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Hybrid Local-global Power-sharing Scheme for Droop-free Controlled Microgrids

Journal of Modern Power Systems and Clean Energy 2024年第5期12卷 1520-1534页

作者： Kunyu Zuo Lei Wu Electrical and Computer Engineering Department Stevens Institute of TechnologyHobokenNJ 07030USA

The droop-free control adopted in microgrids has been designed to cope with global power-sharing goals,i.e.,sharing disturbance mitigation among all controllable assets to even their ***,limited by neighboring communication,the time-consuming peer-to-peer coordination of the droopfree control slows down the nodal convergence to global consensus,reducing the power-sharing efficiency as the number of nodes *** this end,this paper first proposes a local power-sharing droop-free control scheme to contain disturbances within nearby nodes,in order to reduce the number of nodes involved in the coordination and accelerate the convergence speed.A hybrid local-global power-sharing scheme is then put forward to leverage the merits of both schemes,which also enables the autonomous switching between local and global power-sharing modes according to the system *** guidance for key control parameter designs is derived via the optimal control methods,by optimizing the power-sharing distributions at the steady-state consensus as well as along the dynamic trajectory to *** system stability of the hybrid scheme is proved by the eigenvalue analysis and Lyapunov direct ***,simulation results validate that the proposed hybrid local-global power-sharing scheme performs stably against disturbances and achieves the expected control performance in local and global power-sharing modes as well as mode ***,compared with the classical global power-sharing scheme,the proposed scheme presents promising benefits in convergence speed and scalability.

关键词： Droop-free control power-sharing optimal control Lyapunov stability

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Pseudoinvertible Neural Networks

IEEE Transactions on Artificial Intelligence

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IEEE Transactions on Artificial Intelligence 2024年第2期5卷 602-612页

作者： Bolluyt, Elijah D. Comaniciu, Cristina Stevens Institute of Technology Department of Electrical and Computer Engineering HobokenNJ07030 United States

This work introduces novel architecture components and training procedures to create augmented neural networks with the ability to process data bidirectionally via an end-to-end approximate inverse. We develop pseudoinvertible neural network (PsI-NN) layers which function as drop-in replacements for corresponding convolutional and fully connected layers;by using these, existing architectures gain a pseudoinverse function which, with training, approximately reverses the forward function. For cases where learning both a task and its inverse are necessary or desirable, we show that PsI-NN enabled models match or exceed the quality of results generated by systems that use two separate models while drastically reducing system parameter count. We demonstrate this on two tasks: unpaired image translation and semisupervised classification. In both, PsI-NN greatly reduces parameter count without any loss of output quality;in semisupervised image classification, PsI-NN improves classification performance beyond the baseline autoencoder method. Our approach creates pseudoinvertible versions of existing architectures, circumventing the stringent constraints required to create a true inverse while allowing a single neural network to learn a task in two directions simultaneously. © 2023 IEEE.

关键词： Supervised learning

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Learning-based user association and dynamic resource allocation in multi-connectivity enabled unmanned aerial vehicle networks

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Digital Communications and Networks 2024年第1期10卷 53-62页

作者： Zhipeng Cheng Minghui Liwang Ning Chen Lianfen Huang Nadra Guizani Xiaojiang Du Department of Information and Communication Engineering Xiamen UniversityXiamen361005China School of Electrical and Computer Engineering University of Texas at ArlingtonArlingtonTX76019USA Department of Electrical and Computer Engineering Stevens Institute of TechnologyHobokenNJ07030USA

Unmanned Aerial Vehicles(UAvs)as aerial base stations to provide communication services for ground users is a flexible and cost-effective paradigm in ***,dynamic resource allocation and multi-connectivity can be adopted to further harness the potentials of UAVs in improving communication capacity,in such situations such that the interference among users becomes a pivotal disincentive requiring effective *** this end,we investigate the Joint UAV-User Association,Channel Allocation,and transmission Power Control(J-UACAPC)problem in a multi-connectivity-enabled UAV network with constrained backhaul links,where each UAV can determine the reusable channels and transmission power to serve the selected ground *** goal was to mitigate co-channel interference while maximizing long-term system *** problem was modeled as a cooperative stochastic game with hybrid discrete-continuous action space.A Multi-Agent Hybrid Deep Reinforcement Learning(MAHDRL)algorithm was proposed to address this *** simulation results demonstrated the effectiveness of the proposed algorithm and showed that it has a higher system utility than the baseline methods.

