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Distributed Coordination of Networked Microgrids for Voltage Support in Bulk Power Grids

IEEE TRANSACTIONS ON INDUSTRY APPLICATIONS 2024年第6期60卷 7971-7981页

作者： Gray, Nathan Sadnan, Rabayet Bose, Anjan Dubey, Anamika Vu, Thanh Long Xie, Jing Marinovici, Laurentiu D. Schneider, Kevin P. Klauber, Cecilia Trinh, Wei Washington State Univ WSU Sch Elect Engn & Comp Sci Pullman WA 99163 USA Pacific Northwest Natl Lab Richland WA 99354 USA Lawrence Livermore Natl Lab Livermore CA 94550 USA

The increasing deployment of distributed energy resources (DERs) and microgrids (MGs) in power distribution systems has enabled the adjustment of reactive power consumption as seen at the substation, which can be used to provide voltage support for the bulk power system (BPS). Leveraging this new capability will provide greater resiliency to the power system as a whole. The goal of this paper is to develop and compare three different algorithms, namely distributed optimal power flow, distributed consensus algorithm, and fully decentralized collaborative autonomy for unbalanced distribution systems for microgrid coordination. These algorithms use networked MGs to support the BPS voltage when a contingency at the bulk grid results in abnormally low voltages, which may be a precursor to voltage collapse. Our comparative analysis includes both qualitative and quantitative assessments of the three algorithms and a discussion of the trade-offs between the decentralized and distributed methods in normal and disrupted conditions. Each algorithm was evaluated on the modified IEEE 13-bus system and a real power distribution system in North America that encompasses more than 4500 buses. Each algorithm excels differently and may be suited for different scenarios depending on the condition, operations, and priorities of the power and communication systems.

关键词： Reactive power Voltage control Microgrids Substations Power system stability consensus algorithm Peer-to-peer computing Collaborative autonomy distributed control consensus voltage support microgrid distributed energy

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Accelerating and Securing Blockchain-Enabled Distributed Machine Learning

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IEEE TRANSACTIONS ON MOBILE COMPUTING 2024年第6期23卷 6712-6730页

作者： Du, Yao Wang, Zehua Leung, Cyril Leung, Victor C. M. Univ British Columbia Dept Elect & Comp Engn Vancouver V6T 1Z4 BC Canada China Univ Min & Technol Sch Comp Sci & Technol Xuzhou 221116 Jiangsu Peoples R China Shenzhen Univ Coll Comp Sci & Software Engn Shenzhen 518060 Guangdong Peoples R China

In the Internet of Things (IoT) employing centralized machine learning, security is a major concern due to the heterogeneity of end devices. Malicious devices could launch poisoning attacks to degrade machine learning models. Distributed machine learning (DML) with blockchain provides a potential solution. Once local weights are recorded on the blockchain, model aggregation with defensive schemes can be executed on smartphones to prevent attacks. However, blockchain with the proof-of-work (PoW) consensus mechanism wastes computing resources and adds latency to DML. Computing resources can be utilized more efficiently with proof-of-useful-work (uPoW), which secures transactions by solving relevant real-world problems. We propose a novel uPoW method to minimize per-round latency of DML. The uPoW mining process schedules DML instances among multi-access edge computing (MEC) servers by solving a multi-way number partitioning problem. Moreover, poisoning attacks on heterogeneous training data pose significant challenges to blockchain-based DML. To address this problem, we propose a novel aggregation protocol, named ${Corrected\ Krum}$CorrectedKrum, to counter such attacks and improve the convergence speed of DML. By leveraging the mean-field approximation method, training errors are corrected to reduce the negative impact of poisoning attacks. Simulation results show that our proposed blockchain approach can significantly speed up DML compared with benchmarks.

