期刊：
Electric Power Systems Research,2026年250:112102 ISSN：0378-7796
通讯作者：
Yong Li
作者机构：
College of Electrical and Information Engineering, Hunan University, Changsha, 410082, China;Greater Bay Area Institute for Innovation, Hunan University, Guangzhou, 511300, China;[Yijia Cao] School of Electrical & Information Engineering, Changsha University of Science and Technology, Changsha, 410114, China;[Fang Wu; Rui Li; Jiuqing Cai] Wuhan second ship design and research institute, Wuhan, 44227, China;[Yinglong Zhao; Yong Li; Sijia Hu] College of Electrical and Information Engineering, Hunan University, Changsha, 410082, China<&wdkj&>Greater Bay Area Institute for Innovation, Hunan University, Guangzhou, 511300, China
通讯机构：
[Yong Li] C;College of Electrical and Information Engineering, Hunan University, Changsha, 410082, China<&wdkj&>Greater Bay Area Institute for Innovation, Hunan University, Guangzhou, 511300, China
关键词：
Electrified ship;Electric power system;Transformer design;Vibration reduction;Finite element model;Multiple optimization
摘要：
The optimization of transformer vibration and power density in marine electrical power systems poses a challenging task due to the constraints imposed by ship noise and limited space. This paper introduces a multi-optimization design method for transformers based on multi-objective optimization model and finite element model, with the objective of minimizing vibration and improving power density. The proposed approach leverages the merits of both methodologies by initially utilizing a multi-objective optimization technique to attain an optimal transformer preliminary design, featuring optimized volume, loss, and vibration acceleration. Subsequently, based on this preliminary design, a finite element model is constructed to further refine the transformer’s placement configuration and thermal limits, ultimately yielding an optimal design scheme for a transformer that boasts both low vibration and high power density. Experimental results demonstrate that the proposed method effectively reducing transformer vibrations and volume. Compared to previous-generation transformers not utilizing this method, the proposed approach leads to a 55.81% reduction in vibrational acceleration and 44.93% reduction in volume. Additionally, the calculation values of the transformer from the proposed method exhibit high precision compared to actual measurements.
The optimization of transformer vibration and power density in marine electrical power systems poses a challenging task due to the constraints imposed by ship noise and limited space. This paper introduces a multi-optimization design method for transformers based on multi-objective optimization model and finite element model, with the objective of minimizing vibration and improving power density. The proposed approach leverages the merits of both methodologies by initially utilizing a multi-objective optimization technique to attain an optimal transformer preliminary design, featuring optimized volume, loss, and vibration acceleration. Subsequently, based on this preliminary design, a finite element model is constructed to further refine the transformer’s placement configuration and thermal limits, ultimately yielding an optimal design scheme for a transformer that boasts both low vibration and high power density. Experimental results demonstrate that the proposed method effectively reducing transformer vibrations and volume. Compared to previous-generation transformers not utilizing this method, the proposed approach leads to a 55.81% reduction in vibrational acceleration and 44.93% reduction in volume. Additionally, the calculation values of the transformer from the proposed method exhibit high precision compared to actual measurements.
作者机构：
[Xia, Xiangyang; Xia, Tian; Xia, XY; Yue, Jiahui] Changsha Univ Sci & Technol, Sch Elect & Informat Engn, Changsha 410114, Peoples R China.;[Gong, Yu] State Grid Jibei Elect Power Co Ltd, Beijing 100045, Peoples R China.;[Tan, Jianguo] Zhejiang Narada Power Source Co Ltd, Hangzhou 311300, Peoples R China.;[Wen, Lixing] Was Energy Technol Co Ltd, Xiangtan 411100, Peoples R China.
关键词：
lithium-ion battery;state of charge;Kalman filter algorithm;dung beetle optimizer
摘要：
Accurate prediction of the State of Charge (SOC) of lithium-ion batteries is the foundation for the stable and efficient operation of battery management systems. This paper proposes a lithium-ion battery SOC estimation method based on the Dung Beetle Optimizer (DBO), optimizing the second-order Kalman filter algorithm (DBO-DKF). Leveraging the DBO's fast convergence speed and strong global search capability, this method optimizes the Kalman filter algorithm in the parameter identification stage and the extended Kalman filter algorithm in the SOC estimation stage to address the issue of insufficient estimation accuracy caused by noise covariance matrices of input current and voltage measurements. Through the discharge of current tests under complex conditions, as well as comparing and analyzing credibility indicators such as MAE, RMSE, and MSE as measures of estimation accuracy, it can be verified that the proposed method effectively enhances SOC estimation accuracy.
