Station Failure Research Articles

An Ancillary Decision-Making Method for Hydropower Station Failure Handling Based on Case-Based Reasoning and Knowledge Graph

This paper proposes an ancillary decision-making method for hydropower station failure handling based on knowledge graph and case-based reasoning. The proposed method assists the power station dispatcher to carry out accurate and timely failure handling after an accident. First, the main steps of case-based reasoning are introduced. The main difficulties and their corresponding solutions when applying case-based reasoning to hydropower station failure handling are discussed. Then, an ancillary decision-making method for hydropower station failure handling is proposed. Key steps such as case construction, case retrieval, and case revision are designed. In the proposed method, each case is represented in the form of multiple knowledge graphs, i.e., a system topology knowledge graph, a dispatching regulation knowledge graph, and an accident case knowledge graph. The flexibility of case knowledge extraction, management, and retrieval is greatly enhanced. Finally, the simulation analysis is carried out on a large-scale cascade hydropower station in China. The simulation results show that the proposed method can provide reasonable and reliable ancillary decision-making for the power station dispatcher in the failure handling process, and greatly improve the intelligence level of emergency management at a hydropower station.

Vulnerability assessment and evolution analysis of Beijing's Urban Rail Transit Network

With the development of urban rail transit system, the complexity of the network intensifies, and its vulnerability shifts correspondingly. Understanding the characteristics and evolution of network vulnerability, as well as identifying developmental patterns, enables more scientific network planning. Current researches on network vulnerability predominantly focus on the static vulnerability assessment of existing networks, with limited studies on vulnerability evolution. This paper divides the topological evolution of the Beijing Urban Rail Transit Network (BURTN) from 2000 to 2020 into Formation and Improvement stages using the K-means++ method. By constructing a multidimensional vulnerability assessment model that considers node degree uniformity, network efficiency, and connectivity, the vulnerability evolution characteristics and patterns of BURTN are explored in cases of both Single-station failures and Multi-station consecutive failures (including random and intentional failures). Furthermore, the evolutionary relationship between network vulnerability and network structure is explored using the Ridge regression model. Calculations reveal that in the case of Single-station failures, during the Formation stage, the proportion of highly vulnerable stations (HVS) and the impact of each station failure on network performance decrease significantly, by 69.36 % and 67.67 %, respectively. During the Improvement stage, the proportion of HVS decreases significantly, while the impact of each station failure on network performance decreases slightly, by 79.10 % and 37.04 %, respectively. In the case of Multi-station consecutive failures, during the Formation stage, the network’s ability to cope with both random and intentional failures decreases, with the percentage of network nodes removed at the collapse state decreasing by 24.95 % and 11.12 %, respectively. During the Improvement stage, the network’s ability to cope with random failures remains stable, while its ability to cope with intentional failures decreases. This study helps to understand vulnerability from an evolutionary perspective and provides practical strategies for reducing vulnerability.

Analyzing Volcanic, Tectonic, and Environmental Influences on the Seismic Velocity from 25 Years of Data at Mount St. Helens

Abstract We estimate changes in the seismic velocity (dv/v) from 25 years of ambient seismic noise recorded at Mount St. Helens (MSH). At MSH, the availability of seismic stations changes frequently due to station failure and the installation of new stations. Therefore, it is difficult to combine relative measurements that do not span the same time and space. We tackle this challenge by developing a spatial imaging algorithm to normalize all ∼1400 dv/v time series onto one spatial grid. Thereby, we obtain time-dependent velocity change maps of the MSH region, which we analyze with the help of auxiliary observations, such as ground position (i.e., Global Navigation Satellite System [GNSS]), weather data, environmental observations, and regional seismicity. In the dv/v time series, we find a variety of dynamics caused by volcanic, tectonic, and environmental forcing. With the initiation of MSH’s 2004–2008 volcanic crisis, dv/v exhibits a significant increase, which we link to the deflation of the volcanic plumbing system, also observed on GNSS data. Between 2013 and 2018, when seismicity levels are elevated, we find lower velocities at depth. This phase is followed by an episode of relative quiescence, accompanied by significant dv/v increases close to the St. Helens seismic zone. We suggest a reinflation of the magmatic plumbing system after MSH’s 2004–2008 eruption lasting until about 2017. Afterward, the magmatic activity in the subsurface reduces, thereby decreasing pressure and increasing the seismic velocity. Fluctuating groundwater levels may dominate the seasonal cycles in the dv/v time series. A contrasting seasonal response between the high-elevation edifice and foothill valleys may indicate that surface freezing inhibits subsurface groundwater infiltration at higher altitudes.

