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A Study on Magnetic Field under Unconventional Lines with Increased Power Delivery

IEEE Transactions on Industry Applications 2025年第3期61卷 5128-5134页

作者： Arafat, Easir Porkar, Babak Ghassemi, Mona Laboratory Department of Electrical and Computer Engineering RichardsonTX75080 United States

To achieve net-zero emission in America by 2050, high voltage transmission capacity must expand approximately 60% by 2030 and triple by 2050 to connect further renewable (wind and solar) facilities to increased power delivery. Addressing this challenge requires not only conventional transmission lines (TLs) but also innovative, unconventional designs that modify phase configurations and subconductor arrangements in geometrically optimized ways. Different line design aspects need to be studied to realize these unconventional lines. This paper calculates and studies the magnetic field under the two unconventional lines we proposed in our previous work. The magnetic field was analyzed across the entire Right of Way (ROW) using validated simulation models. The quantitative analysis reveals that while the conventional 500 kV line generates a ground-level magnetic field of 5 μT, the unconventional designs - TL-1 and TL-2 - achieve significantly lower values of less than 0.5 μT and 3 μT, respectively. Furthermore, these designs comply with ICNIRP and WHO safety standards across the entire ROW, highlighting their potential to enhance system capacity while maintaining public health and safety. © 2025 IEEE.

关键词： Power transmission lines

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Security, Latency, and Throughput of Proof-of-Work Nakamoto Consensus

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IEEE Transactions on Information Theory 2025年第6期71卷 4708-4731页

作者： Cao, Shu-Jie Guo, Dongning Northwestern University Department of Electrical and Computer Engineering EvanstonIL United States

This paper investigates the fundamental trade-offs between block safety, confirmation latency, and transaction throughput of proof-of-work (PoW) longest-chain fork-choice protocols, also known as PoW Nakamoto consensus. New upper and lower bounds are derived for the probability of block safety violations as a function of honest and adversarial mining rates, a block propagation delay limit, and confirmation latency measured in both time and block depth. The results include the first non-trivial closed-form finite-latency bound applicable across all delays and mining rates up to the ultimate fault tolerance. Notably, the gap between these upper and lower bounds is narrower than previously established bounds for a wide range of parameters relevant to Bitcoin and its derivatives, including Litecoin and Dogecoin, as well as Ethereum Classic. Additionally, the study uncovers a fundamental trade-off between transaction throughput and confirmation latency, ultimately determined by the desired fault tolerance and the rate at which block propagation delay increases with block size. © 1963-2012 IEEE.

关键词： Bitcoin

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Innovative Design for Mutual Coupling Reduction in Dual-Element Array Antennas for ISM Applications Using Whale Optimization Algorithm

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Progress in Electromagnetics Research C 2025年 152卷 121-129页

作者： Atashpanjeh, Elham Rezaei, Pejman Department of Electrical and Computer Engineering Semnan University Semnan35131-19111 Iran

This paper introduces a decoupled dual-element array antenna designed to address the challenges of mutual coupling between elements. To tackle this issue, a neutralization line is strategically incorporated to suppress leaky surface currents, while ensuring that the antenna’s central frequency and radiation pattern remain intact. The dimensions of the neutralization line are carefully optimized using the Whale Optimization Algorithm (WOA) to achieve the best possible performance, focusing on minimizing mutual coupling and enhancing gain. By placing the neutralization line nearby between the two elements, surface currents are efficiently redirected back to the radiating element, preventing leakage to neighboring elements. This approach also results in a more compact structure. The proposed antenna, with overall dimensions of 50 mm × 30 mm × 1.6 mm, is simulated using analytic software. It achieves an impressive 27 dB reduction in mutual coupling and delivers an ultra-wide bandwidth of 1.2 GHz within the Industrial Scientific and Medical (ISM) band at an operating frequency of 2.4 GHz, with a measured maximum gain of −5.19 dB. The structure was fabricated, and experimental results closely matched the simulations, confirming the design’s effectiveness. By leveraging the WOA optimization method, the geometry of the neutralization line was fine-tuned to maximize performance, significantly improving inter-element decoupling. This design approach is simple yet effective and can be readily extended to other antenna array configurations, demonstrating strong potential for compact and efficient ISM band applications. © 2025, Electromagnetics Academy. All rights reserved.