摘要：
Accurate oscillation mode recognition and stability analysis based on big data are critical for the safe operation of wind turbine systems. This paper utilizes modern statistical and machine learning methodology to analyze the correlation between monitored wind turbine operation data and oscillation phenomena, and a system oscillation analysis and diagnosis method is proposed based on an improved association rule mining (ARM) model. Firstly, the oscillation modes in the power data are measured by the synchronous extraction transform. By improving the ARM model, a thorough study is conducted on the correlation between oscillation modes and variables such as wind speed, compensation degree, voltage fluctuation, etc. Finally, the component importance measure is used to optimize each element's risk weight calculation method relative to the system oscillation. The experiments demonstrate that the proposed association rule analysis method can effectively analyze the relationship between system oscillation phenomena and influencing factors and exhibits high diagnostic accuracy.
摘要：
Since the voltage amplitude of the arc suppression device is different during the normal operation and single line-to-ground fault, the problems of high cost and low module utilization rate are serious. An integrated grid-connected converter (IGCC) with reactive power compensation and fault regulation ability is proposed. First, the topology and operation mechanism of IGCC are introduced in this article. A common unit combining neutral point clamped (NPC) and cascaded H-bridge is formed by improving the traditional arc suppression device. By adding a fourth leg in the NPC module and connecting with the arc suppression inductance, the integration of the two structures is realized. The access of NPC unit not only reduces the number of modules of traditional arc suppression device, but also provides an integrated port for arc suppression device and reactive power compensation device. Second, the parameters of active and passive part of IGCC are optimally designed to ensure the stable operation of IGCC. In addition, compared with existing schemes, the superiority of IGCC in cost and volume is proved. Finally, the correctness, feasibility and effectiveness of the proposed topology and functions are verified by the simulation and experiment results.
摘要：
In the modular multilevel converter (MMC) based high voltage direct current (HVDC) practical projects, the existing voltage feedforward control (VFC) method presents challenges in addressing the frequency shift of high-frequency resonance (HFR) caused by the changes in the interconnected AC system's operating conditions. In this paper, the mathematical characterization function of the impedance real part is used to reveal the mechanism why the existing VFC cannot simultaneously reshape the multiple HFR risk regions into the positive damping characteristics. Therefore, a frequency divided voltage feedforward control (FDVFC) based on the second-order band-pass filters (BPFs) is proposed to simultaneously reshape the multiple HFR risk regions into the positive damping characteristics. The proposal includes the selection of the number of BPFs and how to design their parameters. The parameter design principles and parameter selection ranges of the BPFs are presented one by one using the simplified model of the MMC in high-frequency band. Finally, the effectiveness and correctness of the FDVFC and its analytical calculation expressions for parameter selection are verified by time-domain simulations.
摘要：
The integration of large-scale wind power clusters significantly reduces the inertia level of the power system, increasing the risk of frequency instability. Accurately assessing the equivalent virtual inertia of wind farms is critical for grid stability. Addressing the dual bottlenecks in existing inertia assessment methods, where physics-based modeling requires full control transparency and data-driven approaches lack interpretability for inertia response analysis, thus failing to reconcile commercial confidentiality constraints with analytical needs, this paper proposes a symbolic regression framework for inertia evaluation in doubly fed wind farms with limited control information constraints. First, a dynamic model for the inertia response of DFIG wind farms is established, and a mathematical expression for the equivalent virtual inertia time constant under different control strategies is derived. Based on this, a nonlinear function library reflecting frequency-active power dynamic is constructed, and a symbolic regression model representing the system's inertia response characteristics is established by correlating operational data. Then, sparse relaxation optimization is applied to identify unknown parameters, allowing for the quantification of the wind farm's equivalent virtual inertia. Finally, the effectiveness of the proposed method is validated in an IEEE three-machine nine-bus system containing a doubly fed wind power cluster. Case studies show that the proposed method can fully utilize prior model knowledge and operational data to accurately assess the system's inertia level with low computational complexity.
