2020.3038243
34.
Huang, J.; Gao, C.; He, X. Privacy-preserving state estimation with unreliable channels. ISA Trans., 2022, 127: 4-12. doi: 10.1016/j.isatra.2022.05.035
35.
Song, Y.; Wang, C.X.; Tay, W.P. Privacy-aware Kalman filtering. In Proceedings of 2018 IEEE International Conference on Acoustics, Speech and Signal Processing, Calgary, 15–20 April 2018; IEEE: New York, 2018 ; pp. 4434–4438. doi: 10.1109/ICASSP.2018.8462600.
36.
Moradi, A.; Venkategowda, N.K.D.; Talebi, S.P.; et al. Privacy-preserving distributed Kalman filtering. IEEE Trans. Signal Process., 2022, 70: 3074-3089. doi: 10.1109/TSP.2022.3182590
37.
Chen, W.; Wang, Z.D.; Hu, J.; et al. Differentially private average consensus with logarithmic dynamic encoding-decoding scheme. IEEE Trans. Cybern., 2023, 53: 6725-6736. doi: 10.1109/TCYB.2022.3233296
38.
Chen, W.; Liu, G.P. Privacy-preserving consensus-based distributed economic dispatch of smart grids via state decomposition. IEEE/CAA J. Autom. Sin., 2024, 11: 1250-1261. doi: 10.1109/JAS.2023.124122
39.
An, W.J.; Ding, D.R.; Dong, H.L.; et al. Privacy-preserving distributed optimization for economic dispatch over balanced directed networks. IEEE Trans. Inf. Forensics Secur., 2025, 20: 1362-1373. doi: 10.1109/TIFS.2024.3438129
40.
Sun, L.; Ding, D.R.; Dong, H.L.; et al. Distributed economic dispatch of microgrids based on ADMM algorithms with encryption-decryption rules. IEEE Trans. Autom. Sci. Eng. 2025 , in press. doi: 10.1109/TASE.2024.3485922.

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