Resilient Consensus Control With Privacy Protection for Battery Energy Storage Systems

Battery Energy Storage Systems (BESS) are essential for balancing power supply and demand through dynamic adjustments in charging and discharging. However, their integration into public networks exposes them to vulnerabilities, including adversarial attacks and privacy breaches, which threats system stability and coordination of agents. To mitigate these challenges, this paper presents a distributed resilient consensus algorithm that integrates Mean-Subsequence-Reduced techniques with Differential Privacy within a leader-follower framework. Our proposed approach ensures robust consensus on State-of-Charge, accurate demand tracking, and equitable power distribution while safeguarding the privacy of initial states, even in the presence of malicious nodes. For this purpose, we also introduce an error tracking factor to guarantee the accuracy of demand tracking. Our algorithm is provably correct since it converges with privacy preserved. Numerical simulations further substantiate its performance in practical scenarios.

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Publication Details

Journal
IEEE Control Systems Letters
Published
2025-01-01
DOI
https://doi.org/10.1109/lcsys.2025.3596499
Primary Topic
Optimization and Search Problems
Type
article
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article

Resilient Consensus Control With Privacy Protection for Battery Energy Storage Systems

Yiding Ji, Shiheng Zhang
IEEE Control Systems Letters
Optimization and Search Problems
article

Resilient Consensus Control With Privacy Protection for Battery Energy Storage Systems

Yiding Ji, Shiheng Zhang
article en

Abstract

Battery Energy Storage Systems (BESS) are essential for balancing power supply and demand through dynamic adjustments in charging and discharging. However, their integration into public networks exposes them to vulnerabilities, including adversarial attacks and privacy breaches, which threats system stability and coordination of agents. To mitigate these challenges, this paper presents a distributed resilient consensus algorithm that integrates Mean-Subsequence-Reduced techniques with Differential Privacy within a leader-follower framework. Our proposed approach ensures robust consensus on State-of-Charge, accurate demand tracking, and equitable power distribution while safeguarding the privacy of initial states, even in the presence of malicious nodes. For this purpose, we also introduce an error tracking factor to guarantee the accuracy of demand tracking. Our algorithm is provably correct since it converges with privacy preserved. Numerical simulations further substantiate its performance in practical scenarios.

IEEE Control Systems LettersVol. 9
University of Hong Kong (HK), South China University of Technology (CN)
Affordable and clean energy
Openalex Percentile: Top 78%
Optimization and Search Problems
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Resilient Consensus Control With Privacy Protection for Battery Energy Storage Systems — Yiding Ji, Shiheng Zhang · IEEE Control Systems Letters (2025) | TGRS Research Map | TGRS