作者机构：
[Xu Jiang; Yusheng Zhou] School of Electrical and Information Engineering, Changsha University of Science and Technology, Changsha, China
会议名称：
2025 2nd International Conference on Smart Grid and Artificial Intelligence (SGAI)
会议时间：
21 March 2025
会议地点：
Changsha, China
会议论文集名称：
2025 2nd International Conference on Smart Grid and Artificial Intelligence (SGAI)
关键词：
electric railway catenary;high-frequency de-icing;skin effect;critical current
摘要：
The ice-covered of the electric railway catenary is one of the significant factors affecting railway operations. Aiming at the problems of low efficiency of traditional de-icing methods, this paper proposes to use the de-icing method based on high-frequency current. By enhancing the current frequency to enhance the conductor skin effect, increase the resistance value per unit length of the conductor, and effectively increase the heating power under the same energizing current. According to the physical process of high-frequency de-icing of ice-covered conductors in electric railway catenary, the calculation method of high-frequency de-icing critical current is deduced, and the effects of the thickness of the ice-covered, ambient temperature and external wind speed on the critical current of high-frequency de-icing are analyzed.
期刊：
IEEE Transactions on Power Systems,2025年:1-11 ISSN：0885-8950
作者机构：
[Yifu Luo; Fengzhe Dai] School of Electrical and Information Engineering, Changsha University of Science and Technology, Changsha, China;[Qinran Hu; Yuanshi Zhang; Tao Chen] School of Electrical and Engineering, Southeast University, Nanjing, China;[Bokang Zou; Qi Wang; Zenghui Li] School of Electrical and Automation Engineering, Nanjing Normal University, Nanjing, China
摘要：
The power system, as vital national infrastructure, is confronted with increasingly severe external attack threats. Current research has primarily focused on defensive layouts and loss analyses in the context of specific attack levels, neglecting the unpredictability of attacker's capability and lacking an endurance safety assessment for the power system. Compared to mainstream studies, the work reported in this paper presents a novel analytical scenario where a regional power system experiences complete failure due to the physical attack, aiming to develop a holistic vulnerability assessment method for localized power grids facing unknown attacker capability. The proposed method specifically establishes an Attack-Defense game model including two distinct objective functions with interdependent decision-making to maintain the resistance characteristic of the defender. Besides, based on the characteristics of the model, a customized method is proposed to solve and validate the original optimization problem through permutation problem. Simulation results based on the IEEE 14-bus and 118-bus systems verified the correctness of the proposed models. And a comparative analysis of various resource allocation schemes for national territorial defense has been conducted to validate the effectiveness of the assessment methodology.
期刊：
International Journal of Circuit Theory and Applications,2025年53(5):2834-2854 ISSN：0098-9886
通讯作者：
Liu, HW
作者机构：
[Liu, Hongwen; Yang, Qing] Chongqing Univ, State Key Lab Power Transmiss Equipment & Syst Sec, Chongqing 400044, Peoples R China.;[Liu, Hongwen] Yunnan Power Grid Co Ltd, Elect Power Res Insitute, Kunming, Peoples R China.;[Zeng, Xiangjun] Changsha Univ Sci & Technol, Sch Elect & Informat Engn, Changsha, Peoples R China.;[Chai, Chenchao] Yunnan Megasun Technol Co Ltd, Kunming, Peoples R China.
通讯机构：
[Liu, HW ] C;Chongqing Univ, State Key Lab Power Transmiss Equipment & Syst Sec, Chongqing 400044, Peoples R China.
