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Assessment on gas-polyethylene terephthalate solid interface partial discharge properties of C4F7N/CO_(2)gas mixture for eco-friendly gas insulating transformer

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High Voltage 2024年第1期9卷 35-45页

作者： Song Xiao Yifan Wang Chenhua Ren Haoran Xia Yue Zhao Jingzi Qin Xiaoxing Zhang Yi Luo Yi Li State Key Laboratory of power grid Environmental Protection School of Electrical Engineering and AutomationWuhan UniversityWuhanHubeiChina Beijing International S&T Cooperation Base for Plasma Science and energy Conversion Institute of Electrical EngineeringChinese Academy of SciencesBeijingChina State grid Anhui Electric power Company Anhui Electric power research Institute HefeiAnhuiChina hubei engineering research center for safety monitoring of new energy and power grid equipment School of Electrical and Electronic EngineeringHubei University of TechnologyWuhanHubeiChina

The eco-friendly insulating gas perfluoroisobutyronitrile(C_(4)F_(7)N)is potentially used in gas-insulated transformers(GIT)to replace sulphur hexafluoride(SF_(6)).However,evaluation of the long-term insulation reliability and gas–solid interface discharge decomposition characteristics of the gas–solid film insulation structure in GIT is *** authors simulated the gas–solid film insulation structure in GIT and explored the interface partial discharge(PD)characteristics of C4F7N/CO_(2)gas mixture with polyethylene terephthalate(PET).The effect of gas pressure,mixing ratio on gas–solid interface gas decomposition,PET degradation was investigated,and the interaction mechanism was *** is found that the interface PD generated three degradation regions on a PET *** gas–solid interface reaction in the electrode contact region and the discharge development trace was significantly higher than that of halation *** content of gas decomposition products decreases with the increase of gas pressure and the PD intensity of SF6-PET is inferior to that of C_(4)F_(7)N/CO_(2)under the same *** results provide reference for the development and application of C_(4)F_(7)N/CO_(2)based GIT.

关键词： interface solid insulation

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Single flow treatment degradation of antibiotics in water using falling-film dielectric barrier discharge

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Plasma Science and Technology 2024年第4期26卷 27-36页

作者：许志远章程伍云健黄邦斗席登科张晓星邵涛 hubei engineering research center for safety monitoring of new energy and power grid equipment Hubei University of TechnologyWuhan 430068People’s Republic of China Beijing International S&T Cooperation Base for Plasma Science and energy Conversion Institute of Electrical EngineeringChinese Academy of SciencesBeijing 100190People’s Republic of China University of Chinese Academy of Sciences Beijing 100049People’s Republic of China

The environmental contamination caused by antibiotics is increasingly conspicuous due to their widespread manufacture and misuse. Plasma has been employed in recent years for the remediation of antibiotic pollution in the environment. In this work, a falling-film dielectric barrier discharge was used to degrade the antibiotic tetracycline(TC) in water. The reactor combined the gas-liquid discharge and active gas bubbling to improve the TC degradation performance. The discharge characteristics, chemical species’ concentration, and degradation rates at different parameters were systematically studied. Under the optimized conditions(working gas was pure oxygen, liquid flow rate was 100 mL/min, gas flow rate was 1 L/min,voltage was 20 kV, single treatment), TC was removed beyond 70% in a single flow treatment with an energy efficiency of 145 mg/(kW·h). The reactor design facilitated gas and liquid flow in the plasma area to produce more ozone in bubbles after a single flow under pure oxygen conditions, affording fast TC degradation. Furthermore, long-term stationary experiment indicated that long-lived active species can sustain the degradation of TC. Compared with other plasma treatment systems, this work offers a fast and efficient degradation method, showing significant potential in practical industrial applications.

关键词： antibiotic degradation dielectric barrier discharge reactive species single flow treatment

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Editorial:The development of eco-friendly insulating gases and SF6-free equipment for‘net-zero’

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High Voltage 2024年第1期9卷 1-1页

作者： Song Xiao Yi Li Ju Tang Xiaoxing Zhang State Key Laboratory of power grid Environmental Protection School of Electrical Engineering and AutomationWuhan UniversityWuhanHubeiChina hubei engineering research center for safety monitoring of new energy and power grid equipment School of Electrical and Electronic EngineeringHubei University of TechnologyWuhanHubeiChina

Developing low-carbon gas insulated transmission and distribution equipment is essential to achieve the‘carbon peak,carbon neutralisation’or‘net-zero’in the power *** have carried out various research on the eco-friendly insulating gas(such as C4F7N,C5F10O)and next-generation SF6-free equipment to gradually reduce the utilisation of strong greenhouse gas SF6.

