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Enhancing Network Abnormal Detection With NMF-SECNN: Leveraging Deep Feature Learning for High-Precision Traffic Analysis

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IEEE Transactions on Network Science and engineering 2025年第3期12卷 2069-2080页

作者： Yuan, Yazhou Yu, Ning Zheng, Zhuolin Yang, Yong Ma, Kai Liu, Zhixin Chen, Cailian Zhang, Jianmin Yanshan University Institute of Electrical Engineering Qinhuangdao066004 China Yanshan University Key Laboratory of Intelligent Control and Neural Information Processing of the Ministry of Education of China Qinhuangdao066004 China State Grid Handan Electric Power Supply Company Hebei 056000 China Shanghai Jiao Tong University Department of Automation Shanghai200240 China Ministry of Education of China Key Laboratory of System Control and Information Processing Shanghai200240 China Baosteel Research Institute Automation Department Shanghai200240 China

Detection of abnormalities in industrial network traffic plays a crucial role in maintaining network system security. However, current abnormal detection models suffer from low precision, and extracting deep-level feature information from industrial network traffic is difficult. This leads to the loss of partial feature information during the detection process, thereby affecting detection efficiency. To address this issue, this paper proposes an abnormal traffic detection framework for industrial networks. By employing a Non-negative Matrix Factorization (NMF)-based method for extracting abnormal traffic features and optimizing the NMF decomposition process through constructing label consistency constraints, we facilitate effective feature extraction. Additionally, the Squeeze-and-Excitation attention mechanism is introduced into a Convolutional Neural Network (CNN) to construct a classifier that enhances detection precision without increasing complexity, enabling efficient identification of complex network traffic patterns. This results in the NMF-Squeeze-and-Excitation-CNN (NMF-SECNN) model, which combines effective feature extraction capability with a lightweight structural design, achieving superior detection performance in industrial network environments. The proposed method achieves a detection accuracy of 99.4%, representing a 5.6% improvement over baseline methods, and a recall rate of 98.2%, showcasing the model's capability to identify abnormalities across diverse scenarios. Various classification metrics confirm the model's robustness and effectiveness, demonstrating its significant advantages over traditional methods. © 2013 IEEE.

关键词： Non-negative matrix factorization

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Resilient Cooperative control of Multiple DC Microgrids With Interconnection Networks Against Cyber Attacks

IEEE Transactions on Industrial Cyber-Physical Systems

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IEEE Transactions on Industrial Cyber-Physical systems 2025年 3卷 116-126页

作者： Xiao, Feng Liu, Shiyu Wei, Bo Fang, Fang Qin, Jiahu North China Electric Power University State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources Beijing102206 China North China Electric Power University School of Control and Computer Engineering Beijing102206 China North China Electric Power University New Energy Generation National Engineering Research Center Beijing102206 China University of Science and Technology of China Department of Automation Hefei230027 China

The two control objectives of voltage regulation and precise current sharing are conflicting in multi-bus DC microgrids. In this paper, a distributed control strategy is proposed, and it can achieve accurate current sharing and regulate the voltage of a critical node to the rated value. However, such a distributed control system is susceptible to potential cyber attacks that could deteriorate microgrids performances by corrupting communication links or actuators. To overcome these difficulties, we design the interconnected communication networks to establish a resilient cooperative system of multiple microgrids against unknown bounded injection attacks. The proposed resilient control strategy can achieve the control objectives of maintaining voltage regulation and current sharing within each microgrids under different operating conditions, and the interconnected system consisting of multiple microgrids cooperates to mitigate the adverse effect of cyber attacks. The dynamics and stability of the overall close-loop system of the DC microgrids are analyzed, in the present or absent of cyber attacks. Simulation results validate the effectiveness of the proposed approach in two 4-bus DC microgrids. © 2023 IEEE.

