A distributed information network with complex network structure always has a challenge of locating fault root causes.In this paper,we propose a novel root cause analysis(RCA)method by random walk on the weighted faul...A distributed information network with complex network structure always has a challenge of locating fault root causes.In this paper,we propose a novel root cause analysis(RCA)method by random walk on the weighted fault propagation graph.Different from other RCA methods,it mines effective features information related to root causes from offline alarms.Combined with the information,online alarms and graph relationship of network structure are used to construct a weighted graph.Thus,this approach does not require operational experience and can be widely applied in different distributed networks.The proposed method can be used in multiple fault location cases.The experiment results show the proposed approach achieves much better performance with 6%higher precision at least for root fault location,compared with three baseline methods.Besides,we explain how the optimal parameter’s value in the random walk algorithm influences RCA results.展开更多
Gyro's fault diagnosis plays a critical role in inertia navigation systems for higher reliability and precision. A new fault diagnosis strategy based on the statistical parameter analysis (SPA) and support vector ...Gyro's fault diagnosis plays a critical role in inertia navigation systems for higher reliability and precision. A new fault diagnosis strategy based on the statistical parameter analysis (SPA) and support vector machine (SVM) classification model was proposed for dynamically tuned gyroscopes (DTG). The SPA, a kind of time domain analysis approach, was introduced to compute a set of statistical parameters of vibration signal as the state features of DTG, with which the SVM model, a novel learning machine based on statistical learning theory (SLT), was applied and constructed to train and identify the working state of DTG. The experimental results verify that the proposed diagnostic strategy can simply and effectively extract the state features of DTG, and it outperforms the radial-basis function (RBF) neural network based diagnostic method and can more reliably and accurately diagnose the working state of DTG.展开更多
In this paper,a fault location method for the petal-shaped distribution network(PSDN)with inverter-interfaced distributed generators(IIDGs)is proposed to shorten the time of manual inspection.In order to calculate the...In this paper,a fault location method for the petal-shaped distribution network(PSDN)with inverter-interfaced distributed generators(IIDGs)is proposed to shorten the time of manual inspection.In order to calculate the fault position,the closed-loop structure of the PSDN is skillfully exploited,and the common control strategies of IIDGs are considered.For asymmetrical faults,a fault line identification formula based on the negative-sequence current phase differences is presented,and a fault location formula only utilizing the negative-sequence current amplitudes is derived to calculated the fault position.For symmetrical faults,the positive-sequence current at both ends of lines and the current output from IIDGs are used to identify the fault line,and the positive-sequence current on multiple lines are used to pinpoint the fault position.In this method,corresponding current phasors are separated into amplitudes and phases to satisfy the limitation of communication level.The simulation results show that the error is generally less than 1%,and the accuracy of the proposed method is not affected by the fault type,fault position,fault resistance,load current,and the IIDG penetration.展开更多
Load shedding is a major problem in Central Africa, with negative consequences for both society and the economy. However, load profile analysis can help to alleviate this problem by providing valuable information abou...Load shedding is a major problem in Central Africa, with negative consequences for both society and the economy. However, load profile analysis can help to alleviate this problem by providing valuable information about consumer demand. This information can be used by power utilities to forecast and reduce power cuts effectively. In this study, the direct method was used to create load profiles for residential feeders in Kinshasa. The results showed that load shedding on weekends results in significant financial losses and changes in people’s behavior. In November 2022 alone, load shedding was responsible for $ 23,4 08,984 and $ 2 80,9 07,808 for all year in losses. The study also found that the SAIDI index for the southern direction of the Kinshasa distribution network was 122.49 hours per feeder, on average. This means that each feeder experienced an average of 5 days of load shedding in November 2022. The SAIFI index was 20 interruptions per feeder, on average, and the CAIDI index was 6 hours, on average, before power was restored. This study also proposes ten strategies for the reduction of load shedding in the Kinshasa and central Africa power distribution network and for the improvement of its reliability, namely: Improved load forecasting, Improvement of the grid infrastructure, Scheduling of load shedding, Demand management programs, Energy efficiency initiatives, Distributed Generation, Automation and Monitoring of the Grid, Education and engagement of the consumer, Policy and regulatory assistance, and Updated load profile analysis.展开更多
Distribution networks denote important public infrastructure necessary for people’s livelihoods.However,extreme natural disasters,such as earthquakes,typhoons,and mudslides,severely threaten the safe and stable opera...Distribution networks denote important public infrastructure necessary for people’s livelihoods.However,extreme natural disasters,such as earthquakes,typhoons,and mudslides,severely threaten the safe and stable operation of distribution networks and power supplies needed for daily life.Therefore,considering the requirements for distribution network disaster prevention and mitigation,there is an urgent need for in-depth research on risk assessment methods of distribution networks under extreme natural disaster conditions.This paper accessesmultisource data,presents the data quality improvement methods of distribution networks,and conducts data-driven active fault diagnosis and disaster damage analysis and evaluation using data-driven theory.Furthermore,the paper realizes real-time,accurate access to distribution network disaster information.The proposed approach performs an accurate and rapid assessment of cross-sectional risk through case study.The minimal average annual outage time can be reduced to 3 h/a in the ring network through case study.The approach proposed in this paper can provide technical support to the further improvement of the ability of distribution networks to cope with extreme natural disasters.展开更多