关键词： SF6 carbon free

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Short-Term Household Load Forecasting Based on Attention Mechanism and CNN-ICPSO-LSTM

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energy engineering 2024年第6期121卷 1473-1493页

作者： Lin Ma Liyong Wang Shuang Zeng Yutong Zhao Chang Liu Heng Zhang Qiong Wu Hongbo Ren new energy Technology center State Grid Beijing Electric Power Research InstituteBeijing100075China College of energy and Mechanical engineering Shanghai University of Electric PowerShanghai200090China

Accurate load forecasting forms a crucial foundation for implementing household demand response plans andoptimizing load scheduling. When dealing with short-term load data characterized by substantial fluctuations,a single prediction model is hard to capture temporal features effectively, resulting in diminished predictionaccuracy. In this study, a hybrid deep learning framework that integrates attention mechanism, convolution neuralnetwork (CNN), improved chaotic particle swarm optimization (ICPSO), and long short-term memory (LSTM), isproposed for short-term household load forecasting. Firstly, the CNN model is employed to extract features fromthe original data, enhancing the quality of data features. Subsequently, the moving average method is used for datapreprocessing, followed by the application of the LSTM network to predict the processed data. Moreover, the ICPSOalgorithm is introduced to optimize the parameters of LSTM, aimed at boosting the model’s running speed andaccuracy. Finally, the attention mechanism is employed to optimize the output value of LSTM, effectively addressinginformation loss in LSTM induced by lengthy sequences and further elevating prediction accuracy. According tothe numerical analysis, the accuracy and effectiveness of the proposed hybrid model have been verified. It canexplore data features adeptly, achieving superior prediction accuracy compared to other forecasting methods forthe household load exhibiting significant fluctuations across different seasons.

关键词： Short-term household load forecasting long short-term memory network attention mechanism hybrid deep learning framework

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Non-intrusive Load monitoring Based on Graph Total Variation for Residential Appliances

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Journal of Modern power Systems and Clean energy 2024年第3期12卷 947-957页

作者： Xiaoyang Ma Diwen Zheng Xiaoyong Deng Ying Wang Dawei Deng Wei Li the College of Electrical engineering Sichuan UniversityChengdu 610065China State grid Chongqing Electric power Company Chongqing 400014China State grid Sichuan Electric power Company Chengdu 610095China State grid hubei Electric power Company Limited research Institute Wuhan 430077China

Non-intrusive load monitoring is a technique for monitoring the operating conditions of electrical appliances by collecting the aggregated electrical information at the household power *** several studies on the mining of unique load characteristics,few studies have extensively considered the high computational burden and sample *** on lowfrequency sampling data,a non-intrusive load monitoring algorithm utilizing the graph total variation(GTV)is proposed in this *** algorithm can effectively depict the load state without the need for prior ***,the combined Kmeans clustering algorithm and graph signals are used to build concise and accurate graph structures as load *** GTV representing the internal structure of the graph signal is introduced as the optimization model and solved using the augmented Lagrangian iterative *** introduction of the difference operator reduces the computing cost and addresses the inaccurate reconstruction of the graph *** low-frequency sampling data,the algorithm only requires a little prior data and no training,thereby reducing the computing *** conducted using the reference energy disaggregation dataset and almanac of minutely power dataset demonstrated the stable superiority of the algorithm and its low computational burden.

关键词： Non-intrusive load monitoring graph total variation augmented Lagrangian function smart grid

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Steady-state Voltage Security-constrained Optimal Frequency Control for Weak HVDC Sending-end AC power Systems

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Journal of Modern power Systems and Clean energy 2024年第2期12卷 658-669页

作者： Qiangqiang Wang Liangzhong Yao Jian Xu Yuping Zheng Wei Li Wei Wang School of Electrical engineering and Automation Wuhan UniversityWuhan 430072China hubei engineering and Technology research center for AC/DC Intelligent Distribution Network(Wuhan University) Wuhan 430072China State Key Laboratory of Smart grid Protection and Control NARI Group Corporation(State Grid Electric Power Research Institute)Nanjing 211106China

Due to the fact that a high share of renewable energy sources(RESs)are connected to high-voltage direct current(HVDC)sending-end AC power systems,the voltage and frequency regulation capabilities of HVDC sending-end AC power systems have *** has resulted in potential system operating problems such as overvoltage and overfrequency,which occur simultaneously when block faults exist in the HVDC *** this study,a steady-state voltage security-constrained optimal frequency control method for weak HVDC sending-end AC power systems is *** integrated virtual inertia control of RESs is employed for system frequency *** dynamic reactive power compensation devices are utilized to control the voltage of all nodes meet voltage security ***,an optimization model that simultaneously considers the frequency and steady-state voltage security constraints for weak HVDC sending-end AC power systems is *** optimal control scheme with the minimum total cost of generation tripping and additional dynamic reactive power compensation required is obtained through the optimization *** are conducted on a modified IEEE 9-bus test system and practical Qing-Yu line commutated converter based HVDC(LCC-HVDC)sending-end AC power system to verify the effectiveness of the proposed method.