Seismic Resilience in Critical Infrastructures: A Power Station Preparedness Case Study

The role of critical infrastructures in maintaining the functioning of the economy and society and ensuring national security, particularly their durability in delivering essential services during crises, including natural disasters such as earthquakes, is critical. This work introduces an analytical methodology to quantify potential earthquake damage to power stations and evaluate the cost-effectiveness of measures to enhance their seismic resistance. By employing fragility curves and probabilistic risk analyses, this approach provides a structured framework for the comprehensive assessment of risks and the identification of economically practical mitigation strategies. A detailed examination of strategies to protect critical power station components against seismic activity is presented, revealing that a minor investment relative to the overall project budget for earthquake-proofing measures is economically effective. This investment, representing a marginal fraction of 0.5% of the total project expenditure significantly reduces the seismic risk of power station failure by 36%. Reinforcing essential elements, including switching stations, water treatment facilities, and water tanks, is emphasized to ensure their continued operation during and after an earthquake. This research highlights the critical significance of integrating risk assessment with benefit-to-cost analysis in strategic decision-making processes, supporting the prioritization of investments in infrastructure enhancements. These enhancements promise substantial reductions of risks at minimal costs, thus protecting essential services against the impacts of natural disasters. This research contributes to state-of-the-art research in critical infrastructures resilience.

A resilient battery electric bus transit system configuration

Electric mobility is fundamental to combat climate change and attaining the United Nations Sustainable Development Goals (SDG-11). However, electric mobility necessitates a seamless integration between power and transportation systems, as the resiliency of both systems is becoming far more interdependent. Here, we focus on disruption to Battery Electric Bus (BEB) transit system charging infrastructure and offer a resilient BEB transit system planning model. The proposed model optimizes the BEB system costs while ensuring the system’s robustness against simultaneous charging station failures. In our case study, a single charging station failure would lead to up to 34.03% service reduction, and two simultaneous failures would reduce the service by up to 58.18%. Our proposed two-stage robust model addresses this issue with a relatively small added cost (3.26% and 8.12% higher than the base model). This cost enables uninterrupted BEB system operation during disruption, ensuring personal mobility, social interaction, and economic productivity.

Spatio-Temporal Analysis and Prediction of Mass Telecommunication Base Station Failure Events

Large-scale telecommunication systems are lifeline infrastructure in modern society. A telecommunication system typically consists of a huge number of base stations with diverse geographical locations across a country, which highly complicates maintenance operations. To allocate maintenance resource properly, it is important to have a good understanding on the failure pattern of these base stations. Statistical inference of recurrent failures of these base stations is challenging because of the large number of base stations and the spatial correlation of their failure processes. Based on eight-month failure data of telecommunication base stations in Harbin, China, we propose a customized nonhomogeneous Poisson process (NHPP) model for recurrent failure data from telecommunication systems. The model consists of two layers, where the temporal layer applies an NHPP with station-specific frailty for failures of each base station, and the spatial layer uses a multivariate lognormal distribution to characterize the correlation among the frailties. The Monte Carlo EM (MCEM) algorithm is applied to estimate parameters included in the proposed model. We demonstrate the proposed model using the Harbin telecommunication system example with 7725 base stations and 4615 failure records.

