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Optical Fibre communication Feature Analysis and Small Sample Fault Diagnosis Based on VMD-FE and Fuzzy Clustering

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Energy Engineering 2024年第1期121卷 203-219页

作者： Xiangqun Li Jiawen Liang Jinyu Zhu Shengping Shi Fangyu Ding Jianpeng Sun Bo Liu Gannan power Supply company of State Grid Gansu Electric power Supply company Hezuo747000China Digital communication Department Gannan Power Supply Company of State Grid Gansu Electric Power Supply CompanyHezuo747000China

To solve the problems of a few optical fibre line fault samples and the inefficiency of manual communication optical fibre fault diagnosis,this paper proposes a communication optical fibre fault diagnosis model based on variational modal decomposition(VMD),fuzzy entropy(FE)and fuzzy clustering(FC).Firstly,based on the OTDR curve data collected in the field,VMD is used to extract the different modal components(IMF)of the original signal and calculate the fuzzy entropy(FE)values of different components to characterize the subtle differences between *** fuzzy entropy of each curve is used as the feature vector,which in turn constructs the communication optical fibre feature vector matrix,and the fuzzy clustering algorithm is used to achieve fault diagnosis of faulty optical *** VMD-FE combination can extract subtle differences in features,and the fuzzy clustering algorithm does not require sample *** experimental results show that the model in this paper has high accuracy and is relevant to the maintenance of communication optical fibre when compared with existing feature extraction models and traditional machine learning models.

关键词： Optical fibre fault diagnosis OTDR curve variational mode decomposition fuzzy entropy fuzzy clustering

Distributed Graph Database Load Balancing Method Based on Deep Reinforcement Learning

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Computers, Materials & Continua 2024年第6期79卷 5105-5124页

作者： Shuming Sha Naiwang Guo Wang Luo Yong Zhang Nanjing NARI Information&communication technology Co. Ltd.Nanjing210032China State Grid Electric power Research Institute Nanjing211106China State Grid Shanghai Municipal Eleciric power company Shanghai200122China

This paper focuses on the scheduling problem of workflow tasks that exhibit *** indepen-dent batch tasks,workflows typically consist of multiple subtasks with intrinsic correlations and *** necessitates the distribution of various computational tasks to appropriate computing node resources in accor-dance with task dependencies to ensure the smooth completion of the entire *** scheduling must consider an array of factors,including task dependencies,availability of computational resources,and the schedulability of ***,this paper delves into the distributed graph database workflow task scheduling problem and proposes a workflow scheduling methodology based on deep reinforcement learning(DRL).The method optimizes the maximum completion time(makespan)and response time of workflow tasks,aiming to enhance the responsiveness of workflow tasks while ensuring the minimization of the *** experimental results indicate that the Q-learning Deep Reinforcement Learning(Q-DRL)algorithm markedly diminishes the makespan and refines the average response time within distributed graph database *** quantifying makespan,Q-DRL achieves mean reductions of 12.4%and 11.9%over established First-fit and Random scheduling strategies,***,Q-DRL surpasses the performance of both DRL-Cloud and Improved Deep Q-learning Network(IDQN)algorithms,with improvements standing at 4.4%and 2.6%,*** reference to average response time,the Q-DRL approach exhibits a significantly enhanced performance in the scheduling of workflow tasks,decreasing the average by 2.27%and 4.71%when compared to IDQN and DRL-Cloud,*** Q-DRL algorithm also demonstrates a notable increase in the efficiency of system resource utilization,reducing the average idle rate by 5.02%and 9.30%in comparison to IDQN and DRL-Cloud,*** findings support the assertion that Q-DRL not only upholds a lower average

关键词： Reinforcement learning workflow task scheduling load balancing

Cyber-physical Collaborative Restoration Strategy for power Transmission System Considering Maintenance Scheduling

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CSEE Journal of power and Energy Systems 2024年第3期10卷 1331-1341页

