Distributed secondary control of DC microgrids with event-triggered quantization communication under DoS attacks
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Baoyan Wang
,
Xin Cai
,
Xinyuan Nan
Abstract
A resilient distributed secondary control strategy is proposed for DC microgrids (MGs) with denial-of-service (DoS) attacks on communication channels to achieve accurate current sharing and voltage regulation. According to the designed resilient control strategy, when there is no DoS attacks, the quantization information is sent to neighboring distributed generators (DGs) only when the triggering condition is satisfied. When there is a DoS attack, the communication can not be carried out normally. Then, each DG would attempt to send messages to its neighbors at a preset period until the attack disappears. The maximum allowable communication attempt period is determined by theoretical analysis, which is one of sufficient conditions to ensure current sharing and voltage regulation. As a result, the control signals are updated by discrete-time quantized information, which greatly reduces the communication burden, and effectively defends against DoS attacks. The asymptotic stability of the system is analyzed to show the results that voltage regulation and accurate current sharing are achieved. The proposed control strategy is verified through simulations.
Funding source: Natural Science Foundation of Xinjiang Uygur Autonomous Region
Award Identifier / Grant number: 2022D01C694
Funding source: National Natural Science Foundation of China
Award Identifier / Grant number: 62303394
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Research ethics: Not applicable.
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Informed consent: Informed consent was obtained from all individuals included in this study, or their legal guardians or wards.
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Author contributions: All authors have accepted responsibility for the entire content of this manuscript and approved its submission.
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Use of Large Language Models, AI and Machine Learning Tools: None declared.
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Conflict of interest: The authors state no conflict of interest.
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Research funding: This work was supported in part by the National Natural Science Foundation of China (NSFC, Grant No. 62303394) and in part by the Natural Science Foundation of Xinjiang Uygur Autonomous Region (Grant No. 2022D01C694).
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Data availability: Not applicable.
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