An Improved Master-Slave Control Strategy for Automatic DC Voltage Control Under the Master Station Failure in MTDC System

The master-slave (MS) control is often used in multi-terminal direct current (MTDC) system due to its stable dc voltage control and precise power regulation. However, the MS switching, which aims to maintain dc voltage control under the master station failure, relies heavily on the high-speed communication between the power dispatch center and each station. Some methods in existing works are proposed to address the high communication dependence, at the cost of steady-state control performance. In this article, an improved MS control including five-state control process is proposed to realize the automatic MS switching without communication participation. Based on logic judgment, the multilayer dc voltage clamping mechanism is created to enhance the redundancy of the dc voltage control, and a reasonable dc voltage recovery process is included to eliminate the dc voltage deviation caused by the master station failure. Furthermore, the power and dc voltage hybrid controller are developed to improve the dynamic performance of each station during the MS switching. Simulation and experimental results demonstrate the effectiveness and advantages of proposed method.

Resilience Assessment of an Urban Rail Transit Network Under Short-Term Operational Disturbances

Operational disturbances within 30 min, namely, short-term operational disturbances (STODs), occur frequently during the daily operation of an urban rail transit (URT) system. Therefore, there is an urgent need to assess a network’s ability to respond to STODs to improve its operational level. The resilience of a URT network jointly considering turn-back operations, the occurrence time of STODs, and passenger travel experience is addressed. By considering passenger travel alternatives under STODs, we assessed the resilience of a network by utilizing the ratio of the average loss of a time-dependent performance indicator, which is referred to as the operational service level indicator in this paper. A simulation-based resilience assessment flowchart is also proposed. Numerical experiments conducted on the Chengdu subway network indicate that this network is more resilient to successive station failure than to simultaneous failure. Guaranteeing the normal operation of transfer stations is vital for enhancing the resilience of a network. The metric proposed in this paper is more practical for assessing resilience than the two commonly used metrics (performance loss and disturbance duration). Additionally, the experimental results highlight that turn-back operations at the stations have a significant impact on the resilience of a URT network. The sensitivity analysis of the parameters indicates that ensuring the normal operation of links connected by critical stations, preventing large-scale station failure, improving passenger tolerance to disturbance durations, and restoring the connectivity of disrupted links rapidly have practical significance for enhancing the resilience of a network.

A Secure LEACH-PRO Protocol Based on Blockchain.

Wireless Sensor Networks (WSNs) are becoming more popular for many applications due to their convenient services. However, sensor nodes may suffer from significant security flaws, leading researchers to propose authentication schemes to protect WSNs. Although these authentication protocols significantly fulfill the required protection, security enhancement with less energy consumption is essential to preserve the availability of resources and secure better performance. In 2020, Youssef et al. suggested a scheme called Enhanced Probabilistic Cluster Head Selection (LEACH-PRO) to extend the sensors' lifetime in WSNs. This paper introduces a new variant of the LEACH-PRO protocol by adopting the blockchain security technique to protect WSNs. The proposed protocol (SLEACH-PRO) performs a decentralized authentication mechanism by applying a blockchain to multiple base stations to avoid system and performance degradation in the event of a station failure. The security analysis of the SLEACH-PRO is performed using Burrows-Abadi-Needham (BAN) logic and Automated Validation of Internet Security Protocols and Applications (AVISPA) tool. Moreover, the SLEACH-PRO is evaluated and compared to related protocols in terms of computational cost and security level based on its resistance against several attacks. The comparison results showed that the SLEACH-PRO protocol is more secure and requires less computational cost compared to other related protocols.

