Distributed Privacy-Preserving Active Power Sharing and Frequency Regulation in Microgrids

Fan, Bo; Wang, Xiongfei

doi:10.1109/tsg.2021.3067142

Cited by 21 publications

(2 citation statements)

References 12 publications

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“…Sufficient conditions involving the selected range of parameters in private keys were derived to guarantee the desired platoon stability and privacy preservation performance. One of our future work will focus on platooning control with simultaneous privacy-preserving and collision-free guarantees [49], [50].…”

Section: Discussionmentioning

confidence: 99%

Privacy-Preserving Platooning Control of Vehicular Cyber–Physical Systems With Saturated Inputs

Pan

Ding

et al. 2023

IEEE Trans. Syst. Man Cybern, Syst.

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Metaverse allows the physical reality to tightly integrate with the digital universe. As one typical metaverse application, platooning control of vehicular cyber-physical systems has attracted extensive attention as it is beneficial to improve traffic efficiency, driving safety, and emission reduction. However, due to the open nature of wireless communication networks, the transmitted vehicle-to-vehicle (V2V) data packets become exposed to the public and concomitant data leakage can lead to unintended consequences to vehicular platoons. This article is concerned with the privacy-preserving platooning control issue of vehicular cyber-physical systems with input saturations. First, a novel distributed proportional-integral observer is proposed to estimate the full state of each vehicle, where the integral terms with a forgetting factor facilitate to realize the tradeoff between transient performance and steady-state performance for the platoon. Second, sampled-data-based dynamic encryption and decryption schemes, featuring a dynamic private key, are developed such that the encrypted and decrypted V2V data can be kept private to each platoon vehicle. It is then shown that the platooning control problem over a generic communication topology can be cast into the stability issue of an auxiliary dynamic system. Furthermore, sufficient conditions on the existence of the desired observer and controller gains as well as the private key parameter selection are derived to guarantee the desired platoon stability and privacy preservation requirements. Finally, an illustrative example is given to demonstrate the effectiveness of the proposed control method.

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Section: Discussionmentioning

confidence: 99%

Privacy-Preserving Platooning Control of Vehicular Cyber–Physical Systems With Saturated Inputs

Pan

Ding

et al. 2023

IEEE Trans. Syst. Man Cybern, Syst.

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“…In power grid network, emergency rescue scenarios are scenarios where the network base stations and other basic communication facilities in the power grid network are damaged due to sudden climatic and natural disasters [1][2][3], resulting in interruption of communication links and inability to meet normal communication needs of power grid [4][5][6]. For the communication needs of the surviving nodes in the power grid, the extensive damage to the network base stations and other basic communication facilities has led to the paralysis of the original communication network, making it impossible to meet the communication needs of the power grid [7]. The communication demand cannot be satisfied.…”

Section: Introductionmentioning

confidence: 99%

Deep-learning-based resource allocation of satellite-assisted emergency rescue network for power grid

Zhou,

Han,

Zhang

et al. 2024

International Conference on Communication, Information, and Digital Technologies (CIDT2024)

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In this paper, the scenario of single satellite assisted emergency rescue network is proposed for power grid, in which the satellite moves to the position over the surviving node in the power grid, broadcasts information to the nodes in the coverage area through the downlink. The surviving node collects decodes the received signals, and then uploads the data information based through the uplink to the satellite. An algorithm is given by applying the Self-correcting Deep Q Network (SCDQN) algorithm in the Dueling Deep Q Network (DQN) network structure, and the dynamic resource allocation algorithm is proposed. In the proposed algorithm, the self-correcting DQN algorithm is selected as the base algorithm, which can realize self-correction. Both the estimated value network and the target value network adopt the Dueling DQN structure, which replaces the evaluation of the action value in the original DQN by evaluating the state value and the action value respectively. The improved algorithm can achieve efficient and stable convergence. The validity of the algorithm is verified through the simulation experiments and the superiority of the algorithm is verified through comparison.

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Programmable Crypto‐Control for Networked Microgrids

Wang,

Zhang,

Tang

2024

Microgrids

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Distributed Privacy-Preserving Active Power Sharing and Frequency Regulation in Microgrids

Cited by 21 publications

References 12 publications

Privacy-Preserving Platooning Control of Vehicular Cyber–Physical Systems With Saturated Inputs

Privacy-Preserving Platooning Control of Vehicular Cyber–Physical Systems With Saturated Inputs

Deep-learning-based resource allocation of satellite-assisted emergency rescue network for power grid

Programmable Crypto‐Control for Networked Microgrids

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