关键词： Cyber attacks

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Improved Insulation Properties of Polypropylene With Highly Orientated Lamellar Induced by NonIsothermal Shear Stress

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IET Nanodielectrics 2025年第1期8卷

作者： Huang, Lei Song, Yan-Hui Yin, Li-Juan Zhong, Shao-Long Dang, Zhi-Min Department of Electrical Engineering State Key Laboratory of Power System Operation and Control Tsinghua University Beijing China ZhongYuan Electric Laboratory Xuchang China

Polypropylene plays an irreplaceable role in electrical insulation and electrostatic capacitors and has been extensively studied with its microstructure and insulation properties optimised for high-power density miniaturised devices. The extrinsic modifiers or industrial upgrading have not yet achieved a remarkable breakthrough in either concise theory or comprehensive performance. Here, we develop a nonisothermal shear process on melt to regulate the nucleation density and the lamellar orientation along the surface and reveal pore defects in disorder boundaries between spherulites as the microscopic nature of the property bottleneck. The high-rated shear process induces a crystallographic surface texture of (1 1 0) planes from which the elimination of micro-defect benefits. Our high-rated shear strategy achieves an excellent dielectric strength of 573.7 MV/m with an increase of 33% and an improved insulation resistance by 130% at 100 MV/m with the minimised absorption of injected current. © 2025 The Author(s). IET Nanodielectrics published by John Wiley & Sons Ltd on behalf of The Institution of engineering and Technology.

关键词： Crystal orientation

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False Data Injection Detection in power system Based on LOSSA-AdaBoostDT

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Protection and control of Modern power systems 2025年第3期10卷 55-64页

作者： Xi, Lei Tian, Xilong He, Miao Cheng, Chen College of Electrical Engineering & New Energy China Three Gorges University Hubei Provincial Key Laboratory for Operation and Control of Cascaded Hydropower Station Yichang443002 China Qianjiang Power Supply Company State Grid Hubei Electric Power Co. Ltd. Qianjiang433100 China Jingzhou Power Supply Company State Grid Hubei Electric Power Co. Ltd. Jingzhou434000 China Southern Power Grid Co. Ltd. Foshan Supply Bureau Leliu Power Supply Station Foshan528000 China

The attack of false data injection can contaminate the measurements acquired from the supervisory control and data acquisition (SCADA) system, which can seriously endanger the safety and stability of power system operations. The conventional machine learning attack detection methods use a single strong classifier and are difficult to solve the problem of overfitting, making them lack of generalization ability. On the other hand, most existing dimension reduction approaches based on feature extraction can change the original physical meanings of measurements. Here, a novel method is proposed based on feature selection and ensemble learning to solve the above problems. Squirrel search algorithm combines Latin hypercube sampling and opposition-based learning to form an improved algorithm with strong global search ability for feature selection. This avoids the problem of feature extraction changing the original physical meanings of measurements. Besides, the classifier based on adaptive boosting decision tree ensemble learning algorithm with stronger generalization ability is used to distinguish the false data injection. Simulation results using the IEEE 14-bus and IEEE 57-bus test systems verify the proposed method with higher performance of detection compared with other widely adopted methods. © 2019 power system Protection and control Press.

关键词： Adaptive boosting

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Performance-Aware control of Modular Batteries For Fast Frequency Response

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IEEE Transactions on Sustainable Energy 2025年

作者： He, Yutong Ruan, Guangchun Zhong, Haiwang Tsinghua University State Key Laboratory of Power System Operation and Control Department of Electrical Engineering Beijing100084 China Massachusetts Institute of Technology Lab for Information and Decision Systems CambridgeMA02139 United States

Modular batteries can be aggregated to deliver frequency regulation services for power grids. Although utilizing the idle capacity of battery modules is financially attractive, it remains challenging to consider the heterogeneous module-level characteristics such as dynamic operational efficiencies and battery degradation. In addition, real-time decision making within seconds is required to enable fast frequency response. In order to address these issues, this paper proposes a performance-aware scheduling approach for battery modules to deliver fast frequency response (FFR) support. In particular, the conduction loss and switching loss of battery packs as well as converters are captured within a mix-integer quadratic constrained program (MIQCP). The cycle-based aging model identifies the aging cost of battery modules during frequent cycling by introducing the aging subgradient calculation and linearization. Case studies based on real-world battery data show that the proposed scheduling approach can effectively reduce power loss cost by nearly 28%-57% and battery aging cost by 4%-15% compared to conventional methods, which can also enhance the SoC balance. © 2010-2012 IEEE.

