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Bayesian Prony Modal Identification and Hierarchical Control Strategy for Low-Frequency Oscillation of Ship Microgrid

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Pubblicato in:Electronics vol. 14, no. 23 (2025), p. 4669-4691
Autore principale: Ding, Yue
Altri autori: Zhao, Ke, Duan Jiandong, Sun, Li
Pubblicazione:
MDPI AG
Soggetti:
International Maritime Organization
Modal identification
Waveforms
Deep learning
Distributed generation
Bayesian analysis
Prony's method
Recursive functions
Damping
Algorithms
Energy storage
Time series
Real time
Power plants
Least squares
Shipping industry
Parameter estimation
Signal to noise ratio
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Abstract:A Bayes–Prony oscillating modal identification and hierarchical control strategy for low-frequency oscillation (LFO) of a ship microgrid (SM) is presented in this paper. The modal probabilistic estimation of the proposed algorithm replaces point estimation of the traditional Prony method and improves the robustness of modal identification. The hierarchical control strategy first performs modal identification by means of the batch least squares Prony (BLS-Prony) algorithm. The modal identification results are calibrated by the explanatory variance score (EVS), and the control process is transferred to recursive least squares Prony (RLS-Prony) real-time detection. The third layer of decision making transfers to Bayesian Prony (Bayes–Prony) identification in case of a loss of modality or failure of identification. The designed Bayes–Prony algorithm identifies the oscillatory modal of signals with a signal-to-noise ratio (SNR) equal to 2 dB. Compared to BLS-Prony and RLS-Prony, Bayes–Prony reduces the SNR convergence domain of the signal by 30 dB as the last layer of hierarchical control. Therefore, the third-layer decision commands are used as a scheduling reference for damping control in SM power plants. The proposed algorithms and strategies maximize the saving of computational resources while ensuring that the modal identification is effective. Finally, the correctness of the proposed algorithm and strategy is verified by the LFO waveforms of the experimental platform.
ISSN:2079-9292
DOI:10.3390/electronics14234669
Fonte:Advanced Technologies & Aerospace Database