关键词： Blockchain consensus algorithm distributed machine learning multi-access edge computing poisoning attacks

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A Novel Collusion Combination Cyberattack Strategy Against Integrated Energy System

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IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS 2024年第11期20卷 12669-12683页

作者： Zhang, YunNing Tu, Xun Fu, WenLong Gao, YiHeng Chen, Xi Zhang, Lei China Three Gorges Univ Hubei Prov Engn Technol Res Ctr Microgrid Yichang 443002 Peoples R China China Three Gorges Univ Coll Elect Engn & New Energy Yichang 443002 Peoples R China

This article investigates the social welfare problem of the integrated energy system (IES), which faces supply-side and demand-side collusion attack strategies that consider the coordinated effects of two typical cyberattacks. First, an important node denial of service (DoS) attack mechanism based on malicious node collusion is proposed, which eases the restriction on the system parameter requirements. The explicit factors for deriving the optimal DoS attack strategy under limited attack resources are deduced by establishing relevant DoS attack models. Subsequently, a new collusion-based power vector false data injection (FDI) attack strategy between supply and demand sides is considered, aiming to enhance the economic disruptive capability of DoS attacks on IES. Building on the abovementioned work, a communication link FDI attack is further proposed, which can broaden the scope of attacks and disrupt defensive strategies. In addition, FDI attack termination and attack vector constraints are given. To alleviate the communication burden among attackers, the dynamic FDI attack vector is transformed into a static FDI attack determined by constant parameters, and all attack outcomes satisfying the local power constraints of malicious agents are provided. Finally, the stealthiness of the attack strategy is theoretically demonstrated and the effectiveness of the attack strategy is verified by 39-32 thermoelectric IES.

关键词： Collusion attack consensus algorithm cyberattacks integrated energy system (IES) social welfare (SW) Collusion attack consensus algorithm cyberattacks integrated energy system (IES) social welfare (SW)

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Distributed multi-horizon model predictive control for network of energy hubs

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CONTROL ENGINEERING PRACTICE 2024年 147卷

作者： Behrunani, Varsha N. Cai, Hanmin Heer, Philipp Smith, Roy S. Lygeros, John Swiss Fed Inst Technol Automat Control Lab Zurich Switzerland Swiss Fed Labs Mat Sci & Technol Empa Urban Energy Syst Lab Dubendorf Switzerland

The increasing penetration of renewable energy resources has transformed the energy system from a traditional hierarchical energy delivery paradigm to a distributed structure. Local energy hubs activates synergies among energy carriers rendering flexibility to the system and gives rise to possible energy trading among networked local energy hubs. Joint operation of such hubs and peer -to -peer trading between them can improve energy efficiency and support the integration of renewable energy resources. However, for such complex systems involving multiple stakeholders, both computational tractability and privacy concerns need to be accounted for. In this work, a novel multi -horizon distributed MPC framework is introduced for the control of energy hub networks. The multi -horizon approach increases the prediction horizon for MPC without compromising the time discretization or making the problem computationally intractable. The distributed scheme is based on a consensus alternating direction method of multipliers algorithm. It combines the superior performance of the centralized approach with the privacy preservation of the decentralized approach. A benchmark three -hub network is used to investigate the performance of the proposed method in simulation and compare it to the decentralized, centralized and standard model predictive control (MPC) approaches. The results show superior performance of the distributed multi -horizon MPC in terms of total cost, computational time, and robustness to demand and prices variations. Finally, the performance was also experimentally validated in real time by implementing the controller on a real energy hub system.

关键词： Distributed control Model predictive control Energy hubs ADMM consensus algorithm Multi horizon MPC

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A Gain Scheduling Control Framework for Mitigation of Time Varying Network Latency in Autonomous AC Microgrids

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IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS 2025年第1期21卷 347-356页

作者： Mallick, Amit Pradhan, Jatin Kumar Pradhan, Rosy Achary, K. Sujita Kumar Rath, Suman Guha, Arijit Veer Surendra Sai Univ Technol Burla Dept Elect Engn Sambalpur 768018 India Natl Inst Technol Rourkela Dept Elect Engn Sundargarh 769008 India Univ Nevada Reno NV 89512 USA

AC microgrids, being cyber-physical systems, rely heavily on communication networks to achieve their control objectives. However, the possibility of communication delays due to protocol-based errors, external noise addition, etc., raises suspicion on the reliability of communication infrastructure. This, in turn, makes the control architecture of the microgrid look complex and vulnerable. To address this problem, this work designs a consensus-based distributed secondary controller within the hierarchical control structure to achieve improved voltage and frequency regulation along with active and reactive power sharing while accounting for time-varying communication delays. Also, this work proposes a gain scheduling control in the secondary control that can effectively reduce the effects of communication delay over the performance of the hierarchical control structure. Our results show that this can efficiently eliminate system vulnerability to large values of time-varying delays. The efficacy of the proposed controller is also investigated in real-time with the help of a hardware-in-loop (HIL) setup.