关键词： Battery management systems

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Energy-carbon comprehensive efficiency evaluation of hydrogen metallurgy system considering low-temperature waste heat recovery

arXiv

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arXiv 2025年

作者： Ji, Qiang Cheng, Lin Liang, Zeng Zhuang, Yingrui Shi, Fashun Zhang, Jianliang Li, Kejiang State Key Laboratory of Power Power System Operation and Control Department of Electrical Engineering Tsinghua University Beijing100084 China School of Metallurgical and Ecological Engineering University of Science and Technology Beijing Beijing100083 China

To address the lack of energy-carbon efficiency evaluation and the underutilization of low-temperature waste heat in traditional direct reduction iron (DRI) production, this paper proposes a novel zero-carbon hydrogen metallurgy system that integrates the recovery and utilization of low-temperature and high-temperature waste heat, internal energy, and cold energy during hydrogen production, storage, reaction and circulation. Firstly, the detailed mathematical models are developed to describe energy and exergy characteristics of the operational components in the proposed zero-carbon hydrogen metallurgy system. Additionally, energy efficiency, exergy efficiency, and energy-carbon efficiency indices are introduced from a full life-cycle perspective of energy flow, avoiding the overlaps in energy inputs and outputs. Subsequently, the efficiency metrics of the proposed zero-carbon hydrogen metallurgy system are then compared with those of traditional DRI production systems with H2/CO ratios of 6:4 and 8:2. The comparative results demonstrate the superiority and advancement of the proposed zero-carbon hydrogen metallurgy system. Finally, sensitivity analysis reveals that the overall electricity energy generated by incorporating the ORC and expander equipments exceeds the heat energy recovered from the furnace top gas, highlighting the energy potential of waste energy utilization. Copyright © 2025, The Authors. All rights reserved.

关键词： Low temperature production

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A Quasi-Parallel Resonant Switched Capacitor DC-DC Converter with Wide Input Voltage Range Regulation and Enhanced Dynamic Performances

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IEEE Journal of Emerging and Selected Topics in power Electronics 2025年

作者： Qi, Jingjing Wu, Xuezhi Sun, Kai Tsinghua University State Key Laboratory of Power System Operation and Control Department of Electrical Engineering Beijing100084 China Beijing Jiaotong University National Active Distribution Network Technology Research Center Beijing100044 China

Wide-range and high-efficiency DC-DC converters are in high demand for various applications, such as distributed systems, electric vehicles, and DC buildings. Resonant switched capacitor converters (ReSCC) can achieve soft switching, have small passive device capacity, and exhibit low voltage stress, but the voltage ratio is difficult to be regulated continuously. In this paper, a quasi-parallel resonant switched capacitor DC-DC converter is proposed to satisfy the design requirements, which incorporates a ReSCC with soft-switching and variable voltage ratio, as well as a Buck converter. In addition, a simplified optimal trajectory controller for ReSCC is investigated, which can be combined with PI controller of Buck converter to enhance the load transient of the proposed converter. Moreover, the input voltage feedforward control is implemented with the optimized feedforward coefficient to suppress the input voltage disturbance. The proposed converter can achieve high efficiency and rapid dynamic response over a wide conversion range. The correctness of the theoretical analyses is verified by a 36V∼60V-5V/20A prototype. © 2013 IEEE.