关键词：
distribution network;extinction coil;ground fault controllable power supply;ground fault extinction
摘要：
A PI automatic adjustment method based on phase deviation fault residual voltage control is proposed to automatically and stably control the amplitude and phase of controllable voltage sources, achieving fast and effective arc suppression of grounding faults in distribution networks. Abstract Aiming at the problem that the current arc suppression method of coil cannot achieve full compensation. First, the calculation model of the full compensation parameters of the controllable voltage source is established by analyzing the grounding fault arc suppression principle of the independent controllable voltage source and the parallel arc suppression coil. Second, by analyzing the arc suppression characteristics of controllable voltage source, a PI automatic regulation method based on phase deviation‐fault residual voltage control is proposed. The method uses fault residual voltage and the change of output voltage amplitude of controllable voltage source to control the adjustment direction and fault residual voltage to control the output voltage amplitude of controllable voltage source. The simulation results show that when the capacitive current of the distribution network is 24.47 A, the fault residual voltage is 2.5 V and the residual current is 446 mA after compensation by the independent controllable voltage source. When the capacitive current is 40.8 A and the deharmonic degree of arc suppression coil is −9%, the fault residual voltage and residual current are 2.2 V and 60 mA after compensated by the parallel arc suppression coil of the controlled voltage source. The proposed PI control method exhibits good stability, resulting in low fault residual voltage, and outperforms traditional control methods, enhancing the arc extinction effect of ground faults.
关键词：
Fault location;Hybrid lines;Traveling wave method;Virtual time difference value;SOGWO
摘要：
Fault location accuracy of traveling wave method is constrained to the reliable traveling wave velocity. In this paper, a novel fault traveling waves location method is proposed to eliminate the effects of velocity uncertainty on hybrid lines’ fault location. The initial amplitude ratio coefficient (IARC) K is defined based on propagation characteristic analysis of initial fault traveling wave (IFTW) signals for hybrid lines, and the corresponding identification principle of fault line sections is derived from numerical relationships within different fault points’ K values. Then, taking into account the uncertainties of fault traveling wave (TW) velocity, a fault location method based on the virtual time difference is proposed. By comparing the difference value between the virtual time difference value and the real arrival time difference value of IFTW signals, the minimum difference value is defined as the objective function H. The fault location result is equal to the optimal fault distance value of the objective optimal model, so that the negative effects of velocity uncertainty are reduced. Besides, in order to search for the optimal value, a selected opposition-based grey wolf optimizer (SOGWO) is employed. Various fault scenarios are simulated, and the obtained results validate that the proposed approach is reliable for identifying fault sections and locating fault points in hybrid lines.
Fault location accuracy of traveling wave method is constrained to the reliable traveling wave velocity. In this paper, a novel fault traveling waves location method is proposed to eliminate the effects of velocity uncertainty on hybrid lines’ fault location. The initial amplitude ratio coefficient (IARC) K is defined based on propagation characteristic analysis of initial fault traveling wave (IFTW) signals for hybrid lines, and the corresponding identification principle of fault line sections is derived from numerical relationships within different fault points’ K values. Then, taking into account the uncertainties of fault traveling wave (TW) velocity, a fault location method based on the virtual time difference is proposed. By comparing the difference value between the virtual time difference value and the real arrival time difference value of IFTW signals, the minimum difference value is defined as the objective function H. The fault location result is equal to the optimal fault distance value of the objective optimal model, so that the negative effects of velocity uncertainty are reduced. Besides, in order to search for the optimal value, a selected opposition-based grey wolf optimizer (SOGWO) is employed. Various fault scenarios are simulated, and the obtained results validate that the proposed approach is reliable for identifying fault sections and locating fault points in hybrid lines.
摘要：
The frequent occurrence of motor faults has been a great disturbance to the development of production in various fields. Traditional fault diagnosis methods primarily use 1-D data or 2-D data. However, 3-D data hold significant promise for motor fault diagnosis due to its voluminous data and unique spatial information. This article aims to explore a motor fault diagnosis method leveraging 3-D data. Nonetheless, motor fault 3-D data exhibit the limitation of lacking geometric structure. To address this limitation, this article proposes a fault diagnosis method named SP-PointCNN. This method uses the proposed spherical projection (SP) method to mitigate the limitations present in the 3-D data of the motor. Meanwhile, a neural network based on PointCNN is constructed to enable the utilization of 3-D data in fault diagnosis. A series of experiments demonstrated the validity of the proposed method. After tested, the diagnosis accuracy of SP-PointCNN can reach 99.36%.