关键词： Delays Voltage control Microgrids Reactive power Topology Robustness Network topology Mathematical models Frequency control Stability analysis consensus algorithm gain scheduling control graph theory microgrid proportional integral control secondary control

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IDHG-ECC-integrated Diffie Hellman Galois-elliptic-curve cryptography for enhancing EHR data security

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JOURNAL OF INFORMATION SECURITY AND APPLICATIONS 2025年 90卷

作者： Jyothy, S. T. Sarvagya, Mrinal REVA Univ Sch Elect & Commun Engn Bangalore 560064 Karnataka India

Electronic Health Records (EHRs), which are used in modern healthcare systems, store private medical histories for a large number of people. A strong security architecture is required to guarantee patient privacy within EHR databases due to the importance of preserving this personal data. Improving data security and patient privacy during the transfer of sensitive information across healthcare providers for diagnostic purposes is the main emphasis of this work. To enhance the security of electronic health record data, this article proposes a new approach that combines a decentralized, secure blockchain paradigm with a lightweight cryptosystem. The proposed workflow starts with gathering electronic health record data from databases and initializing user transaction information to facilitate communication across various nodes. Public and private keys are produced via an elliptic scheme to enhance the security of health data. Then, medical data is encrypted and decrypted using Integrated Diffie-Hellman Galois-Elliptic-curve Cryptography (IDHG-ECC). The encrypted data is further strengthened by using a consensus process known as Affinity-Propagation encased Practical Byzantine Fault Tolerance (AP-PBFT). Extra security is provided by storing the encrypted data on the off-chain Inter Planetary File System (OIPFS) blockchain. In the evaluation, the proposed model attains efficient encryption and decryption times of 7.88 s and 1.80 s, respectively, with a quick uploading time of 0 .09s. It achieves high transaction throughput (78,288 TPS) with low latency (0.71 s), while read throughput is 137.54 MB/s with minimal latency (0.01 s). CPU utilization is moderate at 20.70%, and memory utilization is 54.00%, ensuring balanced resource management for optimal performance.

关键词： Diffie-Hellman Elliptic-curve cryptography consensus algorithm Electronic health records Off-chain inter planetary File system Affinity-propagation approach

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Distributed Average consensus in Open Multi-Agent Systems 63

Distributed Average Consensus in Open Multi-Agent Systems

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63rd IEEE Conference on Decision and Control, CDC 2024

作者： Hadjicostis, Christoforos N. Dominguez-Garcia, Alejandro D. University of Cyprus Department of Electrical and Computer Engineering Nicosia Cyprus University of Illinois at Urbana-Champaign Department of Electrical and Computer Engineering UrbanaIL61801 United States

ISBN: (纸本)9798350316339

In this paper, we consider the problem of distributed average consensus in multi-agent systems, where each agent can come in or move out of the system, possibly multiple times. In the literature, such systems are referred to as open multi-agent systems. A typical goal in such settings is to use an iterative distributed algorithm to calculate the average of some quantities of interest each agent possesses, which can be crucial in many estimation, control, or optimization applications. We consider an open multi-agent setting and propose a distributed algorithm that allows the participating agents to track their average. More specifically, if the set of agents remaining in the computation eventually settles to a certain subset of agents, then the proposed algorithm allows them (under some mild connectivity conditions) to asymptotically reach consensus to the average of the quantities of interest these remaining agents hold. Analysis and numerical examples to illustrate the operation of the proposed algorithm are also provided. © 2024 IEEE.

