Reliability Of Network System Research Articles

Research on the Application of Automation Equipment in Distribution Network Fault Repair

As modern society increasingly relies on electricity supply, the reliability and efficiency of distribution network systems have become particularly important. Distribution network failures will not only cause serious economic losses but may also affect key public services and residents' daily lives. Therefore, quickly and effectively repairing distribution network faults is an important challenge for the power industry. The application of automation equipment has greatly improved the ability to repair distribution network faults. This technological development trend is of great significance to improving the reliability and safety of power grid operations. The article introduces the common problems of distribution network fault repair and the limitations of traditional methods and then discusses in detail the specific application of automation equipment in distribution network fault repair.

Enhancing Fault Identification, Classification and Location Accuracy in Transmission Lines

This research paper presents a proposed system for fault identification, classification and location in transmission lines using a Support Vector Machine (SVM)-based technique in conjunction with a Positive Sequence Analyzer. The objective is to develop an accurate and reliable method for identifying, classifying and locating different fault types in transmission lines. The proposed system leverages the capabilities of SVMs in handling high-dimensional feature spaces and the fault signature extraction capabilities of the Positive Sequence Analyzer. Experimental evaluations are conducted to assess the performance and effectiveness of the proposed system, comparing it with existing fault identification and classification methods. The results demonstrate the superior performance and robustness of the SVM-based technique utilizing the Positive Sequence Analyzer, providing a valuable contribution to fault management and system reliability in transmission line networks.

Exploring Fault Tolerance Consensus for Wireless Sensor Networks: A Comprehensive Detailed Study

The integration of wireless networks into modern communication systems has revolutionized information exchange across various applications. However, achieving reliable agreement in these networks is significantly impeded by their unique properties, such as blurring, interruption, and transparency. A fundamental component of distributed systems, fault-tolerant consensus ensures that nodes in the network can agree on a consistent value even in the presence of malfunctioning or corrupted elements. This study explores both non-Byzantine and Byzantine fault-tolerant consensus approaches, with a focus on achieving agreement in the presence of benign faults. The importance of fault-tolerant consensus in wireless connections is underscored, particularly in applications like wireless blockchain, IoT, and vehicular networks. The research delves into wireless network-specific fault-tolerant consensus algorithms to address the specific challenges posed by networking environments. Furthermore, a comparative analysis of Byzantine Fault Tolerance mechanisms in distributed systems is provided to shed light on their features and benefits. It highlights the importance of ensuring system reliability and consistency in wireless networks to maintain seamless communication and data integrity. Moreover, the paper emphasizes the critical role of fault-tolerant consensus in enhancing system resilience and performance. It underscores the need for robust algorithms and protocols to detect and mitigate errors, ensuring reliable communication and coordination despite potential node failures. By providing insights into fault-tolerant consensus mechanisms tailored to dynamic conditions, the study aims to optimize system adaptation and effectively mitigate both Byzantine and non-Byzantine failures in wireless network environments.

Critical Analysis of Active Filter for Harmonic Reduction under Varying Load

In this paper, we give the main focus on the proliferation of non-linear loads in power systems, the mitigation of harmonics has become a critical concern to ensure stable and efficient operation. This study presents an analysis of an advanced control active filter (ACAF) designed for harmonic reduction under varying load conditions. The ACAF is a sophisticated solution that employs advanced control algorithms to effectively suppress harmonics and maintain power quality. The research investigates the performance of the ACAF under varying load conditions, which represent real-world scenarios where power consumption fluctuates. A comprehensive analysis is conducted to evaluate the filter's ability to adapt and maintain harmonic suppression efficiency across different load profiles. The study considers various load scenarios, including steady-state operation, transient load changes, and dynamic load fluctuations. The findings of this research contribute to the understanding of advanced control active filters in practical power systems with non-linear loads and varying operating conditions. The analysis provides valuable insights into the design, optimization, and implementation of ACAFs for harmonic mitigation, ultimately improving power quality and system reliability in modern electrical networks. A classified list of 38 publications on this topic is also given for the quick reference.