期刊：
High Voltage,2025年10(2):362-373 ISSN：2397-7264
通讯作者：
Wang, FP
作者机构：
[Wang, Feipeng; Du, Guoqiang; Pan, Lei; He, Yushuang; Li, Jian] Chongqing Univ, Sch Elect Engn, State Key Lab Power Transmiss Equipment Technol, Chongqing, Peoples R China.;[Yang, Hongming; He, Yushuang] Changsha Univ Sci & Technol, Sch Elect & Informat Engn, Changsha, Peoples R China.;[Zhang, Xiao] Naval Univ Engn, Natl Key Lab Sci & Technol Vessel Integrated Power, Natl Key Lab Vessel Integrated Power Syst Technol, Wuhan, Peoples R China.;[Zhang, Zhicheng] Xian Jiaotong Univ XJTU, Sch Chem, Xian Key Lab Sustainable Energy Mat Chem, Xian, Peoples R China.;[Wang, Kaizheng] Kunming Univ Sci & Technol, Fac Elect Engn, Kunming, Peoples R China.
通讯机构：
[Wang, FP ] C;Chongqing Univ, Sch Elect Engn, State Key Lab Power Transmiss Equipment Technol, Chongqing, Peoples R China.
摘要：
AbstractMetallised film capacitors (MFCs) are renowned for their unique self‐healing (SH) properties, which bestow them with exceptional reliability and stability in the face of intense electric fields, high voltages, and pulse power applications. Nonetheless, the exploration of SH characteristics concerning single‐layer dielectric film remains insufficient for advancing MFC reliability evaluation. To establish the theoretical correlation of SH characteristics from the device to the film in the MFCs, this work developed a simulation model to analyse the SH dynamic behaviour in the MFCs. The effects of coupling capacitors, arc resistance and insulation resistance on the macroscopic characteristics (voltage drop and pulse current) are focused during the SH process in MFCs. The results indicate that SH is primarily associated with the voltage drop duration rather than the sampling current. Consequently, the SH process in MFC is characterised as an abrupt decrease in voltage to its minimum value. This refinement enhances the SH energy dissipation model of MFC. The quantified relationship between the macroscopic characteristics and microstructure evolution (polypropylene decomposition and aluminium electrode vaporisation) is established in MFCs under diverse SH energy levels. As SH energy and duration increase, the proportion of energy attributed to polypropylene decomposition increases, resulting in multi‐layer ablation and adhesion within the metallised film and a pronounced deterioration in MFC electrical performance. The examination of macro–micro perspectives sheds new light on the intricate mechanisms governing the SH behaviour in MFCs, offering valuable insights for the advancement of their design, reliability evaluation, and performance optimisation in diverse electrical applications.
摘要：
Increasing multi-energy coordination in the ship necessitates advanced operation strategies to achieve greenhouse gas reduction and energy efficiency improvement in the maritime industry. However, previous research always overlooks onboard heterogeneous energy carriers and ship power distribution networks (SPDN), as well as underwater radiated noise (URN) generated by ship propellers. This will pose a huge threat to the operational safety of the multi-energy ship microgrids (MESMs) and further harm normal marine life. Hence, this paper formulates a coordinated model for a MESM with combined power, thermal, hydrogen, and freshwater flows. First, the joint energy management and voyage scheduling are modeled for the MESM, considering SPDN constraints and URN limits. Then, a copula-based two-stage operation structure with stochastic programming (SP) and rolling horizon (RH) methods is designed to tackle diverse uncertainties from onboard multi-energy loads and renewable energy. Finally, a progressive hedging (PH) algorithm is developed to support distributed calculation and accelerate the solution. Numerical case studies based on a real voyage in the Nordic countries are used to validate the effectiveness and superiority of the proposed model and method.
摘要：
This study aims to investigate SF 6 decomposition gases, specifically H 2 S, SO 2 , SOF 2 , and SO 2 F 2 , as a means of diagnosing faults in GIS. Using first-principles density functional theory (DFT), simulations were conducted on Zr- and In-modified WTe 2 from several perspectives, including adsorption energy, charge transfer, adsorption distance, density of states, differential charge density, and desorption times at different temperatures. The results demonstrate that the modification of WTe 2 with Zr and In atoms is spontaneous. The pristine WTe 2 exhibits weak physisorption towards all four SF 6 decomposition gases. In contrast, the Zr-WTe 2 system shows strong chemisorption for all four decomposition gases, while the In-WTe 2 system exhibits robust chemisorption specifically for SO 2 , SOF 2 , and SO 2 F 2 , with adsorption energies of −1.169 eV, −1.371 eV, and −1.255 eV, respectively. The Zr-WTe 2 system also demonstrates prolonged desorption times for H 2 S, SO 2 , SOF 2 , and SO 2 F 2 , suggesting its potential as a scavenger for SF 6 decomposition gases. Notably, the In-WTe 2 system exhibits a rapid desorption time of only 0.892 s for SOF 2 at room temperature, indicating its potential for detecting H 2 S gas under ambient conditions.