关键词： Directional patterns (antenna)

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A New Approach to Determine Feasible Operating Region of Unbalanced Distribution Networks with Distributed Photovoltaics

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IEEE Transactions on Power Delivery 2025年第3期40卷 1493-1504页

作者： Prasad, Manorath Rather, Zakir Hussain Razzaghi, Reza Doolla, Suryanarayana Indian Institute of Technology Bombay Department of Energy Science and Engineering Mumbai India Monash University Department of Electrical and Computer Systems Engineering Melbourne Australia

Amidst rising distributed generation and its potential role in grid management, this article presents a new realistic approach to determine the operational space and flexibility potential of an unbalanced active distribution network. The feasible operating region of an active distribution network is constituted by its range of active-reactive power exchanges with the bulk power system without breaching network constraints. This study explores the potential of highly penetrated single- and three-phase distributed photovoltaics and voltage-sensitive loads to determine the feasible operating region at different operating points. The cumulative response of Volt-Var controlled distributed photovoltaics and voltage-sensitive loads determines the power flow at the bulk power system-active distribution network interconnection, ensuring feasibility with respect to voltage magnitude and unbalance constraints. Further, the correspondence of feasible operating region with the tap-settings of substation transformer enables a novel feature to traverse throughout the available operating region and facilitate bulk power system-active distribution network power coordination. Additionally, a nodal sensitivity-based adjustable Volt-Var control scheme is proposed for distributed photovoltaics, improving the feasible operating region. The proposed strategy is validated on bulk power systemactive distribution network integrated test system. Bulk power system: IEEE-9 bus system-Active distribution network: (highly unbalanced IEEE-13 bus distribution system (medium voltage) + modified CIGRE low voltage system). © 1986-2012 IEEE.

关键词： Power distribution networks

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Learning and Optimization over Robust Networked Systems

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Performance Evaluation Review 2025年第3期52卷 23-26页

作者： Lin, I-Cheng Department of Electrical and Computer Engineering Carnegie Mellon University United States

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A Modified Geometry-Based Analytical Model of Switched Reluctance Motor for Rapid Design Process

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IEEE Transactions on Industry Applications 2025年第3期61卷 3753-3763页

作者： Vadamodala, Lavanya Das, Shuvajit Chowdhury, Anik Sozer, Yilmaz Electrical and Computer Engineering Department University of Akron AkronOH United States

This paper presents a Modified Geometry-Based Analytical Model for Switched Reluctance Machines (SRM) to facilitate a rapid design process. The primary objectives involve enhancing the accuracy of flux linkage and torque predictions by introducing modifications to the conventional geometry-based analytical model. The proposed model accounts for the tapering of stator and rotor poles, providing a more realistic representation of SRM pole shapes. The analytical model also considers the basic geometric parameters like turns, phase current, and geometric dimensions that affect average torque and current density. Methodologically, the research employs analytical derivations based on the modified geometry, utilizing equations that consider the impact of fringing flux and saturation effects on iron. The Flux Linkage Models are used to calculate Co-energy and static torque as functions of rotor position. These models are crucial for understanding and predicting the energy characteristics and mechanical output of SRMs at different rotor positions. The model's validity is compared with Finite Element Analysis (FEA) and experimental results from an 18-slot 12 pole (18/12) SRM prototype. The study also conducts a comparative analysis with the conventional analytical model, demonstrating the improved accuracy achieved through the proposed modifications. © 2025 IEEE.

关键词： Reluctance motors

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Optimization of Magnetization State Manipulation in Variable-Flux PMSMs

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IEEE Transactions on Industry Applications 2025年第3期61卷 3862-3876页

作者： Orviz, Marcos Tiemblo, Javier G. Laborda, Diego F. Reigosa, David Guerrero, Juan M. Department of Electrical Electronic Computer and System Engineering University of Oviedo Gijon Spain

Variable-flux permanent magnet synchronous machines (VF-PMSMs) were proposed to avoid the additional losses of conventional PMSMs during flux weakening (FW) operation at high speeds, as they allow dynamic manipulation of the magnetization state (MS) of the permanent magnets (PMs). However, the effect of eddy currents induced in the PMs during MS manipulation has not yet been analyzed;this issue is evaluated in this paper. Different current waveforms (i.e., pulse, trapezoidal, and half-sinusoidal signals) will be compared regarding MS manipulation capabilities and energy consumption considering PMs eddy current effects, to identify the most advantageous one. © 1972-2012 IEEE.