Stability analysis and control parameter optimization for AC-DC hybrid spot networks

AC-DC hybrid spot networks contain strong redundancy. It further enhances the power supply reliability of spot network systems and is helpful for the integration of distributed energy resources (DERs). However, there are few stability analysis studies of AC-DC hybrid spot networks. Focusing on the AC-DC hybrid spot network, which adopts a unified control strategy, its stability problem is studied in this article. A mathematical model of each unit is constructed for this system. Via linearization of spatial state equations, a small-signal model of the AC-DC hybrid spot network is established under different operation modes. Moreover, corresponding eigenvalue criteria are obtained, and the stability problem is analyzed by using the eigenvalue analysis method when the AC-DC hybrid spot network is subjected to a slight interference under the unified control strategy. The dominant factors of each eigenvalue are studied. Based on this approach, the influence of different control parameters on the system stability is demonstrated. Then, the control parameters are selected for control optimization. A simulation model is constructed in MATLAB/Simulink software. The eigenvalue criteria and simulation results validate the applicability of the small-signal model constructed in this article and the effectiveness of the optimization conclusions.

Optimal Allocation of Battery Energy Storage Systems to Enhance System Performance and Reliability in Unbalanced Distribution Networks

The continuously increasing renewable distributed generation (DG) penetration rate significantly reduces environmental pollution and power generation cost and satisfies society’s rapid growth in electricity demand. Nevertheless, high penetration of renewable DGs, such as wind power and photovoltaics (PV), might deteriorate the system’s efficiency and reliability due to its intermittent and stochastic natures. Introducing battery energy storage systems (BESSs) to the distribution system provides a practical method to compensate for the above deficiency since it can deliver and absorb power when needed. Hence, it is important to determine the optimal allocation of BESS to achieve maximum assistance in the grid. This study proposes an optimal BESS allocation methodology to improve reliability and economics in unbalanced distribution systems. The optimal BESS allocation problem is solved by simultaneously minimizing the cost of energy interruption, expected energy not supplied, power loss, line loading, voltage deviation, and BESS cost. The proposed technique is implemented and analyzed on a high renewable DG penetrated unbalanced IEEE-33 bus network using DIgSILENT PowerFactory software (version 2020 SP2A). An enhanced grey wolf optimization (EGWO) algorithm is developed to optimize BESS location and size according to the selected objective function. The simulation results show that the proposed optimal BESS optimization technique significantly improves the economics and reliability in unbalanced distribution systems and the EGWO outperforms the gray wolf optimization (GWO) and particle swarm optimization (PSO) algorithms.

English

English

Функциональное формирование нейроморфного резервуарного вычислительного элемента на базе мемристивного метаматериала

A neural network structure is designed based on the ability of a certain class of calculators to recombine internal resources in order to produce neuromorphic elements to solve applied problems. This approach is rooted in a composite material with controlled local conductivity to form volumetric inhomogeneities capable of responding to and influencing external electrostatic effects. Such compounds aggregate into stable clusters suitable for modelling the processes that occur during information processing in natural neuronal entities. The use of conductive transitions between substrate-formed neuromorphic clusters as a learning structure makes it possible to increase the reliability of the neural network system. Long-term, non-volatile storage of information about the elements of the training sample in variable structures is possible. The basic approach to information conversion is to manage the electrostatic influence as it passes through the layered structures formed. The response to the input is not formed by propagating the signal through conductive elements with variable conductivity, but by passing the energy impact through a limited volume of metamaterial. Thus, a massively parallel processing of information can be achieved with the implementation of a mechanism for combining the opinions of independent neural network clusters that influence the final decision. Furthermore, this method of spreading effects in such an environment greatly simplifies the process of adding elements to the neural network. The lack of direct electrical interconnection facilitates the easy addition of new computational elements without significant rearrangement of the conductive media. Networks of this type are capable of significant growth without loss of experience. The input conversion process using modified delta coding prevents premature wear and tear on reconfigurable network elements. The manner in which information is presented and the manner in which neural network computing is organised enabled the creation of limited autonomous oscillations within the volume of the calculator to maintain circulating memory and the ability to gradually accumulate network experience for its subsequent recording in configurable elements. The identified features resulted in the application of this kind of calculators in the task of developing radio frequency management plans for the organisation of stable communication in a complex electromagnetic environment.