关键词： Capacitor bank

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Sharing energy in wider area: A two-layer energy sharing scheme for massive prosumers

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Applied Energy 2025年 392卷

作者： Su, Yifan Yang, Peng Kang, Kai Wang, Zhaojian Qi, Ning Liu, Tonghua Liu, Feng State Key Laboratory of Power Transmission Equipment Technology School of Electrical Engineering Chongqing University Chongqing400044 China School of Electronics and Information Xi'an Polytechnic University Xi'an710048 China State Key Laboratory of Power System Operation and Control Department of Electrical Engineering Tsinghua University Beijing100084 China Key Laboratory of System Control and Information Processing Ministry of Education of China Department of Automation Shanghai Jiao Tong University Shanghai200240 China Department of Earth and Environmental Engineering Columbia University New YorkNY10027 United States

The popularization of distributed energy resources transforms end-users from consumers into prosumers. Inspired by the sharing economy principle, energy sharing markets for prosumers are proposed to facilitate the utilization of renewable energy. This paper proposes a novel two-layer energy sharing market for massive prosumers, which can promote social efficiency by wider-area sharing. In this market, there is an upper-layer energy sharing market (U-ESM) in the distribution system and numerous lower-layer energy sharing markets (L-ESMs) in local communities. Prosumers in the same community share energy with each other in the L-ESM, which can be uncleared. The energy surplus and shortage of L-ESMs are cleared in the U-ESM. Thanks to the wider-area two-layer structure, the market outcome is near-social-optimal in large-scale systems. However, the proposed market forms a complex mathematical program with equilibrium constraints (MPEC). To solve the problem, we propose an efficient and hierarchically distributed bidding algorithm. The proposed two-layer market and bidding algorithm are verified on the IEEE 123-bus system with 11,250 prosumers, which demonstrates the practicality and efficiency for large-scale markets. © 2025 Elsevier Ltd

关键词： Game theory

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Selection for Schottky Barrier Diodes with Various On-Resistance in Full-SiC Voltage Source Converters

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IEEE Transactions on Industry Applications 2025年

作者： Chen, Yuzhi Li, Chi Liu, Jianwei Wu, Yifan Liu, Zicheng Zheng, Zedong Tsinghua University State Key Laboratory of Power System Operation and Control Department of Electrical Engineering Beijing 100084 China Huazhong University of Science and Technology State Key Laboratory of Advanced Electromagnetic Engineering and Technology School of Electrical and Electronic Engineering Wuhan 430074 China

In Silicon Carbide based voltage source converters (VSCs), pairing Schottky barrier diodes (SBDs) presents trade-offs. While SBDs reduce the freewheeling loss and mitigate the adverse effects of bipolar conduction, their junction capacitance also contributes to increased switching loss. This paper proposes a systematic selection strategy for SBDs aimed at enhancing converter efficiency, using on-resistance as the design variable. A three-phase VSC with 1.2 kV MOSFETs and four sets of 1.2 kV SBDs is demonstrated as the case study. The static and switching characteristics for MOSFET/SBD pair are measured and analyzed over a wide temperature range. VSC efficiency is evaluated in both inverter and rectifier modes under different operating conditions. It appears that VSC using SBDs with 126% of the MOSFETs' resistance exhibits an overall superior performance. A 4 kW full-SiC VSC prototype is developed to validate the proposed selection strategy. Compared to other SBDs, using the recommended selection enhances VSC efficiency by up to 2% (± 0.5%) under light loads while maintaining high performance under medium and heavy loads. Compared to freewheeling by the body diode, using the recommended selection enhances VSC efficiency by an average of 0.4% (± 0.1%) across nearly the entire load range. © 1972-2012 IEEE.

关键词： efficiency on-resistance Schottky barrier diodes selection strategy SiC MOSFETs voltage source converter

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Performance-Aware control of Modular Batteries For Fast Frequency Response

arXiv

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arXiv 2025年

作者： He, Yutong Ruan, Guangchun Zhong, Haiwang State Key Laboratory of Power System Operation and Control Department of Electrical Engineering Tsinghua University Beijing100084 China Lab for Information and Decision Systems Massachusetts Institute of Technology CambridgeMA02139 United States

关键词： Battery management systems

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