Analysis and Research on 10kV Distribution Network Faults

The 10kV distribution network is an essential component of the power system,and its stable operation is crucial for ensuring reliable power supply.However,various factors can lead to faults in the distribution network.In order to enhance the safety and reliability of power distribution,this paper focuses on the analysis of faults in the 10kV distribution network caused by natural factors,operational factors,human factors,and equipment factors.It elucidates the various hazards resulting from distribution network faults and proposes corresponding preventive measures for different types of faults in the 10kV distribution network.The aim is to mitigate or reduce the impact of distribution network faults,ensuring the safe and stable operation of the distribution system.

A Situational Awareness Method for Initial Insulation Fault of Distribution Network Based on Multi-Feature Index Comprehensive Evaluation

Most ground faults in distribution network are caused by insulation deterioration of power equipment.It is difficult to find the insulation deterioration of the distribution network in time,and the development trend of the initial insulation fault is unknown,which brings difficulties to the distribution inspection.In order to solve the above problems,a situational awareness method of the initial insulation fault of the distribution network based on a multi-feature index comprehensive evaluation is proposed.Firstly,the insulation situation evaluation index is selected by analyzing the insulation fault mechanism of the distribution network,and the relational database of the distribution network is designed based on the data and numerical characteristics of the existing distribution management system.Secondly,considering all kinds of fault factors of the distribution network and the influence of the power supply region,the evaluation method of the initial insulation fault situation of the distribution network is proposed,and the development situation of the distribution network insulation fault is classified according to the evaluation method.Then,principal component analysis was used to reduce the dimension of the training samples and test samples of the distribution network data,and the support vector machine(SVM)was trained.The optimal parameter combination of the SVM model was found by the grid search method,and a multi-class SVM model based on 1-v-1 method was constructed.Finally,the trained multi-class SVM was used to predict 6 kinds of situation level prediction samples.The results of simulation examples show that the average prediction accuracy of 6 situation levels is above 95%,and the perception accuracy of 4 situation levels is above 96%.In addition,the insulation maintenance decision scheme under different situation levels is able to be given when no fault occurs or the insulation fault is in the early stage,which can meet the needs of power distribution and inspection for accurately sensing the insulation fault situation.The correctness and effectiveness of this method are verified.

Optimal Configuration of Fault Location Measurement Points in DC Distribution Networks Based on Improved Particle Swarm Optimization Algorithm

The escalating deployment of distributed power sources and random loads in DC distribution networks hasamplified the potential consequences of faults if left uncontrolled. To expedite the process of achieving an optimalconfiguration of measurement points, this paper presents an optimal configuration scheme for fault locationmeasurement points in DC distribution networks based on an improved particle swarm optimization algorithm.Initially, a measurement point distribution optimization model is formulated, leveraging compressive sensing.The model aims to achieve the minimum number of measurement points while attaining the best compressivesensing reconstruction effect. It incorporates constraints from the compressive sensing algorithm and networkwide viewability. Subsequently, the traditional particle swarm algorithm is enhanced by utilizing the Haltonsequence for population initialization, generating uniformly distributed individuals. This enhancement reducesindividual search blindness and overlap probability, thereby promoting population diversity. Furthermore, anadaptive t-distribution perturbation strategy is introduced during the particle update process to enhance the globalsearch capability and search speed. The established model for the optimal configuration of measurement points issolved, and the results demonstrate the efficacy and practicality of the proposed method. The optimal configurationreduces the number of measurement points, enhances localization accuracy, and improves the convergence speedof the algorithm. These findings validate the effectiveness and utility of the proposed approach.

Distributed Fault Estimation for Nonlinear Systems With Sensor Saturation and Deception Attacks Using Stochastic Communication Protocols

This paper is aimed at the distributed fault estimation issue associated with the potential loss of actuator efficiency for a type of discrete-time nonlinear systems with sensor saturation.For the distributed estimation structure under consideration,an estimation center is not necessary,and the estimator derives its information from itself and neighboring nodes,which fuses the state vector and the measurement vector.In an effort to cut down data conflicts in communication networks,the stochastic communication protocol(SCP)is employed so that the output signals from sensors can be selected.Additionally,a recursive security estimator scheme is created since attackers randomly inject malicious signals into the selected data.On this basis,sufficient conditions for a fault estimator with less conservatism are presented which ensure an upper bound of the estimation error covariance and the mean-square exponential boundedness of the estimating error.Finally,a numerical example is used to show the reliability and effectiveness of the considered distributed estimation algorithm.