Comparative Study on Strategies for the Division of Earthquake-Proof Strengthening Segments to Reinforce the Reliability of Water Supply Systems

It is very important to secure the sustainability of physical and non-physical social infrastructure facilities in the event of a disaster. The water supply network is particularly vulnerable to seismic damage, and so physical earthquake resistance is very necessary to adapt to or withstand disaster situations. This study evaluated various strategic methods to improve the reliability of water distribution network systems in the event of an earthquake disaster with a focus on structural earthquake-proofing methods for pipelines. For this purpose, three major flow-, diameter- and connection-hierarchy-based earthquake proofing strategies are proposed. We quantified the extent to which earthquake reliability improved after the strengthening of the earthquake-proofing of the pipeline segments, which had been divided based on the proposed strategies. The proposed methodology of dividing the pipeline segments for earthquake-proof strengthening was applied to the water supply system of the Republic of Korea and analyzed thereafter. As a result, it was confirmed that the associated costs and the extent of the improvement in the reliability of earthquake proofing for each strategy and scenario need to be precisely analyzed. Thus, it is necessary to execute strategic earthquake proofing of pipelines with medium size diameters and which occupy most of the length of a mainline, in order to simultaneously satisfy the reliability and cost efficiency of the relevant water supply. However, additional earthquake proofing for segments of a higher level of flowrate is required because a marked drop in overall reliability is caused if they are damaged. In addition, because the effect of an increase in reliability in comparison with the costs incurred is insignificant in the case of some low demand and small-diameter pipeline segments, it is reasonable to exclude earthquake resistance strategies for these sections. The proposed study results—determining the level of importance of each resistance method—can be utilized to make a combined plan for optimal earthquake-proofing strategies.

Optimization method of distribution network energy storage and capacity planning considering uncertainty of new energy sources

The large-scale connection of the renewable energy with random and fluctuating output of the grid has a serious impact on the safe and stable operation of the grid. Considering the high cost of energy storage and the fluctuation of load, in this study, an optimization approach for designing the distribution network’s energy storage capacity is presented. This paper analyzes the uncertainty of new energy, and constructs a single distribution network energy storage station model based on the analysis results. In this paper, the typical daily total network loss is taken as the objective function for site selection and capacity planning. In this paper, particle swarm optimization algorithm is used to optimize the energy storage and capacity planning of distribution network. The experimental results show that this method can reduce the operating cost of distribution network and restrain the system load fluctuation. This method optimizes the economy and reliability of distribution network system.

Analyzing connectivity reliability and critical units for highway networks in high-intensity seismic region using Bayesian network

It is important to evaluate the connectivity reliability of highway networks for the emergency response and rehabilitation of transportation systems in high-intensity seismic regions. Given the complexity and uncertainty of seismic damages of highway networks in high-intensity seismic region, this paper describes a Bayesian network (BN) model for evaluating the network connectivity reliability and identifying critical units. The empirical prediction method is employed to compute the connectivity probability of highway units based on the structural damage of units under earthquakes. A success tree is used to construct the network connectivity graph. Then, the network connectivity graph is converted into the BN model by BN method with the connectivity probability of highway units as prior probability. Sensitivity analysis and Bayesian updating are performed in BN to identify critical units and dynamically assess the connectivity reliability of highway network. The proposed model is applied to a highway network composed of G213 and S9 in the Wenchuan Earthquake. The results show that the BN model integrates the structural damage of units with the functional performance of the highway network in high-intensity seismic region. Bayesian updating allows the posterior probability of segments and origin–destination pairs to be computed, providing an online evaluation of the functional performance of the highway network. The identification of critical units at each stage enables seismic reinforcement priority, thus contributing to the rehabilitation on connectivity reliability of network system.