The tight wavelet neural network was constituted by taking the nonlinear Morlet wavelet radices as the excitation function. The idiographic algorithm was presented. It combined the advantages of wavelet analysis and n...The tight wavelet neural network was constituted by taking the nonlinear Morlet wavelet radices as the excitation function. The idiographic algorithm was presented. It combined the advantages of wavelet analysis and neural networks. The integrated wavelet neural network fault diagnosis system was set up based on both the information fusion technology and actual fault diagnosis, which took the sub-wavelet neural network as primary diagnosis from different sides, then came to the conclusions through decision-making fusion. The realizable policy of the diagnosis system and established principle of the sub-wavelet neural networks were given. It can be deduced from the examples that it takes full advantage of diversified characteristic information, and improves the diagnosis rate.展开更多
Lifelines, such as pipeline, transportation, communication, electric transmission and medical rescue systems, are complicated networks that always distribute spatially over large geological and geographic units. The q...Lifelines, such as pipeline, transportation, communication, electric transmission and medical rescue systems, are complicated networks that always distribute spatially over large geological and geographic units. The quantification of their reliability under an earthquake occurrence should be highly regarded, because the performance of these systems during a destructive earthquake is vital in order to estimate direct and indirect economic losses from lifeline failures, and is also related to laying out a rescue plan. The research in this paper aims to develop a new earthquake reliability calculation methodology for lifeline systems. The methodology of the network reliability for lifeline systems is based on fault tree analysis （FTA） and geological information system （GIS）. The interactions existing in a lifeline system ale considered herein. The lifeline systems are idealized as equivalent networks, consisting of nodes and links, and are described by network analysis in GIS. Firstly, the node is divided into two types： simple node and complicated node, where the reliability of the complicated node is calculated by FTA and interaction is regarded as one factor to affect performance of the nodes. The reliability of simple node and link is evaluated by code. Then, the reliability of the entilre network is assessed based on GIS and FTA. Lastly, an illustration is given to show the methodology.展开更多
The most important elements of “intellectual networks” (Smart Grid) are the systems of monitoring the parameters of electrical equipment. Information-measuring systems (IMS), which described in this paper, were prop...The most important elements of “intellectual networks” (Smart Grid) are the systems of monitoring the parameters of electrical equipment. Information-measuring systems (IMS), which described in this paper, were proposed to use together with rapid digital protection against short-circuit regimes in transformer windings. This paper presents an application’s experience of LVI-testing, some results of the use of Frequency Response Analysis (FRA) to check the condition of transformer windings and infra-red control results of electrical equipment. The LVI method and short-circuit inductive reactance measurements are sensitive for detecting such faults as radial, axial winding deformations, a twisting of low-voltage or regulating winding, a losing of winding’s pressing and others.展开更多
由于柔性多状态开关(soft normal open point,SNOP)复杂的控制策略及其弱馈特性,传统配电网故障定位方法难以适用于柔性互联配电网(flexible distribution network,FDN)。因此,文中提出一种利用电流正序分量波形相似性进行FDN故障区段...由于柔性多状态开关(soft normal open point,SNOP)复杂的控制策略及其弱馈特性,传统配电网故障定位方法难以适用于柔性互联配电网(flexible distribution network,FDN)。因此,文中提出一种利用电流正序分量波形相似性进行FDN故障区段定位的方法。首先,针对SNOP的典型控制策略,分析FDN的短路故障特征。其次,计算配电网中不同故障位置电流正序分量的Tanimoto系数,通过对比不同位置的电流正序分量波形相似性,构建FDN短路故障定位判据,并通过Teager能量算子(Teager energy operation,TEO)实现故障时刻的精确定位,利用智能配电终端(smart terminal unit,STU)传递信息。最后,通过建模仿真对所提方法进行分析验证,结果表明该方法能够对故障区段进行准确定位,不受故障位置、故障类型、过渡电阻、采样频率及通信延时等因素的影响,验证了该方法的可行性与有效性。展开更多
The increasing penetration of inverter-based distributed generations(DGs)significantly affects the fault characteristics of distribution networks.Fault analysis is a keystone for suitable protection scheme design.This...The increasing penetration of inverter-based distributed generations(DGs)significantly affects the fault characteristics of distribution networks.Fault analysis is a keystone for suitable protection scheme design.This paper presents the modelling methodology for distribution networks with inverter-based DGs and performs fault simulation based on the model.Firstly,a single inverter-based DG model based on the cascaded control structure is developed.Secondly,a simulation model of distribution network with two inverter-based DGs is established.Then,different fault simulations are performed based on the Real Time Digital Simulator(RTDS).Theoretical analyses are conducted to justify the simulation results,including the equivalent circuit of distribution networks with inverter-based DGs and the solution method for loop currents.展开更多
基金supported by ZTE Industry-University-Institute Cooperation Funds under Grant No.HC-CN-20201120009。
文摘A distributed information network with complex network structure always has a challenge of locating fault root causes.In this paper,we propose a novel root cause analysis(RCA)method by random walk on the weighted fault propagation graph.Different from other RCA methods,it mines effective features information related to root causes from offline alarms.Combined with the information,online alarms and graph relationship of network structure are used to construct a weighted graph.Thus,this approach does not require operational experience and can be widely applied in different distributed networks.The proposed method can be used in multiple fault location cases.The experiment results show the proposed approach achieves much better performance with 6%higher precision at least for root fault location,compared with three baseline methods.Besides,we explain how the optimal parameter’s value in the random walk algorithm influences RCA results.