Identification of Type of a Fault in Distribution System Using Shallow Neural Network with Distributed Generation

A distributed generation system(DG)has several benefits over a traditional centralized power system.However,the protection area in the case of the distributed generator requires special attention as it encounters stability loss,failure re-closure,fluctuations in voltage,etc.And thereby,it demands immediate attention in identifying the location&type of a fault without delay especially when occurred in a small,distributed generation system,as it would adversely affect the overall system and its operation.In the past,several methods were proposed for classification and localisation of a fault in a distributed generation system.Many of those methods were accurate in identifying location,but the accuracy in identifying the type of fault was not up to the acceptable mark.The proposed work here uses a shallow artificial neural network(sANN)model for identifying a particular type of fault that could happen in a specific distribution network when used in conjunction with distributed generators.Firstly,a distribution network consisting of two similar distributed generators(DG1 and DG2),one grid,and a 100 Km distribution line is modeled.Thereafter,different voltages and currents corresponding to various faults(line to line,line to ground)at different locations are tabulated,resulting in a matrix of 500×18 inputs.Secondly,the sANN is formulated for identifying the types of faults in the system in which the above-obtained data is used to train,validate,and test the neural network.The overall result shows an unprecedented almost zero percent error in identifying the type of the faults.

Line Fault Detection of DC Distribution Networks Using the Artificial Neural Network

ADC distribution network is an effective solution for increasing renewable energy utilization with distinct benefits,such as high efficiency and easy control.However,a sudden increase in the current after the occurrence of faults in the network may adversely affect network stability.This study proposes an artificial neural network(ANN)-based fault detection and protection method for DC distribution networks.The ANN is applied to a classifier for different faults ontheDC line.The backpropagationneuralnetwork is used to predict the line current,and the fault detection threshold is obtained on the basis of the difference between the predicted current and the actual current.The proposed method only uses local signals,with no requirement of a strict communication link.Simulation experiments are conducted for the proposed algorithm on a two-terminal DC distribution network modeled in the PSCAD/EMTDC and developed on the MATLAB platform.The results confirm that the proposed method can accurately detect and classify line faults within a few milliseconds and is not affected by fault locations,fault resistance,noise,and communication delay.

Distribution of large-scale detachment faults on mid-ocean ridges in relation to spreading rates

Large-scale detachment faults on mid-ocean ridges （MORs） provide a window into the deeper earth. They have megamullion on their corrugated surfaces, with exposed lower crustal and upper mantle rocks, rela- tively high residual Bouguer gravity anomaly and P-wave velocity, and are commonly associated with ocean- ic core complex. According to 30 detachment faults identified on MORs, we found that their distances to the axis mostly range from 5 to 50 km, half-spreading rates range from 6.8 to 17 mm/a, and activity time ranges from recent to 3 Ma. Most of the detachment faults are developed on the slow spreading Mid-Atlantic Ridge （MAR） and ultra-slow spreading Southwest Indian Ridge （SWIRl, with the dominant half-spreading rates of 7-13 mm/a, especially 10-13 mm/a. Furthermore, they mostly occur at the inside corner of one segment end and result in an asymmetric seafloor spreading. The detachment faults on MORs are mainly controlled by the tectonism and influenced by the magmatism. Long-lived detachment faults tend to be formed where the ridge magma supply is at a moderate level, although the tectonism is a first-order controlling factor. At the slow spreading ridges, detachment faults tend to occur where local magma supply is relatively low, whilst at the ultra-slow spreading ridges, they normally occur where local magma supply is relatively high. These faults are accompanied by hydrothermal activities, with their relationships being useful in the study of hydrothermal polymetallic sulfides and their origin.

Power-law Distribution of Normal Fault Displacement and Length and Estimation of Extensional Strain due to Normal Faults:A Case Study of the Sierra de San Miguelito, Mexico

The Sierra de San Miguelito is a relatively uplifted area and is constituted by a large amount of silicic volcanic rocks with ages from middle to late Cenozoic. The normal faults of the Sierra de San Miguelito are Domino-style and nearly parallel. The cumulative length and displacement of the faults obey power-law distribution. The fractal dimension of the fault traces is -1.49. Using the multi-line one-dimensional sampling, the calculated exponent of cumulative fault displacements is -0.66. A cumulative curve combining measurements of all four sections yielded a slope of -0.63. The displacement-length plot shows a non-linear relationship and large dispersion of data. The large dispersion in the plot is mainly due to the fault linkage during faulting. An estimation of extensional strain due to the normal faults is ca. 0.1830. The bed extension strain is always less than or equal to the horizontal extension strain. The deformation in the Sierra de San Miguelito occurred near the surface, producing pervasive faults and many faults are too small to appear in maps and sections at common scales. The stretching produced by small faults reach ca. 33% of the total horizontal elongation.

