A Kalman Filter-Based Distributed Cyber-Attack Mitigation Strategy for Distributed Generator Units in Meshed DC Microgrids
To ensure fast dynamics and the stability of multiple distributed generator units (DGUs) in DC microgrids, communication links among the controllers of DGUs are generally adopted. However, those communication channels are vulnerable to cyber-attacks. To alleviate this hassle, a Kalman Filter (KF)-ba...
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| Format: | Article |
| Language: | English |
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MDPI AG
2023-12-01
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| Series: | Energies |
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| Online Access: | https://www.mdpi.com/1996-1073/16/24/7959 |
| _version_ | 1797381271926603776 |
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| author | Wenpei Li Han Fu Shun Wu Bin Yang Zhixiong Liu |
| author_facet | Wenpei Li Han Fu Shun Wu Bin Yang Zhixiong Liu |
| author_sort | Wenpei Li |
| collection | DOAJ |
| description | To ensure fast dynamics and the stability of multiple distributed generator units (DGUs) in DC microgrids, communication links among the controllers of DGUs are generally adopted. However, those communication channels are vulnerable to cyber-attacks. To alleviate this hassle, a Kalman Filter (KF)-based distributed cyber-attack mitigation strategy, which is highly involved in both primary and secondary control, is proposed in this paper. The KF, as a robust state estimator, is utilized to accurately estimate the authentic terminal voltages and currents of the DGUs. Based on the discrepancies between the estimated and measured parameters of the systems under cyber-attacks, the proposed control can adaptively compensate the attack signals via an adaptive proportional integral (API) controller and a fractional API (FAPI) controller in cyber-attack-mitigation layers. The main advantage of using the proposed control scheme compared to conventional schemes is the fast dynamic response. The simulation results verify this merit by comparing the adopted KF and comparing it with conventional artificial neural networks (ANN), while the experimental results validate that effectiveness of the proposed control and showcase the superiority of the FAPI control in terms of its perfect compensation for different types of cyber-attacks. |
| first_indexed | 2024-03-08T20:50:02Z |
| format | Article |
| id | doaj.art-ab9f70d4cd654b8ba2e53ddd28e0e054 |
| institution | Directory Open Access Journal |
| issn | 1996-1073 |
| language | English |
| last_indexed | 2024-03-08T20:50:02Z |
| publishDate | 2023-12-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Energies |
| spelling | doaj.art-ab9f70d4cd654b8ba2e53ddd28e0e0542023-12-22T14:05:38ZengMDPI AGEnergies1996-10732023-12-011624795910.3390/en16247959A Kalman Filter-Based Distributed Cyber-Attack Mitigation Strategy for Distributed Generator Units in Meshed DC MicrogridsWenpei Li0Han Fu1Shun Wu2Bin Yang3Zhixiong Liu4State Grid Hubei Electric Power Research Institute, Wuhan 430062, ChinaState Grid Wuhan Power Supply Company, Wuhan 430070, ChinaDepartment of Electrical Engineering, Wuhan Electric Power Technical College, Wuhan 430074, ChinaState Grid Wuhan Power Supply Company, Wuhan 430070, ChinaState Key Laboratory of Power Grid Environment Protection, School of Electrical Engineering and Automation, Wuhan University, Wuhan 430072, ChinaTo ensure fast dynamics and the stability of multiple distributed generator units (DGUs) in DC microgrids, communication links among the controllers of DGUs are generally adopted. However, those communication channels are vulnerable to cyber-attacks. To alleviate this hassle, a Kalman Filter (KF)-based distributed cyber-attack mitigation strategy, which is highly involved in both primary and secondary control, is proposed in this paper. The KF, as a robust state estimator, is utilized to accurately estimate the authentic terminal voltages and currents of the DGUs. Based on the discrepancies between the estimated and measured parameters of the systems under cyber-attacks, the proposed control can adaptively compensate the attack signals via an adaptive proportional integral (API) controller and a fractional API (FAPI) controller in cyber-attack-mitigation layers. The main advantage of using the proposed control scheme compared to conventional schemes is the fast dynamic response. The simulation results verify this merit by comparing the adopted KF and comparing it with conventional artificial neural networks (ANN), while the experimental results validate that effectiveness of the proposed control and showcase the superiority of the FAPI control in terms of its perfect compensation for different types of cyber-attacks.https://www.mdpi.com/1996-1073/16/24/7959adaptive controllerscyber-attack mitigationdc microgridsstate estimation |
| spellingShingle | Wenpei Li Han Fu Shun Wu Bin Yang Zhixiong Liu A Kalman Filter-Based Distributed Cyber-Attack Mitigation Strategy for Distributed Generator Units in Meshed DC Microgrids Energies adaptive controllers cyber-attack mitigation dc microgrids state estimation |
| title | A Kalman Filter-Based Distributed Cyber-Attack Mitigation Strategy for Distributed Generator Units in Meshed DC Microgrids |
| title_full | A Kalman Filter-Based Distributed Cyber-Attack Mitigation Strategy for Distributed Generator Units in Meshed DC Microgrids |
| title_fullStr | A Kalman Filter-Based Distributed Cyber-Attack Mitigation Strategy for Distributed Generator Units in Meshed DC Microgrids |
| title_full_unstemmed | A Kalman Filter-Based Distributed Cyber-Attack Mitigation Strategy for Distributed Generator Units in Meshed DC Microgrids |
| title_short | A Kalman Filter-Based Distributed Cyber-Attack Mitigation Strategy for Distributed Generator Units in Meshed DC Microgrids |
| title_sort | kalman filter based distributed cyber attack mitigation strategy for distributed generator units in meshed dc microgrids |
| topic | adaptive controllers cyber-attack mitigation dc microgrids state estimation |
| url | https://www.mdpi.com/1996-1073/16/24/7959 |
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