Cell Edge User Capacity-Coverage Reliability Tradeoff for 5G-R Systems With Overlapped Linear Coverage

Fifth-Generation mobile networks for Railway (5G-R) is a promising train-ground communication solution to deal with the design challenges on ubiquitous connections and high reliability transmission for smart railways. Considering the linear coverage scenario along the railway lines, deep overlapping coverage can enhance the coverage reliability, but the capacity of cell edge users is plagued by severe inter-cell interference. In this paper, the fundamental performance of 5G-R systems with linear redundant coverage is investigated. We quantitatively analyze the impact of inter-cell interference on the capacity of cell edge users, in which the exponential effective signal to interference plus noise (SINR) mapping method is utilized to analyze SINR distribution of 5G-R users. Then, we investigate the coverage reliability considering the base station (BS) failure. Finally, taking cell edge user capacity as the optimization objective, we analyze the cell edge user capacity-coverage reliability tradeoff for 5G-R systems, and then provide useful insights into BS deployment for 5G-R systems through performance simulations and numerical results.

Location of disaster assessment UAVs using historical tornado data

Preparing and responding to disasters is a complicated task. One must balance coverage of SAR resources versus preparation cost. This article presents a method and solution to prepositioning UAV damage assessment and search teams in Oklahoma using historical tornado data. The approach is based on set covering and multi-station vehicle routing models. It also presents a method to robustify the solution in the event a UAV team cannot be activated to respond to the disaster. This can simulate a team unable to respond. Results show 70% more stations and teams being required when chance of a depot failure goes from 0 to 5% and 90% more stations required when 0–10%. We find that when trying to use a solution that does not account for depot failure, the system of UAVs cannot meet search completion targets in 3–4% of cases. These results demonstrate accounting for the chance of teams not being able to respond to domestic disasters is important and failing to do so means an increased chance of not being able to respond adequately to disasters and incorporating the chance of station failure has a profound impact on the number of stations needed.

The Use of a Fault Tree Analysis (FTA) in the Operator Reliability Assessment of the Critical Infrastructure on the Example of Water Supply System

Background: Specialist literature indicates a large share of the human factor among the causes of failure of technical systems at the level of 70 to 90%, which depends on the sector studied. The collective water supply system is an anthropotechnical system, i.e., it is a complex connection between man and the technical system resulting from the deliberate influence of man on the technical system. Methods: The work presents an assessment of operator reliability of a selected water treatment process based on the fault tree analysis (FTA). Elementary events are determined by the operator’s error probability. Results: A failure tree was prepared for the peak event of the filter station failure, resulting from an operator’s error during the filter washing procedure. The probability of a peak event occurring is 0.0580. Conclusions: The developed fault tree allows for the identification of elementary events leading to an emergency event. The operator fulfills its task of maintaining the continuity of water treatment.

User-BS Selection Strategy Optimization with RSSI-Based Reliability in 5G Wireless Networks

Although fifth-generation (5G) wireless communication can ] support well a high data rate of transmission, issues such as base station (BS) failure and poor BS signals may cause serious interruption problems. This paper studies the user-BS selection strategy with received signal strength indication (RSSI)-based reliability in 5G wireless networks. First, reliability is defined on the basis of the RSSI and failure probability of the BS. The problem is modeled as a selection strategy optimization problem with BS capacity and receiving sensitivity as constraints. Second, the original problem can be transformed into a resource allocation problem with probabilistic constraints. For the situation where user distribution is known, we used dynamic programming to obtain the optimal BS selection strategy. For the situation where user distribution is unknown, starting from user trajectory data, we used the space–time density estimation method based on the Epanechnikov kernel to estimate user density and bring it into dynamic programming to obtain the optimal selection strategy. Simulation results show that our density estimation algorithm is more accurate than the commonly used density estimation algorithm. Compared with the distance-based optimization method, our RSSI-based optimization method also improved the communication signal quality under different scenarios.