文摘Gyro's fault diagnosis plays a critical role in inertia navigation systems for higher reliability and precision. A new fault diagnosis strategy based on the statistical parameter analysis (SPA) and support vector machine (SVM) classification model was proposed for dynamically tuned gyroscopes (DTG). The SPA, a kind of time domain analysis approach, was introduced to compute a set of statistical parameters of vibration signal as the state features of DTG, with which the SVM model, a novel learning machine based on statistical learning theory (SLT), was applied and constructed to train and identify the working state of DTG. The experimental results verify that the proposed diagnostic strategy can simply and effectively extract the state features of DTG, and it outperforms the radial-basis function (RBF) neural network based diagnostic method and can more reliably and accurately diagnose the working state of DTG.
基金supported by State Grid Science and Technology Project:Research on Key Protection Technologies for New-type Urban Distribution Network with Controllable Sources and Loads(5100-201913019A-0-0-00).
文摘In this paper,a fault location method for the petal-shaped distribution network(PSDN)with inverter-interfaced distributed generators(IIDGs)is proposed to shorten the time of manual inspection.In order to calculate the fault position,the closed-loop structure of the PSDN is skillfully exploited,and the common control strategies of IIDGs are considered.For asymmetrical faults,a fault line identification formula based on the negative-sequence current phase differences is presented,and a fault location formula only utilizing the negative-sequence current amplitudes is derived to calculated the fault position.For symmetrical faults,the positive-sequence current at both ends of lines and the current output from IIDGs are used to identify the fault line,and the positive-sequence current on multiple lines are used to pinpoint the fault position.In this method,corresponding current phasors are separated into amplitudes and phases to satisfy the limitation of communication level.The simulation results show that the error is generally less than 1%,and the accuracy of the proposed method is not affected by the fault type,fault position,fault resistance,load current,and the IIDG penetration.
文摘Load shedding is a major problem in Central Africa, with negative consequences for both society and the economy. However, load profile analysis can help to alleviate this problem by providing valuable information about consumer demand. This information can be used by power utilities to forecast and reduce power cuts effectively. In this study, the direct method was used to create load profiles for residential feeders in Kinshasa. The results showed that load shedding on weekends results in significant financial losses and changes in people’s behavior. In November 2022 alone, load shedding was responsible for $ 23,4 08,984 and $ 2 80,9 07,808 for all year in losses. The study also found that the SAIDI index for the southern direction of the Kinshasa distribution network was 122.49 hours per feeder, on average. This means that each feeder experienced an average of 5 days of load shedding in November 2022. The SAIFI index was 20 interruptions per feeder, on average, and the CAIDI index was 6 hours, on average, before power was restored. This study also proposes ten strategies for the reduction of load shedding in the Kinshasa and central Africa power distribution network and for the improvement of its reliability, namely: Improved load forecasting, Improvement of the grid infrastructure, Scheduling of load shedding, Demand management programs, Energy efficiency initiatives, Distributed Generation, Automation and Monitoring of the Grid, Education and engagement of the consumer, Policy and regulatory assistance, and Updated load profile analysis.