Reliability of the nonalcoholic steatohepatitis clinical research network and steatosis activity fibrosis histological scoring systems

We aimed to determine whether lobular inflammation and ballooning grades in the Non-alcoholic Steatohepatitis Clinical Research Network (NASH CRN) scoring system can be directly translated into the same for the Steatosis Activity Fibrosis scoring system (SAF) and to look at intra-observer and inter-observer agreement for each individual histological component and for diagnosis of non-alcoholic steatohepatitis (NASH) using the two scoring systems. Four pathologists from two Asian centers scored 20 digitalized slides, twice using the NASH CRN, twice using the SAF. Intra-observer and inter-observer agreement was analyzed using Fleiss' kappa, weighted kappa, or Cohen kappa, where appropriate. The intra-observer discrepancy rate when using the NASH CRN compared with the SAF was higher than when using the individual scoring system for lobular inflammation (15% comparing both scoring systems vs 10% and 1.8% for the NASH CRN and the SAF, respectively) and hepatocyte ballooning (33.8% vs 12.5% and 5%, respectively), but not for diagnosis of NASH (6.3% vs 6.3% and 0%, respectively). Intra-observer and inter-observer agreement was substantial to almost perfect, except for inter-observer agreement for lobular inflammation and diagnosis of NASH, which was only fair to moderate in most instances. These findings do not support the direct inter-translation between the NASH CRN and the SAF. However, the diagnosis of NASH during examinations using the NASH CRN may be comparable with diagnosis of NASH using the SAF, vice versa. The inter-observer agreement for lobular inflammation and NASH diagnosis needs to be improved.

Super Vertex (Edge)-Connectivity of Varietal Hypercube

The reliability measure of networks is of significant importance to the design and maintenance of networks. Based on connectivity, many refined quantitative indicators for the reliability of network systems have been introduced. The super vertex edge-connectivity and cyclic edge-connectivity, as important parameters to evaluate the robustness of networks, are explored extensively. As a variant of the hypercube Qn, the varietal hypercube VQn has better properties than Qn with the same number of edges and vertices. Wang and Xu have proved that VQn is super vertex-connected for n≥1 and is also super edge-connected if n≠2. In this paper, we use another method to prove these results. Moreover, we also obtain the super restricted connectivity and the cyclic edge-connectivity of the varietal hypercube VQn.

Design Specification for Network Fault Diagnosis System

As the network becomes more and more complex and heterogeneous, the problem of network management becomes more and more prominent. The research and application of network management is of great significance for ensuring the normal operation of network and improving the reliability and availability of network system. The main problems of network management are network configuration, failure, performance, security, planning and scaling, etc. On the basis of in-depth research and discussion on network management and fault management, this paper designs the system requirements of network fault diagnosis system.

Analysis of signature reliability of ring-shaped network system

PurposeThe purpose of this paper is to design a ring network topology system and alter it into a series–parallel type framework. Then, reliability of the framework is analysed and authors also discussed the signature to analyse the most sensitive component.Design/methodology/approachThis study presents a ring-shaped network system where this type of topology forms a single continuous pathway for signals through every node. In this study, a system consists of ring network topology is generalized in the series–parallel mixed configuration and reliability characteristics are evaluated with the assistance of universal generating function (UGF) technique. The system consists of wires, repeaters, components or computers and power supply. The wires and repeaters are in series, so, if they fail the whole system will fail and the signals will not go further. The components or computers are connected to each other in parallel configuration. So, the whole system will not fail until the last computer is working. There is also a two-unit power supply system which has one unit in a standby mode. On the failure of first power supply, the second one will start functioning and the whole system fails on the failure of both power supply.FindingsBy the assistance of UGF technique, reliability function of the framework is evaluated. Also, Barlow–Proschan index and expected lifetime for the designed system is estimated by considering a numerical example for the general ring-shaped network system.Originality/valueUGF technique is very effective for estimating the reliability of a system with complex structure and having two performance rates, i.e. completely failed and perfectly working, or more than two, i.e. multi-state performance. This technique enables to estimate every components contribution in the working and failure of the whole system. A general model of ring-shaped network system is taken and generalized algorithm is drawn for the system. Then a particular numerical example is solved for illustrating the use of this technique.