关键词： UAV-user association Multi-connectivity Resource allocation Power control Multi-agent deep reinforcement learning

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Optimal SOC Headroom of Pump Storage Hydropower for Maximizing Joint Revenue from Day-ahead and Real-time Markets Under Regional Transmission Organization Dispatch

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Journal of Modern Power Systems and Clean Energy 2024年第1期12卷 238-250页

作者： Yikui Liu Bing Huang Yang Lin Yonghong Chen Lei Wu Electrical and Computer Engineering Department Stevens Institute of TechnologyHobokenNJ 07030USA Midcontinent Independent System Operator Inc.CarmelIN 46032USA

In response to the increasing penetration of volatile and uncertain renewable energy,the regional transmission organizations(RTOs)have been recently focusing on enhancing the models of pump storage hydropower(PSH)plants,which are one of the key flexibility assets in the day-ahead(DA)and real-time(RT)markets,to further boost their flexibility provision *** by the recent research works that explored the potential benefits of excluding PSHs’cost-related terms from the objective functions of the DA market clearing model,this paper completes a rolling RT market scheme that is compatible with the DA ***,with the vision that PSHs could be permitted to submit state-of-charge(SOC)headrooms in the DA market and to release them in the RT market,this paper uncovers that PSHs could increase the total revenues from the two markets by optimizing their SOC headrooms,assisted by the proposed tri-level optimal SOC headroom ***,in the proposed tri-level model,the middle and lower levels respectively mimic the DA and RT scheduling processes of PSHs,and the upper level determines the optimal headrooms to be submitted to the RTO for maximizing the total revenue from the two *** case studies quantify the profitability of the optimal SOC headroom submissions as well as the associated financial risks.

关键词： Pump storage hydropower energy market state-of-charge(SOC) headroom market revenue tri-level problem

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A Data-driven Variable Reduction Approach for Transmission-constrained Unit Commitment of Large-scale Systems

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Journal of Modern Power Systems and Clean Energy 2023年第1期11卷 254-266页

作者： Yuzhou Zhou Qiaozhu Zhai Lei Wu Moammad Shahidehpour Systems Engineering Institute MOEKLINNS LabXi’an Jiaotong UniversityXi’an 710049China Electrical and Computer Engineering Department Stevens Institute of TechnologyHobokenU.S. Electrical and Computer Engineering Department Illinois Institute of TechnologyChicagoU.S. IEEE

This paper presents a data-driven variable reduction approach to accelerate the computation of large-scale transmission-constrained unit commitment(TCUC).Lagrangian relaxation(LR)and mixed-integer linear programming(MILP)are popular approaches to solving ***,with many binary unit commitment variables,LR suffers from slow convergence and MILP presents heavy computation *** proposed data-driven variable reduction approach consists of offline and online calculations to accelerate computational performance of the MILP-based large-scale TCUC problems.A database including multiple nodal net load intervals and the corresponding TCUC solutions is first built offline via the data-driven and all-scenario-feasible(ASF)approaches,which is then leveraged to efficiently solve new TCUC instances ***/off statuses of considerable units can be fixed in the online calculation according to the database,which would reduce the computation burden while guaranteeing good solution quality for new TCUC instances.A feasibility proposition is proposed to promptly check the feasibility of the new TCUC instances with fixed binary variables,which can be used to dynamically tune parameters of binary variable fixing strategies and guarantee the existence of feasible UC solutions even when system structure *** tests illustrate the efficiency of the proposed approach.