关键词：
IES-WTE;CCS-P2G;carbon trading;ladder-type GCT;ladder-type CET;low-carbon dispatch;synergistic interaction mechanism;multi-energy system optimization
摘要：
Waste-to-energy (WTE) is considered the most promising method for municipal solid waste treatment. An integrated energy system (IES) with carbon capture systems (CCS) and power-to-gas (P2G) can reduce carbon emissions. The incorporation of a "green-carbon" offset mechanism further enhances renewable energy consumption. Therefore, this study constructs a WTE-IES hybrid system, which conducts multi-dimensional integration of IES-WTP, CCS-P2G, photovoltaic (PV), wind turbine (WT), multiple energy storage technologies, and the "green-carbon" offset mechanism. It breaks through the limitations of traditional single-technology optimization and achieves the coordinated improvement of energy, environmental, and economic triple benefits. First, waste incineration power generation is coupled into the IES. A mathematical model is then established for the waste incineration and CCS-P2G IES. The CO2 produced by waste incineration is absorbed and reused. Finally, the "green-carbon" offset mechanism is introduced to convert tradable green certificates (TGCs) into carbon emission rights. This approach ensures energy demand satisfaction while minimizing carbon emissions. Economic incentives are also provided for the carbon capture and conversion processes. A case study of an industrial park is conducted for validation. The industrial park has achieved a reduction in carbon emissions of approximately 72.1% and a reduction in the total cost of approximately 33.5%. The results demonstrate that the proposed method significantly reduces carbon emissions. The energy utilization efficiency and system economic performance are also improved. This study provides theoretical and technical support for the low-carbon development of future IES.
关键词：
Photovoltaic power generation;Power outlier detection;Sunny day screening;Quantile regression recurrent neural network;Power output correlation
摘要：
Distributed photovoltaic (PV) power generation systems are widely spread. Moreover, due to the randomness of meteorological conditions and the complexity of installation environments, it is difficult to eliminate the interference of factors such as meteorological fluctuations in the monitoring of abnormal states of PV equipment. Based on this, this paper proposes a PV power generation anomaly detection method based on Quantile Regression Recurrent Neural Network (QRRNN). First, the characteristics of solar irradiance on clear days are analyzed, and the clear day masking method is used to eliminate the interference of cloudy and rainy weather. Then, the output correlation of different power stations is analyzed to obtain PV stations with high output correlation as the horizontal reference, which is used to exclude interferences such as permanent faults at the power stations. At the same time, vertical comparison of the output curves of the station under test on different clear days is conducted to eliminate interference factors such as weather and environmental conditions. Subsequently, the metered active power output data, which is free from interference, is input into the QRRNN model to obtain the normal active power output range of the PV. The power threshold of the normal output range is utilized to identify anomalies in PV power generation. Finally, simulation analysis of actual PV system data is conducted, and the results show that the method can effectively identify PV power generation anomalies and has high accuracy in PV fault detection.
Distributed photovoltaic (PV) power generation systems are widely spread. Moreover, due to the randomness of meteorological conditions and the complexity of installation environments, it is difficult to eliminate the interference of factors such as meteorological fluctuations in the monitoring of abnormal states of PV equipment. Based on this, this paper proposes a PV power generation anomaly detection method based on Quantile Regression Recurrent Neural Network (QRRNN). First, the characteristics of solar irradiance on clear days are analyzed, and the clear day masking method is used to eliminate the interference of cloudy and rainy weather. Then, the output correlation of different power stations is analyzed to obtain PV stations with high output correlation as the horizontal reference, which is used to exclude interferences such as permanent faults at the power stations. At the same time, vertical comparison of the output curves of the station under test on different clear days is conducted to eliminate interference factors such as weather and environmental conditions. Subsequently, the metered active power output data, which is free from interference, is input into the QRRNN model to obtain the normal active power output range of the PV. The power threshold of the normal output range is utilized to identify anomalies in PV power generation. Finally, simulation analysis of actual PV system data is conducted, and the results show that the method can effectively identify PV power generation anomalies and has high accuracy in PV fault detection.