作者： Baozhong Ti Chuanyun Zhang Jingfei Liu Zhaoyuan Wu Ziyang Huang North China branch of State Grid Corporation of China Beijing 100053China State Grid Beijing Electric power company Beijing 100031China State Key Laboratory of Alternate Electrical power System with Renewable Energy Sources School of Electrical and Electronic EngineeringNorth China Electric Power UniversityBeijing 102206China IEEE CSEE

In order to improve the ability of power transmission system to cope with compound faults on the communication side and power side,a cyber-physical collaborative restoration strategy is ***,according to the information system’s role in fault diagnosis,remote control of equipment maintenance and automatic output adjustment of generator restoration,a cyber-physical coupling model is *** this basis,a collaborative restoration model of power transmission system is established by studying interactions among maintenance schedule paths,information system operation,and power system *** on power flow linearization and the large M-ε method,the above model is transformed into a mixed integer linear programming model,whose computational burden is reduced further by the clustering *** to the parameters of IEEE39 New England system,the geographic wiring diagram of the cyber-physical system is *** results show the proposed restoration strategy can consider the support function of the information system and space-time coordination of equipment maintenance at both sides comprehensively to speed up load recovery progress.

关键词： Clustering method collaborative restoration cyber-physical power system maintenance scheduling power transmission system restoration

Consumer-branch Connectivity Identification of Low Voltage Distribution Networks Based on Data-driven Approach

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Protection and Control of Modern power Systems 2024年第4期9卷 69-82页

作者： Yongjun Zhang Yingqi Yi Wenyang Deng Siliang Liu Lai Zhou Kaidong Lin Yongzhi Cai the School of Electric power Engineering and Guangdong Key Laboratory of Clean Energy technology South China Uni-versity of TechnologyGuangzhou 510641China the School of Elec-tric power Engineering South China University of TechnologyGuangzhou 510641China the Guangzhou Panyu vocational and technical college Guangzhou 511483China the Metrology Center Guangdong power company Grid Qingyuan 511500China

Accurate topological information is crucial in supporting the coordinated operational requirements of source-load-storage in low-voltage distribution *** coverage of smart meters provides a database for low-voltage topology identification(LVTI).However,because of electricity theft,power line commu-nication crosstalk,and interruption of communication,the measurement data may be *** can seriously affect the performance of LVTI ***,this paper defines hidden errors and proposes an LVTI method based on layer-by-layer stepwise *** the first step,a multi-linear regression model is developed for consumer-branch connectivity identification based on the energy conservation *** the second step,a significance factor based on the t-test is proposed to modify the identification results by considering the hidden *** the third step,the regression model and significance threshold parameters are iteratively updated layer by layer to improve the recall rate of the final identification ***,simulations of a test system with 63 users are carried out,and the practical application results show that the proposed method can guarantee over 90%precision under the influence of hidden errors.

关键词： Data driven hidden error linear re-gression low voltage distribution network topology identification

Deep Learning-Based Secure Transmission Strategy with Sensor-Transmission-Computing Linkage for power Internet of Things

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Computers, Materials & Continua 2024年第3期78卷 3267-3282页

作者： Bin Li Linghui Kong Xiangyi Zhang Bochuo Kou Hui Yu Bowen Liu State Grid Beijing Urban District power Supply company Beijing100034China

The automatic collection of power grid situation information, along with real-time multimedia interaction between the front and back ends during the accident handling process, has generated a massive amount of power grid data. While wireless communication offers a convenient channel for grid terminal access and data transmission, it is important to note that the bandwidth of wireless communication is limited. Additionally, the broadcast nature of wireless transmission raises concerns about the potential for unauthorized eavesdropping during data transmission. To address these challenges and achieve reliable, secure, and real-time transmission of power grid data, an intelligent security transmission strategy with sensor-transmission-computing linkage is proposed in this paper. The primary objective of this strategy is to maximize the confidentiality capacity of the system. To tackle this, an optimization problem is formulated, taking into consideration interruption probability and interception probability as constraints. To efficiently solve this optimization problem, a low-complexity algorithm rooted in deep reinforcement learning is designed, which aims to derive a suboptimal solution for the problem at hand. Ultimately, through simulation results, the validity of the proposed strategy in guaranteed communication security, stability, and timeliness is substantiated. The results confirm that the proposed intelligent security transmission strategy significantly contributes to the safeguarding of communication integrity, system stability, and timely data delivery.