New Principle for Grounding Fault Feeder Detection in MV Distributions with Neutral Ineffectively Earthed

A new principle for grounding fault feeder detection based on negative sequence current variation and energy dissipated in the fault point is presented. It has high precision in both isolated systems and resonance earthed systems, even in full compensated systems. And it can be installed at the local control unit of feeder in distribution automation systems, such as field terminal unit (FTU). This principle is verified by EMTP simulator and experimentation.

The numerical simulation and inversion fitting of radon concentration distribution in homogeneous overburden above active fault zones

Based on the convection and diffusion mechanisms of radon migration, in this paper we deduce the two-dimensional differential equation for radon transportation in the overburden above active fault zones with an unlimited extension along the strike. Making use of the finite difference method, the radon concentration distribution in the overburden above active faults is calculated and modeled. The active fault zone parameters, such as the depth and the width of the fault zone, and the value of radon concentration, can be inverted from the measured radon concentration curve. These realize quantitative interpretation for radon concentration anomalies. The inversion results are in good agreement with the actual fault zone parameters.

Earthquake probabilities and magnitude distribution (M ≥ 6.7) along the Haiyuan fault, northwestern China

In recent years, some researchers have studied the paleoearthquake along the Haiyuan fault and revealed a lot of paleoearthquake events. All available information allows more reliable analysis of earthquake recurrence interval and earthquake rupture patterns along the Haiyuan fault. Based on this paleoseismological information, the recur- rence probability and magnitude distribution for M≥6.7 earthquakes in future 100 years along the Haiyuan fault can be obtained through weighted computation by using Poisson and Brownian passage time models and consid- ering different rupture patterns. The result shows that the recurrence probability of MS≥6.7 earthquakes is about 0.035 in future 100 years along the Haiyuan fault.

Gulong shale oil enrichment mechanism and orderly distribution of conventional–unconventional oils in the Cretaceous Qingshankou Formation,Songliao Basin,NE China

Through the study of organic matter enrichment,hydrocarbon generation and accumulation process of black shale of the Cretaceous Qingshankou Formation in the Songliao Basin,the enrichment mechanism of Gulong shale oil and the distribution of conventional–unconventional oil are revealed.The Songliao Basin is a huge interior lake basin formed in the Early Cretaceous under the control of the subduction and retreat of the western Pacific plate and the massive horizontal displacement of the Tanlu Fault Zone in Northeast China.During the deposition of the Qingshankou Formation,strong terrestrial hydrological cycle led to the lake level rise of the ancient Songliao Basin and the input of a large amount of nutrients,resulting in planktonic bacteria and algae flourish.Intermittent seawater intrusion events promoted the formation of salinization stratification and anoxic environment in the lake,which were beneficial to the enrichment of organic matters.Biomarkers analysis confirms that the biogenic organic matter of planktonic bacteria and algae modified by microorganisms plays an important role in the formation of high-quality source rocks with high oil generation capability.There are four favorable conditions for the enrichment of light shale oil in the Qingshankou Formation of the Gulong Sag,Songliao Basin:the moderate organic matter abundance and high oil potential provide sufficient material basis for oil enrichment;high degree of thermal evolution makes shale oil have high GOR and good mobility;low hydrocarbon expulsion efficiency leads to a high content of retained hydrocarbons in the source rock;and the confinement effect of intra-layer cement in the high maturity stage induces the efficient accumulation of light shale oil.The restoration of hydrocarbon accumulation process suggests that liquid hydrocarbons generated in the early(low–medium maturity)stage of the Qingshankou Formation source rocks accumulated in placanticline and slope after long-distance secondary migration,forming high-quality conventional and tight oil reservoirs.Light oil generated in the late(medium–high maturity)stage accumulated in situ,forming about 15 billion tons of Gulong shale oil resources,which finally enabled the orderly distribution of conventional–unconventional oils that are contiguous horizontally and superposed vertically within the basin,showing a complete pattern of“whole petroleum system”with conventional oil,tight oil and shale oil in sequence.

NEW TECHNOLOGY FOR FAULT DIAGNOSIS BASED ON WAVELET DENOISING AND MODIFIED EXPONENTIAL TIME-FREQUENCY DISTRIBUTION

Fast wavelet multi-resolution analysis (wavelet MRA) provides a effective tool for analyzing and canceling disturbing components in original signal. Because of its exponential frequency axis, this method isn't suitable for extracting harmonic components. The modified exponential time-frequency distribution ( MED) overcomes the problems of Wigner distribution( WD) ,can suppress cross-terms and cancel noise further more. MED provides high resolution in both time and frequency domains, so it can make out weak period impulse components fmm signal with mighty harmonic components. According to the 'time' behavior, together with 'frequency' behavior in one figure,the essential structure of a signal is revealed clearly. According to the analysis of algorithm and fault diagnosis example, the joint of wavelet MRA and MED is a powerful tool for fault diagnosis.