关键词：
Computer crime;Location awareness;Hybrid power systems;Prevention and mitigation;Automation;Power distribution;Hardware;Cyber-physical system;cyber security;hybrid attack;bi-level resilient control;feeder automation
摘要：
Distributed feeder automation system (DFAs), as a promising protection technology for power distribution system (PDS) with distributed generation, its vulnerability to cyberattacks and hybrid attacks (contains both physical and cyberattacks) is gradually recognized and haunts utilities, creating potential risks for its large-scale applications. This paper proposes a novel bi-level resilient control solution (BRCS) deployed to DFAs without hardware burden. Two key modules are developed: 1) Lightweight distributed cyberattack detection module (DCDM), deployed into agents of DFAs, based on unsupervised learning to realize the quick detection and reporting of cyberattacks; 2) Robust centralized fault section localization module (CFSLM), installed in DFAs’ host workstation located in control center, achieving the correctly fault section localization and the high dimensionally awareness of attack events in cyberattack and hybrid attack scenarios. By adopting BRCS, outages and load losses caused by cyberattacks can be 100% avoided, and faults caused by physical attacks can be correctly isolated at once. Finally, the effectiveness and performance of the proposal are verified and conducted by the real two-feeder test platform with DFAs. In this process, a digital high-dimensional awareness and control unit is created against cyber and hybrid attacks, contributing to the system-level application of risk management and resilient control.
通讯机构：
[Huang, JC; Peng, ZY ] C;Changsha Univ Sci & Technol, Sch Energy & Power Engn, Key Lab Efficient & Clean Energy Utilizat, Changsha 410111, Peoples R China.
摘要：
Despite the advancements in film fabrication techniques for emerging perovskite solar cells, achieving a high-quality film by solution processing, while maintaining considerable performance remains a significant challenge. To tackle the issue of inferior CsPbI 2 Br perovskite films deposited via solution-based methods, a novel thermal conduction heating approach was devised and implemented, significantly enhancing film uniformity. Crucially, aliphatic amine acetates (3A) were introduced into the precursor solution to regulate the crystallization process and therefore to mitigate defects. Systematic investigation into the impact of 3A molecules featuring varying alkyl chain lengths on defect passivation revealed that the molecular dipole moment of these additives contributed to both defect mitigation and grain size refinement. Notably, the integration of alkyl chains significantly bolstered the hydrophobic properties of the perovskite film. Consequently, an impressive efficiency of 13.50% for HTM-free carbon-based CsPbI 2 Br perovskite solar cells was achieved, and the device exhibited robust stability retaining 92.4% of its initial efficiency at room temperature after being stored in dry air for 5400 h. This research offers profound insights into defect passivation mechanisms and perovskite crystallization dynamics, paving the way for further advancements in the field of perovskite solar cell technology.
摘要：
Water extraction from Synthetic Aperture Radar (SAR) images is crucial for water resource management and maintaining the sustainability of ecosystems. Though great progress has been achieved, there are still some challenges, such as an insufficient ability to extract water edge details, an inability to detect small water bodies, and a weak ability to suppress background noise. To address these problems, we propose the Global Context Attention Feature Fusion Network (GCAFF-Net) in this article. It includes an encoder module for hierarchical feature extraction and a decoder module for merging multi-scale features. The encoder utilizes ResNet-101 as the backbone network to generate four-level features of different resolutions. In the middle-level feature fusion stage, the Attention Feature Fusion module (AFFM) is presented for multi-scale feature learning to improve the performance of fine water segmentation. In the advanced feature encoding stage, the Global Context Atrous Spatial Pyramid Pooling (GCASPP) is constructed to adaptively integrate the water information in SAR images from a global perspective, thereby enhancing the network's ability to express water boundaries. In the decoder module, an attention modulation module (AMM) is introduced to rearrange the distribution of feature importance from the channel-space sequence perspective, so as to better extract the detailed features of water bodies. In the experiment, SAR images from Sentinel-1 system are utilized, and three different water areas with different features and scales are selected for independent testing. The Pixel Accuracy (PA) and Intersection over Union (IoU) values for water extraction are 95.24% and 91.63%, respectively. The results indicate that the network can extract more integral water edges and better detailed features, enhancing the accuracy and generalization of water body extraction. Compared with the several existing classical semantic segmentation models, GCAFF-Net embodies superior performance, which can also be used for typical target segmentation from SAR images.