关键词： Unit commitment accelerated algorithm data driven variable reduction

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4D-printed intelligent reflecting surface with improved beam resolution via both phase modulation and space modulation

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Microsystems & Nanoengineering 2024年第5期10卷 407-415页

作者： Kyounghwan Kim Ratanak Phon Eiyong Park Sungjoon Lim Department of Intelligent Semiconductor Engineering Chung-Ang UniversitySeoul 06974Republic of Korea Department of Electrical and Computer Engineering Stevens Institute of TechnologyHoboken NJ 07030USA School of Electrical and Electronic Engineering Chung-Ang UniversitySeoul 06974Republic of Korea

Recently,intelligent reflecting surfaces(IRSs)have emerged as potential candidates for overcoming the line-of-sight issue in 5 G/6 G wireless *** IRSs can manipulate the direction of reflected beams,enabling efficient beam steering to enhance the performance of wireless *** unit cell(or unit structure)of an IRS commonly consists of electrical elements for phase ***,by employing phase modulation alone,an IRS can steer the reflected electromagnetic waves toward only discrete and specific angles,leaving a wide range of out-of-beam *** this work,an IRS that uses both phase modulation and space modulation is presented to improve the beam resolution and continuously cover out-of-beam areas that phase modulation alone cannot address.A positive-intrinsic-negative diode is mounted on a unit cell for phase modulation,and a 4D-printed reconfigured structure is fabricated to demonstrate space *** beam-steering function is achieved by alternating the states of the diodes in the same columns,while the beam resolution is improved by controlling the gaps between the *** functions are frst theoretically and numerically analyzed and then experimentally verified,demonstrating that additional angles of-46°/+50°,-22°/+14°,and -16°/+12°are achieved with space modulation and -60°/+62°,-30°/+22°,and±16°are achieved by phase modulation *** proposed IRS offers the possibility of functional integration in a variety of indoor applications within the wireless communication field.

关键词： alone beam columns

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Integrity Verifiable Privacy-preserving Federated Learning for Healthcare-IoT

Integrity Verifiable Privacy-preserving Federated Learning f...

引用

2024 IEEE International Conference on E-Health Networking, Application and Services, HealthCom 2024

作者： Li, Jiarui Yu, Shucheng Department of Electrical and Computer Engineering Stevens Institute of Technology Hoboken United States

ISBN: (纸本)9798350350548

In Healthcare Internet of Things, federated learning has emerged as a promising distributed machine learning paradigm, enabling multiple clients to collaboratively train models with huge amounts of medical data while preserving the privacy of sensitive information. Despite its advantages, federated learning faces significant challenges in maintaining the integrity of the global model due to the potential for data and model poisoning attacks. These attacks are exacerbated by the lack of direct oversight in the local training processes, allowing malicious participants to manipulate model updates. This paper introduces Integrity Verifiable Federated Learning (IV-FED), a novel framework that leverages trusted execution environments (TEEs) to ensure the integrity of the training process without compromising privacy. IV-FED employs an accumulator-based integrity verification protocol, allowing the central server to verify the correctness of local training without reproducing the entire training process. Additionally, the framework incorporates an adversarial perturbation-based detection mechanism to prevent the injection of poisoned data by malicious participants. © 2024 IEEE.

关键词： Federated learning

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Intelligent integrated sensing and communication:a survey

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Science China(Information Sciences) 2025年第3期68卷 5-46页

作者： Jifa ZHANG Weidang LU Chengwen XING Nan ZHAO Naofal AL-DHAHIR George K.KARAGIANNIDIS Xiaoniu YANG School of Information and Communication Engineering Dalian University of Technology College of Information Engineering Zhejiang University of Technology School of Information and Electronics Beijing Institute of Technology Department of Electrical and Computer Engineering The University of Texas at Dallas Department of Electrical and Computer Engineering Aristotle University of Thessaloniki