Earthquake probabilities and magnitude distribution (M≥6.7) along the Haiyuan fault, northwestern China

In recent years, some researchers have studied the paleoearthquake along the Haiyuan fault and revealed a lot of paleoearthquake events. All available information allows more reliable analysis of earthquake recurrence interval and earthquake rupture patterns along the Haiyuan fault. Based on this paleoseismological information, the recur- rence probability and magnitude distribution for M≥6.7 earthquakes in future 100 years along the Haiyuan fault can be obtained through weighted computation by using Poisson and Brownian passage time models and consid- ering different rupture patterns. The result shows that the recurrence probability of MS≥6.7 earthquakes is about 0.035 in future 100 years along the Haiyuan fault.

Characterization and spatial analysis of coseismic landslides triggered by the Luding Ms 6.8 earthquake in the Xianshuihe fault zone, Southwest China

On September 5, 2022, a magnitude Ms 6.8 earthquake occurred along the Moxi fault in the southern part of the Xianshuihe fault zone located in the southeastern margin of the Tibetan Plateau,resulting in severe damage and substantial economic loss. In this study, we established a coseismic landslide database triggered by Luding Ms 6.8 earthquake, which includes 4794 landslides with a total area of 46.79 km^(2). The coseismic landslides primarily consisted of medium and small-sized landslides, characterized by shallow surface sliding. Some exhibited characteristics of high-position initiation resulted in the obstruction or partial obstruction of rivers, leading to the formation of dammed lakes. Our research found that the coseismic landslides were predominantly observed on slopes ranging from 30° to 50°, occurring at between 1000 m and 2500 m, with slope aspects varying from 90° to 180°. Landslides were also highly developed in granitic bodies that had experienced structural fracturing and strong-tomoderate weathering. Coseismic landslides concentrated within a 6 km range on both sides of the Xianshuihe and Daduhe fault zones. The area and number of coseismic landslides exhibited a negative correlation with the distance to fault lines, road networks, and river systems, as they were influenced by fault activity, road excavation, and river erosion. The coseismic landslides were mainly distributed in the southeastern region of the epicenter, exhibiting relatively concentrated patterns within the IX-degree zones such as Moxi Town, Wandong River basin, Detuo Town to Wanggangping Township. Our research findings provide important data on the coseismic landslides triggered by the Luding Ms 6.8 earthquake and reveal the spatial distribution patterns of these landslides. These findings can serve as important references for risk mitigation, reconstruction planning, and regional earthquake disaster research in the earthquake-affected area.

Distribution patterns of rock mass displacement in deeply buried areas induced by active fault creep slip at engineering scale

Active fault creep slip induces deformation of rock mass buried deeply in fault zones that significantly affect the operational safety of long linear projects passing through it.Displacement distribution patterns of rock masses in active fault zones which have been investigated previously are the key design basis for such projects.Therefore,a discrete element numerical model with different fault types,slip time,dip angles,and complex geological features was established,and then the creep slip for normal,reverse,and strike-slip faults were simulated to analyze the displacement distribution in the fault rock mass.A disk rotation test system and the corresponding laboratory test method were developed for simulating rock mass displacement induced by creep slippage of faults.A series of rotation tests for softand hard-layered specimens under combined compression and torsional stress were conducted to verify the numerical results and analyze the factors influencing the displacement distribution.An S-shaped displacement distribution independent of fault dip angle was identified corresponding to reverse,normal,and strike-slip faults.The results indicated that the higher the degree of horizontal extrusion,the softer the rock mass at the fault core,and the higher the degree of displacement concentration in the fault core;about 70%of the creep slip displacement occurs within this zone under 100 years of creep slippage.