关键词： consensus algorithm

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Blockchain-Based Cross-Domain Authentication With Dynamic Domain Participation in IoT

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IEEE INTERNET OF THINGS JOURNAL 2025年第5期12卷 5385-5395页

作者： Luo, Deyu Sun, Gang Yu, Hongfang Guizani, Mohsen Univ Elect Sci & Technol China Sch Informat & Commun Engn Chengdu 611731 Peoples R China Mohamed Bin Zayed Univ Artificial Intelligence Dept Machine Learning Abu Dhabi U Arab Emirates

In the Internet of Things (IoT), blockchain-based cross-domain authentication schemes can effectively establish trust and share data across different administrative domains. However, current blockchain-based cross-domain authentication solutions often overlook dynamic node participation challenges, which is crucial for the flexible IoT environment. In this study, we propose a blockchain-based cross-domain authentication scheme that supports dynamic node participation, allowing administrative domainss to freely join or leave under legal conditions. First, we introduce an efficient blockchain-based cross-domain authentication framework. Second, we propose a blockchain consensus algorithm that supports dynamic node participation to serve the aforementioned framework. Specifically, inspired by the transmission control protocol (TCP) protocol's piggybacking strategy, this algorithm integrates the process of node joining and leaving into the regular consensus flow to enhance efficiency. To further improve the algorithm's efficiency, we designed compressed block and parallel chain structures to increase bandwidth utilization and throughput. Detailed correctness proofs demonstrate the algorithm's security. Extensive experiments have been conducted to show that our scheme increases throughput by approximately 8x compared to existing approaches.

关键词： Authentication Internet of Things Heuristic algorithms Security Servers Public key consensus algorithm Information sharing Protocols Blockchain cross-domain authentication dynamic efficiency improvement Internet of Things (IoT) parallelization parallelization

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Improved algorithms for optimal k sink location on path networks

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THEORETICAL COMPUTER SCIENCE 2025年 1039卷

作者： Bhattacharya, Binay Golin, Mordecai J. Higashikawa, Yuya Kameda, Tsunehiko Katoh, Naoki Simon Fraser Univ Sch Comp Sci Burnaby BC Canada Univ Massachusetts Manning Coll Informat & Comp Sci Amherst MA 01002 USA Univ Hyogo Grad Sch Informat Sci Kobe Japan

We address the problem of placing k sinks on dynamic-flow path networks with n vertices so as to minimize their maximum evacuation completion time. We develop two different algorithms that, when all edges have the same capacity, run respectively in O(n+k2log2 n) and O(n log n) time. When the edge capacities can be different, i.e., are general, they run respectively in O(n log n+k2log4 n) and O(n log3 n) time. These algorithms improve upon the previously most efficient algorithms, which had time complexities O(kn) and O(knlog2n), respectively, for the uniform and general edge capacity models. The improvements are achieved by moving from a dynamic programming based approach to a parametric-search based one.

关键词： consensus algorithm

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Optimal and distributed energy management in interconnected energy hubs

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APPLIED ENERGY 2024年 365卷

作者： Azimi, Maryam Salami, Abolfazl Javadi, Mohammad S. Catalao, Joao P. S. Arak Univ Technol Dept Elect Engn Arak Iran Technol & Sci INESC TEC Inst Syst & Comp Engn Porto Portugal Univ Porto Fac Engn Res Ctr Syst & Technol SYSTEC Adv Prod & Intelligent Syst Associate Lab ARISE P-4200465 Porto Portugal

Recently, multi-carrier energy systems (MCESs) have been rapidly developed as flexible multi-generation systems aiming to satisfy load demands by purchasing, converting, and storing different energy carriers. This study specifically focuses on the optimal and robust large-scale coordination of interconnected energy hubs (IEHs) in an iterative consensus-based procedure considering distribution network losses. Furthermore, a new robustbased hybrid IGDT/consensus algorithm is introduced to achieve risk-averse optimal energy management in IEHs under uncertainty. The fast convergence, needless to collect the total information from all hubs, minimal computational burden, and more robust communication system are the most important features of the proposed distributed consensus algorithm in this study. The effectiveness of the proposed consensus algorithm is verified by simulation results considering various energy trading structures in IEHs at different scales. The obtained results highlight the scalability capability of the proposed method. Regarding an IEHS of 30 energy hubs, the computation burden is lightened by 0.53 (s) and 0.1917 (s), respectively with and without uncertainty. Considering distribution network losses, the total purchasing costs can be increased by 8%. The simulation results also reveal an increase of 11% in the total power trading under the uncertainty.

关键词： consensus algorithm Multi-carrier energy systems Interconnected energy hubs Uncertainty

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