Bi-level programming approach for coordinated configuration of distributed generations and automation devices in distribution networks

Improving system reliability and voltage profiles in distribution networks requires the simultaneous installation of distributed generations and automation devices. This paper builds a bi-level programming model for the coordinated configuration of distributed generations and automation devices. The upper-level problem is to minimize the total investment cost of distributed generations and automation devices and the penalty cost of power shortages, and the lower-level problem is to minimize the voltage deviation during typical operation mode. To explicitly represent the relationship between the penalty cost of power shortages and installation locations of distributed generations and automation devices, an analytical expression of the failure rates of load nodes with respect to installation locations of distributed generations and automation devices is derived. The bi-level model can be transformed to a mixed-integer nonlinear programming problem by applying the Karush–Kuhn–Tucker theorem because the lower-level problem is a quadratically constrained linear programming problem. Case studies on an IEEE 33-bus distribution system and a practical 110-bus distribution system in China are used to verify the effectiveness of the proposed method.

An Improved Merge Search Approach to Evaluate Reliability in Multistate Network Systems

Many real-world problems, such as power line transmission planning, computer network management, water pipe planning, and traffic flow planning, can be modeled using multistate network systems. One of the most interesting aspects of these problems is that one typically wishes to know the reliability of such a plan, namely the network reliability. To evaluate the reliability of a specific network system, the three-stage method (TSM) is typically applied. TSM consists of 1) finding all minimal paths, 2) finding all <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$d$</tex-math></inline-formula> -system vectors, and 3) calculating the union probability for reliability, where 1) is one of the most challenging problems discussed in the literature. This article proposes an improved merge search method that combines the advantages of both enumeration and searching technologies. A step-by-step exploration of the proposed method is presented and several benchmark comparisons are performed using well-known algorithms to demonstrate the efficiency of the proposed method. The results show that the computation time of the proposed algorithm can save as much as 10 times against the well-known methods in the literature.

Feasibility Analysis of Reliability Analysis Methods Applying in Air Traffic Control System

Air traffic control system plays a vital role of air traffic management system, of which reliability determines the service quality and supply level of air transportation. The structure of air traffic control system is considered, and an expression of reliability analysis is applied. A mount of methods including traditional reliability analysis and network system reliability analysis are introduced to demonstrate whether they are feasibility for reliability analysis of air traffic control system. This work can be used as reference and basic for air traffic control system, which is meaningful for ATM safety operation, system selection and response repair.

A Credit-Based System for Traffic Routing in Support of Vehicular Networks

Network routing has a great impact on the efficiency and reliability of the traffic network system in a real-world scenario. To date, achieving network-consistent performance is the main goal of many traffic network research studies. In this research, a mixed strategy game-theory model for network routing is proposed that discovers the optimal strategies that can be adopted by network route players in a network graph. This model has been validated by measuring the model outcomes using quantal response equilibrium (QRE) technique, which explores the players' noisy decisions by comparing the utilized optimal strategies with Nash equilibrium. The experimental results demonstrate that there is an equilibrium with a mixed strategy of a given network.

Unstructured Data Storage Function for 5G Core Network

In present broadband cellular network, all Network Functions are stateful, in which data related to user/connection/association is stored inside network elements itself. However sateful Network Functions cause multiple connection related problems in case of its failure and it needs a separate standby network to continue the process, which increases maintenance cost and reduces the reliability of network system. A technology called Unstructured Data Storage Function (UDSF) is introduced by 3GPP to resolve data storage issue with stateful Network Functions. In this paper the implementation of UDSF has been explained. UDSF has implemented with stateless principle to create a distributed system that can store structured and unstructured data related to each Network Functions on UDSF instead of in Network Functions. Usage of UDSF in 5G improves reliability of the network system.