Measurement and Analysis of Environmental Costs in the General Company for Electricity Production, Central Region: An Applied Research in the First Station south of Baghdad

The research aims to identify the environmental costs of the economic unit in sample research, as well as classifying the environmental cost to prevention costs, appraisal cost, internal failure cost and external failure cost. moreover the research aims to measure and analyses the apparent and hidden environmental cost. related to the activities undertaken and clarifying the impact of these costs on the institute as a whole. The research problem a raised As a result of the high costs incurred by the economic unit in sample research, represented by the electric power plant in order to preserve the environment, it was found that the company suffers from a weakness in the measurement and analysis of environmental costs according to the classifications of its activities, which in turn is reflected in the costs incurred by the company, causing its increase as a result of lack of Classification it at the expense of its activities, in order to remove the environmental damage resulting from the practice of the activity of the unit, which negatively affects the quality of the environmental service of the company. The research was based on the hypothesis that Accurate and clear measurement and analysis of environmental costs will contribute to determining environmental costs based on the classification of their activities, and thus knowledge of the resulting environmental damage and the possibility of avoiding or limiting them, Where the research reached many conclusions, the most important of which is the station's failure to measure, analyze, and determine the environmental costs to prevent pollutants coming out of the electric power production process.

Optimized Voltage-Led Customer Load Active Service Using Genetic Algorithm in Distribution Networks

To mitigate the low frequency problem in a transmission system in an event of a power station failure or during low renewable generation production, UK National Grid (NG) Electricity System Operator has balancing mechanism in place with generators to provide temporary extra power, or with large energy users to reduce load demand or so call fast reserve services. This paper presents an alternative method to aggregately control the existing distribution network primary on load transformer tap changers as a voltage-led customer load active service. The main benefits of the proposed method are (i) to unlock the distribution network load demand flexibility without causing any negative impact on customers, and (ii) to provide the lowest cost of fast reserve service from a distribution network to transmission network. In this paper an optimal control strategy based on genetic algorithm is proposed and developed to achieve an optimized voltage-led customer load active service with the aim of finding the optimal dispatch of on load transformer tap changers by minimizing each transformer tap switching operation as well as network losses. Two practical 102 buses and 222 buses UK distribution networks have been modelled and used to demonstrate and compare the effectiveness of the proposed control methods under different operating conditions. The performances of the proposed method are also compared with both the rule-based and the branch-and-bound methods. The results show that the proposed optimal control strategy based on the genetic algorithm is more effective by achieving more accuracy and a faster solution for a large distribution network than other two methods. These are important findings as the fast reserve service by transmission network requires the accuracy of the load demand reduction delivery within 2 minutes.

Fault Spread and Recovery Strategy of Urban Rail Transit System Based on Complex Network

Urban rail transit is an important existence in the urban transportation system. In recent years, a large number of people will take it as their preferred travel mode, but the station failure caused by emergencies is inevitable. The impact on the whole system makes people put forward higher requirements for the operation of rail transit. Therefore, how to suppress the fault spread and how to quickly and effectively recover the urban rail transit system after the fault spread is an urgent problem to be solved. In this paper, based on the metro network data obtained from Gaode map, the network topology model was established by using the complex network theory. Then, the fault spread law of the metro network without recovery and the fault spread law with recovery were studied. Finally, the four strategies were simulated and compared.

Dynamic Scheduling Framework of the Flexible Mixed-Model Assembly Line Based on the Internet of Manufacturing Things

In mass customization (MC), the assembly operations of modular products tend to be organized as the form of flexible mixed-model assembly line (FMMAL). The dynamic scheduling problem of FMMAL is quite complex with product sequencing, station allocation, material delivery, disruption events of station failure, product inserting and product reworking. To solve these problems, a comprehensive framework combining the architecture of Internet of Manufacturing Things (IoMT) with the dynamic scheduling algorithms is proposed. Firstly, the IoMT-based FMMAL are constructed via the multi-agent system (MAS) and ubiquitous environment. Secondly, a mathematical model of FMMAL is formulated with the decision variables, optimization objectives and constraint conditions. Thirdly, the IoMT-oriented algorithms for dynamic scheduling are proposed including the fuzzy analytic hierarchy process (FAHP) for normalization, weighted sum of properties-improved genetic algorithm (WSP-IGA) for prescheduling, priority weights search-simulated annealing (PWS-SA) for rescheduling. Lastly, a discrete event simulation of a numerical case is conducted to demonstrate the practicality and validity of proposed theories and algorithms. The results show that the proposed hyper-heuristics (WSP-IGA and PWS-SA) can respectively realize the prescheduling and rescheduling of FMMAL in four modes including the synthesized mode, time-efficient mode, just-in-time mode and energy-saving mode, which are superior to the four referenced meta-heuristics.