Landslide distribution and sliding mode control along the Anninghe fault zone at the eastern edge of the Tibetan Plateau

Tibetan Plateau is known as the roof of the world.Due to the continuous uplift of the Tibetan Plateau,many active fault zones are present.These active fault zones such as the Anninghe fault zone have a significant influence on the formation of special geomorphology and the distribution of geological hazards at the eastern edge of the Tibetan Plateau.The Anninghe fault zone is a key part of the Y-shaped fault pattern in the Sichuan-Yunnan block of China.In this paper,high-resolution topographic data,multitemporal remote sensing images,numerical calculations,seismic records,and comprehensive field investigations were employed to study the landslide distribution along the active part of the Anninghe.The influence of active faults on the lithology,rock mass structures and slope stress fields were also studied.The results show that the faults within the Anninghe fault zone have damaged the structure and integrity of the slope rock mass,reduced the mechanical strength of the rock mass and controlled the slope failure modes.The faults have also controlled the stress field,the distribution of the plastic strain zone and the maximum shear strain zone of the slope,thus have promoted the formation and evolution of landslides.We find that the studied landslides are linearly distributed along the Anninghe fault zone,and more than 80%of these landslides are within 2–3 km of the fault rupture zone.Moreover,the Anninghe fault zone provides abundant substance for landslides or debris flows.This paper presents four types of sliding mode control of the Anninghe fault zone,e.g.,constituting the whole landslide body,controlling the lateral boundary of the landslide,controlling the crown of the landslide,and constituting the toe of the landslide.The results presented merit close attention as a valuable reference source for local infrastructure planning and engineering projects.

Dynamic Distribution Adaptation Based Transfer Network for Cross Domain Bearing Fault Diagnosis

In machinery fault diagnosis,labeled data are always difficult or even impossible to obtain.Transfer learning can leverage related fault diagnosis knowledge from fully labeled source domain to enhance the fault diagnosis performance in sparsely labeled or unlabeled target domain,which has been widely used for cross domain fault diagnosis.However,existing methods focus on either marginal distribution adaptation(MDA)or conditional distribution adaptation(CDA).In practice,marginal and conditional distributions discrepancies both have significant but different influences on the domain divergence.In this paper,a dynamic distribution adaptation based transfer network(DDATN)is proposed for cross domain bearing fault diagnosis.DDATN utilizes the proposed instance-weighted dynamic maximum mean discrepancy(IDMMD)for dynamic distribution adaptation(DDA),which can dynamically estimate the influences of marginal and conditional distribution and adapt target domain with source domain.The experimental evaluation on cross domain bearing fault diagnosis demonstrates that DDATN can outperformance the state-of-the-art cross domain fault diagnosis methods.

The Optimization Study about Fault Self-Healing Restoration of Power Distribution Network Based on Multi-Agent Technology

In order to quickly and accurately locate the fault location of the distribution network and increase the stability of the distribution network,a fault recovery method based on multi-objective optimization algorithm is proposed.The optimization of the power distribution network fault system based on multiagent technology realizes fast recovery of multi-objective fault,solve the problem of network learning and parameter adjustment in the later stage of particle swarm optimization algorithm falling into the local extreme value dilemma,and realize the multi-dimensional nonlinear optimization of the main grid and the auxiliary grid.The system proposed in this study takes power distribution network as the goal,applies fuzzy probability algorithm,simplifies the calculation process,avoids local extreme value,and finally realizes the energy balance between each power grid.Simulation results show that the Multi-Agent Technology enjoys priority in restoring important load,shortening the recovery time of power grid balance,and reducing the overall line loss rate of power grid.Therefore,the power grid fault self-healing system can improve the safety and stability of the important power grid,and reduce the economic loss rate of the whole power grid.

Containment-Based Multiple PCC Voltage Regulation Strategy for Communication Link and Sensor Faults

The distributed AC microgrid(MG) voltage restoration problem has been extensively studied. Still, many existing secondary voltage control strategies neglect the co-regulation of the voltage at the point of common coupling(PCC) in the AC multi-MG system(MMS). When an MMS consists of sub-MGs connected in series, power flow between the sub-MGs is not possible if the PCC voltage regulation relies on traditional consensus control objectives. In addition, communication faults and sensor faults are inevitable in the MMS. Therefore, a resilient voltage regulation strategy based on containment control is proposed.First, the feedback linearization technique allows us to deal with the nonlinear distributed generation(DG) dynamics, where the PCC regulation problem of an AC MG is transformed into an output feedback tracking problem for a linear multi-agent system(MAS) containing nonlinear dynamics. This process is an indispensable pre-processing in control algorithm design. Moreover, considering the unavailability of full-state measurements and the potential faults present in the sensors, a novel follower observer is designed to handle communication faults. Based on this, a controller based on containment control is designed to achieve voltage regulation. In regulating multiple PCC voltages to a reasonable upper and lower limit, a voltage difference exists between sub-MGs to achieve power flow. In addition, the secondary control algorithm avoids using global information of directed communication network and fault boundaries for communication link and sensor faults. Finally, the simulation results verify the performance of the proposed strategy.