Integrated sensing and communication (ISAC) is a promising technique to increase spectral efficiency and support various emerging applications by sharing the spectrum and hardware between these functionalities. However, the traditional ISAC schemes are highly dependent on the accurate mathematical model and suffer from the challenges of high complexity and poor performance in practical scenarios. Recently, artificial intelligence (AI) has emerged as a viable technique to address these issues due to its powerful learning capabilities, satisfactory generalization capability, fast inference speed, and high adaptability for dynamic environments, facilitating a system design shift from model-driven to data-driven. Intelligent ISAC, which integrates AI into ISAC, has been a hot topic that has attracted many researchers to investigate. In this paper, we provide a comprehensive overview of intelligent ISAC, including its motivation, typical applications, recent trends, and challenges. In particular, we first introduce the basic principle of ISAC, followed by its key techniques. Then, an overview of AI and a comparison between model-based and AI-based methods for ISAC are provided. Furthermore, the typical applications of AI in ISAC and the recent trends for AI-enabled ISAC are reviewed. Finally, the future research issues and challenges of intelligent ISAC are discussed.

关键词： artificial intelligence deep learning deep reinforcement learning federated learning generative artificial intelligence integrated sensing and communication machine learning transfer learning

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Spectral Estimation of Weak Signals with Strong Interference via Modulo Sampling 59

Spectral Estimation of Weak Signals with Strong Interference...

引用

59th Annual Conference on Information Sciences and Systems, CISS 2025

作者： Ahmed, Shoaib Zeng, Cengcang Li, Hongbin Stevens Institute of Technology Department of Electrical and Computer Engineering HobokenNJ07030 United States

ISBN: (纸本)9798331513269

This paper introduces a framework for spectral analysis of weak signals in the presence of strong interference that can potentially exceed the dynamic range of the analog-to-digital converter (ADC) employed for data acquisition. The framework combines modulo sampling to avoid ADC saturation with interference cancellation (IC) and adaptive spectral estimators such as amplitude and phase estimation of a sinusoid (APES) and Capon for high-resolution spectral analysis. Numerical simulations validate the proposed approach's ability to accurately recover weak signals' spectrum with significantly lower mean-squared error (MSE) in amplitude estimation compared to conventional methods in the considered scenarios. Notably, it is shown that APES and Capon are able to effectively reject the out-of-range interference and reveal weak spectral content, without requiring the interference cancellation step. © 2025 IEEE.

关键词： Mean square error

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Decentralized Demand Management Based on Alternating Direction Method of Multipliers Algorithm for Industrial Park with CHP Units and Thermal Storage

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Journal of Modern Power Systems and Clean Energy 2022年第1期10卷 120-130页

作者： Jingdong Wei Yao Zhang Jianxue Wang Lei Wu Peiqi Zhao Zhengting Jiang School of Electrical Engineering Xi’an Jiaotong UniversityXi’anChina Electrical and Computer Engineering Department Stevens Institute of TechnologyHobokenUSA

This paper proposes a decentralized demand management approach to reduce the energy bill of industrial park and improve its economic gains.A demand management model for industrial park considering the integrated demand response of combined heat and power(CHP)units and thermal storage is firstly ***,by increasing the electricity outputs of CHP units during peak-load periods,not only the peak demand charge but also the energy charge can be *** thermal storage can efficiently utilize the waste heat provided by CHP units and further increase the flexibility of CHP *** heat dissipation of thermal storage,thermal delay effect,and heat losses of heat pipelines are considered for ensuring reliable solutions to the industrial *** proposed model is formulated as a multi-period alternating current(AC)optimal power flow problem via the second-order conic programming *** alternating direction method of multipliers(ADMM)algorithm is used to compute the proposed demand management model in a distributed manner,which can protect private data of all participants while achieving solutions with high *** case studies validate the effectiveness of the proposed demand management approach in reducing peak demand charge,and the performance of the ADMM-based decentralized computation algorithm in deriving the same optimal results of demand management as the centralized approach is also validated.

关键词： Alternating direction method of multipliers(ADMM) combined heat and power(CHP)unit demand management industrial park integrated demand response(IDR) thermal storage

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