文摘Distribution networks denote important public infrastructure necessary for people’s livelihoods.However,extreme natural disasters,such as earthquakes,typhoons,and mudslides,severely threaten the safe and stable operation of distribution networks and power supplies needed for daily life.Therefore,considering the requirements for distribution network disaster prevention and mitigation,there is an urgent need for in-depth research on risk assessment methods of distribution networks under extreme natural disaster conditions.This paper accessesmultisource data,presents the data quality improvement methods of distribution networks,and conducts data-driven active fault diagnosis and disaster damage analysis and evaluation using data-driven theory.Furthermore,the paper realizes real-time,accurate access to distribution network disaster information.The proposed approach performs an accurate and rapid assessment of cross-sectional risk through case study.The minimal average annual outage time can be reduced to 3 h/a in the ring network through case study.The approach proposed in this paper can provide technical support to the further improvement of the ability of distribution networks to cope with extreme natural disasters.
文摘The tight wavelet neural network was constituted by taking the nonlinear Morlet wavelet radices as the excitation function. The idiographic algorithm was presented. It combined the advantages of wavelet analysis and neural networks. The integrated wavelet neural network fault diagnosis system was set up based on both the information fusion technology and actual fault diagnosis, which took the sub-wavelet neural network as primary diagnosis from different sides, then came to the conclusions through decision-making fusion. The realizable policy of the diagnosis system and established principle of the sub-wavelet neural networks were given. It can be deduced from the examples that it takes full advantage of diversified characteristic information, and improves the diagnosis rate.
基金Sponsored by the Natural Science Foundation of China (Grant No.50278028) the Scientific Research Foundation of Harbin Institute of Technology(Grant No.HIT200079).
文摘Lifelines, such as pipeline, transportation, communication, electric transmission and medical rescue systems, are complicated networks that always distribute spatially over large geological and geographic units. The quantification of their reliability under an earthquake occurrence should be highly regarded, because the performance of these systems during a destructive earthquake is vital in order to estimate direct and indirect economic losses from lifeline failures, and is also related to laying out a rescue plan. The research in this paper aims to develop a new earthquake reliability calculation methodology for lifeline systems. The methodology of the network reliability for lifeline systems is based on fault tree analysis （FTA） and geological information system （GIS）. The interactions existing in a lifeline system ale considered herein. The lifeline systems are idealized as equivalent networks, consisting of nodes and links, and are described by network analysis in GIS. Firstly, the node is divided into two types： simple node and complicated node, where the reliability of the complicated node is calculated by FTA and interaction is regarded as one factor to affect performance of the nodes. The reliability of simple node and link is evaluated by code. Then, the reliability of the entilre network is assessed based on GIS and FTA. Lastly, an illustration is given to show the methodology.
文摘The most important elements of “intellectual networks” (Smart Grid) are the systems of monitoring the parameters of electrical equipment. Information-measuring systems (IMS), which described in this paper, were proposed to use together with rapid digital protection against short-circuit regimes in transformer windings. This paper presents an application’s experience of LVI-testing, some results of the use of Frequency Response Analysis (FRA) to check the condition of transformer windings and infra-red control results of electrical equipment. The LVI method and short-circuit inductive reactance measurements are sensitive for detecting such faults as radial, axial winding deformations, a twisting of low-voltage or regulating winding, a losing of winding’s pressing and others.
文摘由于柔性多状态开关(soft normal open point,SNOP)复杂的控制策略及其弱馈特性,传统配电网故障定位方法难以适用于柔性互联配电网(flexible distribution network,FDN)。因此,文中提出一种利用电流正序分量波形相似性进行FDN故障区段定位的方法。首先,针对SNOP的典型控制策略,分析FDN的短路故障特征。其次,计算配电网中不同故障位置电流正序分量的Tanimoto系数,通过对比不同位置的电流正序分量波形相似性,构建FDN短路故障定位判据,并通过Teager能量算子(Teager energy operation,TEO)实现故障时刻的精确定位,利用智能配电终端(smart terminal unit,STU)传递信息。最后,通过建模仿真对所提方法进行分析验证,结果表明该方法能够对故障区段进行准确定位,不受故障位置、故障类型、过渡电阻、采样频率及通信延时等因素的影响,验证了该方法的可行性与有效性。
基金Nation Natural Science Foundation of China(51377100)the Key Scientific and Technological Project of State Grid Shandong Power Company(SGSDWF00YJJS1400563).
文摘The increasing penetration of inverter-based distributed generations(DGs)significantly affects the fault characteristics of distribution networks.Fault analysis is a keystone for suitable protection scheme design.This paper presents the modelling methodology for distribution networks with inverter-based DGs and performs fault simulation based on the model.Firstly,a single inverter-based DG model based on the cascaded control structure is developed.Secondly,a simulation model of distribution network with two inverter-based DGs is established.Then,different fault simulations are performed based on the Real Time Digital Simulator(RTDS).Theoretical analyses are conducted to justify the simulation results,including the equivalent circuit of distribution networks with inverter-based DGs and the solution method for loop currents.