关键词： Renewable energy source(RES) high-voltage direct current(HVDC) AC power system optimal frequency control steady-state voltage security dynamic reactive power compensation

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Multi-Time Scale Operation and Simulation Strategy of the Park Based on Model Predictive Control

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energy engineering 2024年第3期121卷 747-767页

作者： Jun Zhao Chaoying Yang Ran Li Jinge Song grid center State Grid Shanxi Electric Power Company Electric Power Science Research InstituteTaiyuan030000China

Due to the impact of source-load prediction power errors and uncertainties,the actual operation of the park will have a wide range of fluctuations compared with the expected state,resulting in its inability to achieve the expected *** paper constructs an operating simulation model of the park power grid operation considering demand response and proposes a multi-time scale operating simulation method that combines day-ahead optimization and model predictive control(MPC).In the day-ahead stage,an operating simulation plan that comprehensively considers the user’s side comfort and operating costs is proposed with a long-term time scale of 15 *** order to cope with power fluctuations of photovoltaic,wind turbine and conventional load,MPC is used to track and roll correct the day-ahead operating simulation plan in the intra-day stage to meet the actual operating operation status of the ***,the validity and economy of the operating simulation strategy are verified through the analysis of arithmetic examples.

关键词： Demand response model predictive control multiple time scales operating simulation

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Optimal Planning of Hybrid AC/DC Low-voltage Distribution Networks Considering DC Conversion of Three-phase Four-wire Low-voltage AC Systems

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Journal of Modern power Systems and Clean energy 2024年第1期12卷 141-153页

作者： Bo Zhang Lu Zhang Wei Tang Gen Li Chen Wang the College of Information and Electrical engineering China Agricultural UniversityBeijing 100083China the Electric energy Group Department of Engineering TechnologyTechnical University of Denmark(DTU)2750 BallerupDenmark the power Distribution Technology center State Grid Beijing Electric Power Research InstituteBeijing 100075China

The increasing integration of distributed household photovoltaics(PVs)and electric vehicles(EVs)may further ag gravate voltage violations and unbalance of low-voltage distribu tion networks(LVDNs).DC distribution networks can increase the accommodation of PVs and EVs and mitigate mutilple pow er quality problems by the flexible power regulation capability of voltage source *** paper proposes schemes to es tablish hybrid AC/DC LVDNs considering the conversion of the existing three-phase four-wire low-voltage AC systems to DC op *** characteristics and DC conversion constraints of typical LVDNs are *** addition,converter configura tions for typical LVDNs are proposed based on the three-phase four-wire characteristics and quantitative analysis of various DC ***,an optimal planning method of hybrid AC/DC LVDNs is proposed,which is modeled as a bi-level programming model considering the annual investments and three-phase *** are conducted to verify the effectiveness of the proposed optimal planning *** ulation results show that the proposed optimal planning method can increase the integration of PVs while simultaneously reduc ing issues related to voltage violation and unbalance.

关键词： Optimal planning low-voltage distribution net work three-phase unbalance DC conversion

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Equivalent Impedance Parameter Calculation of Three-phase Symmetrical Loads for Harmonic Source Location

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Journal of Modern power Systems and Clean energy 2024年第1期12卷 251-260页

作者： Yi Zhang Bijie Liu Caihua Lin Zhenguo Shao Yuncong Xu the Department of Electrical engineering and Automation Fuzhou UniversityFuzhouChina State grid Fujian Electric power research Institute FuzhouChina

The equivalent impedance parameters of loads have been widely used to identify and locate the harmonic ***,the existing calculation methods suffer from outliers caused by the zero-crossing of the *** outliers can result in inaccuracy and unreliability of harmonic source *** address this issue,this paper proposes an innovative method of equivalent impedance parameter calculation of three-phase symmetrical loads that avoid *** correctness and effectiveness of the proposed method are verified by simulations on Simulink using actual monitoring *** results show that the proposed method is not only simple and easy to implement but also highly accurate.

关键词： abc-αβtransformation equivalent impedance parameters of load harmonic source location nonlinear load power quality

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Deep Reinforcement Learning Based Resource Allocation for Fault Detection with Cloud Edge Collaboration in Smart grid

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CSEE Journal of power and energy Systems 2024年第3期10卷 1220-1230页

作者： Qiyue Li Yadong Zhu Jinjin Ding Weitao Li Wei Sun Lijian Ding Hefei University of Technology engineering Technology research center of Industrial Automation Hefei 230009China Electric power research Institute of State grid Anhui Electric power Co. Ltd.Hefei 230000China Hefei University of Technology Hefei 230009China IEEE CSEE

Real-time fault detection is important for operation of smart *** has become a trend of future development to design an anomaly detection system based on deep learning by using the powerful computing power of the ***,delay of Internet transmission is large,which may make the delay time of detection and transmission go beyond the ***,the edge-based scheme may not be able to undertake all data detection tasks due to limited computing resources of edge ***,we propose a cloud-edge collaborative smart grid fault detection system,next to which edge devices are placed,and equipped with a lightweight neural network with different precision for fault *** addition,a sub-optimal and realtime communication and computing resource allocation method is proposed based on deep reinforcement *** method greatly speeds up solution time,which can meet the requirements of data transmission delay,maximize the system throughput,and improve communication *** results show the scheme is superior in transmission delay and improves real-time performance of the smart grid detection system.

关键词： Cloud-edge collaboration communication delay deep reinforcement learning fault detection smart grid

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