Location Scheme Research Articles

Fault Location Scheme for Over-Zone Feeding Operation Condition on High-Speed Railway

Fault Location Scheme for Over-Zone Feeding Operation Condition on High-Speed Railway

A new fault location scheme for parallel transmission lines using one-terminal data

This paper proposes a fault location (FL) scheme for a two-terminal double-circuit transmission line using one-terminal current and voltage measurements. As the proposed scheme is formulated in the phase-coordinates, the parallel transmission lines are not required to be decoupled, and the proposed scheme can be applied for transposed or untransposed lines. In addition, the proposed scheme takes into account the line asymmetry and the potential couplings between the phases of the same circuit or different circuits. The derived FL equation is based on two concepts. The first concept is that the fault impedance is mainly resistive component. The second one is that the voltages of the similar phases in both circuits at each line terminal are equal to each other. Further, a new fault classification method is introduced to recognize the faulted phases, which are initially required to apply the proposed FL scheme. Moreover, the IEEE 39-bus system is deployed as a test case, and it is simulated on PSCAD/EMTDC software. The frequency-dependent phase model is used to emulate the parallel transmission lines. All fault types, including the cross-circuit faults, are tested considering different fault resistances and locations. In addition, the effect of the measurement errors on the fault location accuracy is investigated.

Stochastic Roadside Unit Location Optimization for Information Propagation in the Internet of Vehicles

This study investigates the problem of roadside unit (RSU) location optimization for information propagation under stochastic traffic conditions. The goal of RSU location optimization is to promote multihop information propagation in the Internet of Vehicles which is the promising application of the Internet of Things in transportation. Considering the information propagation time is significantly affected by traffic density and traffic density is endowed with randomness, the problem is formulated as a two-stage mixed-integer nonlinear stochastic programming. The model aims to minimize the sum of the cost associated with RSU investment and the expectation of the penalty cost associated with the network information propagation time exceeding an acceptable threshold. In the first stage of the programming, the number and location of RSUs are determined when network-wide traffic density is not realized. In the second stage, given the RSU location schemes determined in the first stage and the realization of traffic density, the information propagation shortest paths are determined for all origin-destination pairs to minimize network information propagation time. A genetic algorithm (GA) integrated with the solution of a mixed-integer linear programming (GA-MILP) is proposed to solve the model. Numerical results indicate that the advantage of the proposed model in the reduced information propagation time per cost over the deterministic model can be up to 15.54%. Compared with the conventional GA, the GA-MILP has 10.01% higher computation efficiency. This further leads to a 14.73% lower objective value achieved by the GA-MILP when the number of iterations is 50.

RETRACTED ARTICLE: Fault location measurement of sensor nodes based on fuzzy control algorithm

The sensor nodes are devices with extra capabilities of sensing, communicating and processing of the recorded data. The sensor-based wireless and IoT-enabled networks can contribute a precarious part of army command, defense control, defense communications, computerized based intelligence and surveillance, and above all the targeting systems. Examples of defense applications include monitoring of own army forces and enemy forces; monitoring of ammunition, monitoring of equipment, targeting at certain regions; and nuclear as well as biotechnology-based attack detection. With the advent of AI and latest technologies, a technical paradigm shift can be seen in monitoring the faults in sensor nodes that are capable to collect the data and entire decisions are inferred on the basis of this data. By deploying sensors in critical areas, all the movements can be followed in detail. Hence, instant fault location measurement of sensor nodes with the least complex approaches is the need of the hour. Therefore, a novel soft computing-based approach is proposed in this paper for measuring the fault in locations of sensor-based networks using fuzzy logic and neural networks with high accuracy. The proposed technique allows lower consumption of energy while locating the faults. The results demonstrate the superior performance of the proposed fault location scheme with respect to the network node loss, measurement error, and measurement time taken for detecting faults in locations of sensor nodes. The proposed fuzzy and neural network-based method outperforms the existing benchmarked techniques considered for comparative study.

Completion, development and prospects of multilateral wells

The paper reviews the completion and development of multilateral horizontal wells. Brief data on location schemes of multilateral horizontal wells and completion levels is presented as well. At the same time, the paper analyzes the significance of drilling multilateral horizontal wells in the modern experience of oil and gas production, and their first implementation on the shore of South Caspian in the well No 19 of Garbi Absheron field.

Application of FWA-Artificial Fish Swarm Algorithm in the Location of Low-Carbon Cold Chain Logistics Distribution Center in Beijing-Tianjin-Hebei Metropolitan Area

Green development is the hot spot of cold chain logistics today. Therefore, this paper converts carbon emission into carbon emission cost, comprehensively considers cargo damage, refrigeration, carbon emission, time window, and other factors, and establishes the optimization model of location of low-carbon cold chain logistics in the Beijing-Tianjin-Hebei metropolitan area. Aiming at the problems of the fish swarm algorithm, this paper makes full use of the fireworks algorithm and proposes an improved fish swarm algorithm on the basis of the fireworks algorithm. By introducing the explosion, Gaussian mutation, mapping and selection operations of the fireworks algorithm, the local search ability and diversity of artificial fish are enhanced. Finally, the modified algorithm is applied to optimize the model, and the results show that the location scheme of low-carbon cold chain logistics in Beijing-Tianjin-Hebei metropolitan area with the lowest total cost can be obtained by using fireworks-artificial fish swarm algorithm.