作者机构：
[Liu, Rui; Zhang, Chuanliang; Chen, Jiaxiang; Wang, Ziyi] Changsha Univ Sci & Technol, Coll Energy & Power Engn, Changsha 410114, Peoples R China.;[Zhao, Bin] Changsha Univ Sci & Technol, Sch Elect & Informat Engn, Changsha 410114, Peoples R China.
通讯机构：
[Zhao, B ] C;Changsha Univ Sci & Technol, Sch Elect & Informat Engn, Changsha 410114, Peoples R China.
关键词：
Airfoil fin PCHE;Bezier curves;Pareto front;Multi-objective genetic algorithm;Comprehensive performance
摘要：
The airfoil fin (AFF) Printed circuit heat exchanger (PCHE) has attracted significant attention for its excellent comprehensive performance. This study proposes an optimized design for AFF PCHE to enhance the comprehensive performance by integrating Bézier curves, computational fluid dynamics (CFD), and multi-objective genetic algorithm (MOGA). A set of 12 Bézier curve-based variables is utilized to define and control the airfoil geometry, with optimization targets set on two comprehensive evaluation criteria: the first enhanced ratio (η1) and the third enhanced ratio (η3). The MOGA-generated Pareto front reveals the evolution of AFF structures in relation to η1 and η3. Results show that as the leading and trailing edges of the AFFs become sharper and the thickness decreases, the η1 of the PCHE channel gradually increases, while η3 decreases. Conversely, as the thickness of the AFFs increases and the trailing edge shape transitions from blunt to elliptical and finally to round, η3 significantly increases while η1 decreases. Furthermore, when changes focus mainly on the leading edge of the AFFs, η3 improves without markedly affecting η1. Compared to the traditional airfoil channel, the η1 of the Fin-b channel increases by 3.1%-10.8%, demonstrating its greater suitability under identical flow rate conditions. Similarly, the η3 of the Fin-g channel is 1.4%-11.6% higher than that of the traditional airfoil channel, highlighting its superior performance under identical pumping power conditions. The present work provides a valuable reference for optimizing the design of AFF PCHEs under identical flow rate and pumping power conditions.
The airfoil fin (AFF) Printed circuit heat exchanger (PCHE) has attracted significant attention for its excellent comprehensive performance. This study proposes an optimized design for AFF PCHE to enhance the comprehensive performance by integrating Bézier curves, computational fluid dynamics (CFD), and multi-objective genetic algorithm (MOGA). A set of 12 Bézier curve-based variables is utilized to define and control the airfoil geometry, with optimization targets set on two comprehensive evaluation criteria: the first enhanced ratio (η1) and the third enhanced ratio (η3). The MOGA-generated Pareto front reveals the evolution of AFF structures in relation to η1 and η3. Results show that as the leading and trailing edges of the AFFs become sharper and the thickness decreases, the η1 of the PCHE channel gradually increases, while η3 decreases. Conversely, as the thickness of the AFFs increases and the trailing edge shape transitions from blunt to elliptical and finally to round, η3 significantly increases while η1 decreases. Furthermore, when changes focus mainly on the leading edge of the AFFs, η3 improves without markedly affecting η1. Compared to the traditional airfoil channel, the η1 of the Fin-b channel increases by 3.1%-10.8%, demonstrating its greater suitability under identical flow rate conditions. Similarly, the η3 of the Fin-g channel is 1.4%-11.6% higher than that of the traditional airfoil channel, highlighting its superior performance under identical pumping power conditions. The present work provides a valuable reference for optimizing the design of AFF PCHEs under identical flow rate and pumping power conditions.