The Research on Delay Propagation of Urban Rail Transit Operation under Sudden Failure

With the increase and extension of urban rail transit lines, networked operation has become an inevitable trend of rail transit operations. Once an emergency occurs, it will cause operational delays; in serious cases, it may further lead to group safety incidents. Firstly, the sudden failure of rail transit is defined, statistical calculation is made according to the accumulated failure data, and then the sudden failures and average processing time are quantitatively calculated. Secondly, the time delay and propagation under the state of sudden failure are analyzed, on the basis of which the propagation and dissipation of time delay based on the single station failure cellular automata model and SIR model network based on multistation fault delay propagation are constructed. Finally, the reliability and accuracy of the model are verified by a case of rail transit in a city. The scheme in this paper can be used to estimate the scope of time and space delay under the sudden failure of rail transit and can provide the basis for the adjustment of traffic organization scheme and evacuation of passenger flow under the sudden failure.

Bypass Schemes of Urban Transit Station Based on Complex Network Theory

To study detour scheme after failure of urban transit station, urban transit network model is constructed by considering the reciprocal of urban transit line departure time interval as the weight. In accordance with the characteristics of the traffic flow, the network is studied under different time intervals, namely, morning, evening, and flat rush hours. First, an urban transit network topological characteristic index analysis model was constructed by combining ABC management method to identify the key elements of each indicator. Second, on the basis of the research on topological characteristic indicators, average path length and global efficiency of the network were used to measure the urban transit network connectivity, and an urban transit network station failure optimization scheme was designed. The optimization effect was judged by the changes in the two index values before and after the bus stop detour in accordance with the number of stations in the bypass area, namely, two stations, one station, and zero stations. Finally, the reliability of the model is studied, considering the urban transit network in Huangdao District of Qingdao. Through the analysis of node degree, second-order node degree, centrality, and other indicators, the urban transit network in Huangdao District of Qingdao was found to have evident small-world characteristics, and the top ranking stations of node degree value and centrality index are mainly distributed in the new urban edge planning area and the urban center area. In addition, for stations with the same rank, the node centrality value at each time interval has the following order: morning rush hours> evening rush hours> flat rush hours. The top 10 urban transit stations with node degree value are selected as the failure stations for optimization analysis. Results show that the average shortest path length of the optimized network decreases, the global efficiency of the network increases, and the optimized scheme is reliable.

A Method of Optimal Malfunction Management in Urban Natural Gas Transmission and Distribution Systems

Given the increasing number of urban natural gas transmission and distribution systems, it is particularly crucial to optimize the management of natural gas operations, especially when equipment failure or pipeline leakage occurs in the supply system. To meet the needs of customers for natural gas, in this paper, we considered two cases of pipeline rupture leakage and pressure regulation station failure for different supply areas. We combined natural gas supply pipelines, pressure regulating stations and a gasholder station to establish a failure optimization management model and used genetic algorithms and one-dimensional fluid dynamics models for optimization management and proposed the following two solutions: 1. Complete operation strategy: modify both the pressure of the pressure regulating station and the air supply volume of the gasholder station; 2. Partial operation strategy: modify the pressure of the pressure regulating station only, and keep the supply volume of the gasholder station constant. Finally, our model is applied to an urban natural gas transmission and distribution system. Based on the actual results, failure optimization management is proposed according to the location and the type of failure and constructive options are suggested for the operation of natural gas networks.