关键词： Permanent magnets

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Double Oracle Algorithm for Game-Theoretic Robot Allocation on Graphs

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IEEE Transactions on Robotics 2025年 41卷 3244-3259页

作者： An, Zijian Zhou, Lifeng Department of Electrical and Computer Engineering Drexel University PA19104 United States

We study the problem of game-theoretic robot allocation where two players strategically allocate robots to compete for multiple sites of interest. Robots possess offensive or defensive capabilities to interfere and weaken their opponents to take over a competing site. This problem belongs to the conventional Colonel Blotto Game. Considering the robots' heterogeneous capabilities and environmental factors, we generalize the conventional Blotto game by incorporating heterogeneous robot types and graph constraints that capture the robot transitions between sites. Then we employ the Double Oracle Algorithm (DOA) to solve for the Nash equilibrium of the generalized Blotto game. Particularly, for cyclic-dominance-heterogeneous (CDH) robots that inhibit each other, we define a new transformation rule between any two robot types. Building on the transformation, we design a novel utility function to measure the game's outcome quantitatively. Moreover, we rigorously prove the correctness of the designed utility function. Finally, we conduct extensive simulations to demonstrate the effectiveness of DOA on computing Nash equilibrium for homogeneous, linear heterogeneous, and CDH robot allocation on graphs. © 2025 IEEE. All rights reserved,

关键词： Linear transformations

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NMS-KSD: Efficient Knowledge Distillation for Dense Object Detection via Non-Maximum Suppression and Feature Storage

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IEEE Access 2025年 13卷 80723-80736页

作者： Son, Suho Song, Byung Cheol Inha University Department of Electrical and Computer Engineering Incheon22212 Korea Republic of

Recently, many studies have proposed knowledge distillation (KD) frameworks for object detection. However, these frameworks did not take into account the inefficiencies caused by the teacher detector. The inefficiency refers to the computational cost incurred during the process of passing input data to the teacher model to acquire its knowledge. To solve this inefficiency in image classification, Fast Knowledge Distillation (FKD) was proposed, which stores the teacher model’s knowledge in advance and then uses it in the distillation process. However, directly applying FKD’s knowledge storage mechanism to dense object detectors causes a storage space problem. To address this issue, we propose NMS-KSD, a novel knowledge storage distillation method designed for dense object detection tasks. The core of NMS-KSD is the integration of Non-Maximum Suppression (NMS) and channel max pooling to effectively select and store key features from the teacher model’s intermediate feature maps. By storing and reusing these key features, NMS-KSD addresses the inefficiencies of traditional KD frameworks, significantly reducing training time while maintaining high performance. We validate the effectiveness and efficiency of our method across various dense object detectors through extensive experiments on the COCO, PASCAL VOC, and Cityscapes datasets. © 2013 IEEE.

关键词： Deep neural networks

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Compressing Neural Networks on Limited Computing Resources

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IEEE Access 2025年 13卷 80063-80075页

作者： Lee, Seunghyun Lee, Dongjun Hyun, Minju Kim, Heeje Song, Byung Cheol Inha University Department of Electrical and Computer Engineering Incheon22212 Korea Republic of

Network compression is a crucial technique for applying deep learning models to edge or mobile devices. However, the cost of achieving higher benchmark performance through compression is continuously increasing, making network compression a significant burden - especially for small industries focused on developing compact models. Specifically, existing network compression techniques often require extensive computational resources, rendering them impractical for edge devices and small-scale applications. To democratize network compression, we propose a general-purpose framework that combines novel filter pruning and knowledge distillation techniques. First, unlike conventional filter pruning methods based on static heuristics and costly neural architecture search (NAS)-based approaches, our method leverages meta-learning for rapid and fine examination of the importance of each gate. This enables rapid and stable sub-network discovery, significantly improving the pruning process. Second, to minimize the computational cost of knowledge distillation, we introduce a synthetic teacher assistant that leverages precomputed fixed knowledge - referring to the stored feature maps/logits of the teacher network. By leveraging fixed knowledge, we mitigate the cost incurred by the teacher network and facilitate the transmission of fixed knowledge to the student via synthetic teacher assistants, thereby preventing distribution collapse. Our proposed framework dramatically reduces the compression overhead while maintaining high accuracy, achieving a 55.2% reduction in FLOPs of ResNet-50 trained on ImageNet while preserving 76.2% top-1 accuracy with only 199 GPU hours - significantly lower than previous state-of-the-art methods. Overall, our framework democratizes deep learning compression by offering a cost-effective and computationally feasible solution, enabling broader adoption in low-resource environments. © 2013 IEEE.

关键词： Deep neural networks

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