关键词： Secure transmission deep learning power Internet of Things sensor-transmission-computing

Multi-Time-Scale Resource Allocation Based on Long-Term Contracts and Real-Time Rental Business Models for Shared Energy Storage Systems

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Journal of Modern power Systems and Clean Energy 2024年第2期12卷 454-465页

作者： Yuxuan Zhuang Zhiyi Li Qipeng Tan Yongqi Li Minhui Wan College of Electrical Engineering Zhejiang UniversityHangzhouChina China Southern power Grid power Generation company Energy Storage Research Institute GuangzhouChina IEEE

The push for renewable energy emphasizes the need for energy storage systems(ESSs)to mitigate the unpre-dictability and variability of these sources,yet challenges such as high investment costs,sporadic utilization,and demand mismatch hinder their broader *** response,shared energy storage systems(SESSs)offer a more cohesive and efficient use of ESS,providing more accessible and cost-effective energy storage solutions to overcome these *** enhance the profitability of SESSs,this paper designs a multi-time-scale resource allocation strategy based on long-term contracts and real-time rental business *** initially construct a life cycle cost model for SESS and introduce a method to estimate the degradation costs of multiple battery groups by cycling numbers and depth of discharge within the ***,we design various long-term contracts from both capacity and energy perspectives,establishing associated models and real-time rental ***,multi-time-scale resource allocation based on the decomposition of user demand is *** analysis validates that the business model based on long-term contracts excels over models operating solely in the real-time market in economic viability and user satisfaction,effectively reducing battery degradation,and leveraging the aggregation effect for SESS can generate an additional increase of 10.7%in net revenue.

关键词： Capacity allocation long-term contracts shared energy storage system stochastic programming

Experimental study on the effect of H_(2)O and O_(2) on the degradation of SF_(6) by pulsed dielectric barrier discharge

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Plasma Science and technology 2024年第2期26卷 125-131页

作者：李亚龙万昆王宇非张晓星杨照迪傅明利卓然王邸博 Hubei Key Laboratory for High-efficiency utilization of Solar Energy and Operation Control of Energy Storage System Hubei University of TechnologyWuhan 430068People's Republic of China State Grid HuBei Direct Current company Yichang 443002People's Republic of China CSG Electric power Research Institute CO.Ltd Guangzhou 510080People's Republic of China

SF_(6) has excellent insulation performance and arc extinguishing ability,and is widely used in the power ***,its global warming potential is about 23,500 times that of C0_(2),it can exist stably in the atmosphere,it is not easily degradable and is of great potential harm to the *** on pulsed dielectric barrier discharge plasma technology,the effects of H_(2)O and 0_(2) on the degradation of SF_(6) were *** have shown that H_(2)O can effectively promote the decomposition of SF_(6) and improve its degradation rate and energy efficiency of *** the action of a pulse input voltage and input frequency of 15 kV and 15 kHz,respectively,when H_(2)O is added alone the effect of 1% H_(2)O is the best,and the rate and energy efficiency of degradation of SF_(6) reach their maximum values,which are 91.9% and 8.25 g kWh^(-1),*** synergistic effect of H_(2)O and O_(2) on the degradation of SF_(6) was similar to that of H_(2)*** the concentration of H_(2)O and O_(2) was 1%,the system obtained the best rate and energy efficiency of degradation,namely 89.7% and 8.05 g kWh~(-1),*** the same time,different external gases exhibit different capabilities to regulate decomposition *** addition of H_(2)O can effectively improve the selectivity of S0_(2).Under the synergistic effect of H_(2)O and O_(2),with increase in O_(2) concentration the degradation products gradually transformed into SO_(2)F_(2).From the perspective of harmless treatment of the degradation products of SF_(6),the addition of O_(2) during the SF_(6) degradation process should be avoided.

关键词： SF_(6) pulsed dielectric barrier discharge degradation discharge gas

Effects of Diesel Concentration on the Thermal Conductivity,Specific Heat Capacity and Thermal Diffusivity of Diesel-Contaminated Soil

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Journal of Thermal Science 2024年第2期33卷 696-709页

作者： WU Yuhao WU Yuefei LUO Gubai ZHANG Teng WANG Qing FAN Liwu SONG Xin YU Zitao Key Laboratory of Clean Energy and Carbon Neutrality of Zhejiang Province Zhejiang UniversityHangzhou310027China State Key Laboratory of Clean Energy utilization Zhejiang UniversityHangzhou310027China Institute of Thermal Science and power Systems School of Energy EngineeringZhejiang UniversityHangzhou310027China Center Environmental Protection technology company Limited Beijing100176China Institute of Soil Science Chinese Academy of SciencesNanjing210008China

High energy consumption is a serious issue associated with in situ thermal desorption(TD)remediation of sites contaminated by petroleum hydrocarbons(PHs).The knowledge on the thermophysical properties of contaminated soil can help predict accurately the transient temperature distribution in a remediation site,for the purpose of energy ***,such data are rarely reported for PH-contaminated *** this study,by taking diesel as a representative example for PHs,soil samples with constant dry bulk density but different diesel mass concentrations ranging from 0% to 20% were prepared,and the variations of their thermal conductivity,specific heat capacity and thermal diffusivity were measured and analyzed over a wide temperature range between 0℃ and 120℃.It was found that the effect of diesel concentration on the thermal conductivity of soil is negligible when it is below 1%.When diesel concentration is below 10%,the thermal conductivity of soil increases with raising the ***,when diesel concentration becomes above 10%,the change of the thermal conductivity of soil with temperature exhibits the opposite *** is mainly due to the competition between soil minerals and diesel,because the thermal conductivity of minerals increases with temperature,whereas the thermal conductivity of diesel decreases with *** analysis results showed that,compared with temperature,the diesel concentration has more significant effects on soil thermal *** of the diesel concentration,with the increase of temperature,the specific heat capacity of soil increases,while the thermal diffusivity of soil *** addition,the results of a control experiment exhibited that the relative differences of the thermal conductivity of the soil samples containing the same concentration of both diesel and a pure alkane are all below 10%,indicating that the results obtained with diesel in this study can be extended to the family of PHs.A theo

关键词： contaminated soil diesel concentration thermal conductivity specific heat capacity thermal diffusivity thermal desorption fractal model

Energy Economic Dispatch for Photovoltaic-Storage via Distributed Event-Triggered Surplus Algorithm

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Energy Engineering 2024年第9期121卷 2621-2637页

作者： Kaicheng Liu Chen Liang Naiyue Wu Xiaoyang Dong Hui Yu China Electric power Research Institute Beijing100192China Electric power Research Institute of State Grid Gansu Electric power company Lanzhou730000China State Key Laboratory of power Grid Safety Beijing100084China

This paper presents a novel approach to economic dispatch in smart grids equipped with diverse energy *** method integrates features including photovoltaic(PV)systems,energy storage coupling,varied energy roles,and energy supply and demand *** systemmodel is developed by considering energy devices as versatile units capable of fulfilling various functionalities and playing multiple roles *** strike a balance between optimality and feasibility,renewable energy resources are modeled with considerations for forecasting errors,Gaussian distribution,and penalty ***,this study introduces a distributed event-triggered surplus algorithm designed to address the economic dispatch problem by minimizing production *** in surplus theory and finite time projection,the algorithm effectively rectifies network imbalances caused by directed graphs and addresses local inequality *** algorithm greatly reduces the communication burden through event triggering ***,both theoretical proofs and numerical simulations verify the convergence and event-triggered nature of the algorithm.

关键词： Fully distributed algorithm economic dispatch directed graph renewable energy resource