Off-Network Earthquake Location by Earthquake Early Warning Systems: Methodology and Validation

ABSTRACT Regional source-based earthquake early warning systems perform three consecutive tasks: (1) detection and epicenter location, (2) magnitude determination, and (3) ground-motion prediction. The correctness of the magnitude determination is contingent on that of the epicenter location, and the credibility of the ground-motion prediction depends on those of the epicenter location and the magnitude determination. Thus, robust epicenter location scheme is key for regional earthquake early warning systems. Available source-based systems yield acceptably accurate locations when the earthquakes occur inside the real-time seismic network, but they return erroneous results otherwise. In this study, a real-time algorithm that is intended as a supplement to an existing regional earthquake early warning systems is introduced with the sole objective of ameliorating its off-network location capacity. The new algorithm combines measurements from three or more network stations that are analyzed jointly using an array methodology to give the P-wave slowness vector and S-phase arrival time. Prior to the S-phase picking, the nonarrival of the S phase is used for determining a minimum epicentral distance. This estimate is updated repeatedly with elapsed time until the S phase is picked. Thus, the system timeliness is not compromised by waiting for the S-phase arrival. After the S wave is picked, an epicentral location can be determined using a single array by intersecting the back-azimuth beam with the S-minus-P annulus. When several arrays are assembled, the back azimuth and P and S picks from all arrays are combined to constrain the epicenter. The performance of the array processing for back azimuth and S-wave picking is assessed using a large number of accelerograms, recorded by nine strong motion sensors of the KiK-net seismic network in Japan. The nine stations are treated as three distinct seismic arrays, comprising three stations each. Good agreement is found between array-based and catalog-reported parameters. Finally, the advantage of the new array methodology with respect to alternative schemes for back azimuth and distance is demonstrated.

Fault Location Scheme for Abnormal Grounding Point in Isolated Ground Wire of Large-Scale Clean Energy Transmission

There is a large number of grounding switches along the isolated ground wire for the de-icing in the large-scale wind farm. If any of these grounding switches are left open by accident, this can create an unexpected abnormal grounding point in the isolated ground wire. Based on the analysis of the output power of de-icing devices, the output power of different poles can be applied for the abnormal grounding point fault location. Since the rise of output current to the rated current of de-icing devices requires a long time to build up, the protective relay may lock the de-icing device before the output current reaches the rated current. Thus, the ratio of output energy of two poles can be selected to locate the abnormal grounding point. This study verified this location method by conducting a large number of simulations.

A Hybrid scheme for fault location in unbalanced multi-lateral distribution network with distributed generation

Fault location in an unbalancend multi-lateral distribution network having several branches, laterals, load taps and distributed generation is a major challenge. In case of multi-lateral distribution network, the fault location scheme needs to accurately locate the faulted line segment to avoid the problem of multiple fault location candidates. Traditional fault location schemes in such network employs additional measures to filter out the exact fault location out of the multiple candidates. To overcome the above mentioned problem, a new hybrid method combining high-frequency transient method and impedance based method is proposed in this work for fault location in a unbalacened multi-lateral distribution network. This method first identifies the line section with fault after that the impedance based method is utilized to locate the exact fault location. The simulation results obtained demonstrate that the proposed scheme for fault location is capable of locating all shunt fault type with good accuracy.

Charging station planning based on the accumulation prospect theory and dynamic user equilibrium

Large-scale use of electric vehicles will greatly increase the traffic pressure on urban road network. Therefore, planning of charging stations for electric vehicles considering charging demand and transportation network is particularly important for the coordinated development of electric vehicles and intelligent transportation. Under the condition of bounded rationality, this paper considers such factors as the travel utility perception difference between the users of fuel vehicles and electric vehicles, the time-varying of traffic flow, the location and service level of charging stations. On this basis, combining the cumulative prospect theory, dynamic traffic flow allocation and charging demands, a two-level programming model is established to solve the problem of charging station site selection. The upper layer is a system optimal model, the goal is to minimize the travel time of the network. The lower model describes the time-variability of departure time and the randomness of charging and travel behaviors, establishes the dynamic user equilibrium model and designs the heuristic algorithm. The validity of the model and algorithm is verified by a numerical example. Through the simulation experiment, the optimal location scheme of charging station under different electric vehicle proportion is obtained, and the driving characteristics of two types of vehicles are analyzed. Compared with the traditional model, it is found that the charging station planning considering bounded rationality can achieve higher road network traffic efficiency with fewer charging piles.

A Frequency-Domain-Based Algorithm for Detecting Microseismicity Using Dense Surface Seismic Arrays

ABSTRACT We propose a new frequency-domain-based algorithm for detecting small-magnitude seismic events using dense surface seismic arrays. Our proposed method takes advantage of the high energy carried by S waves, and approximate known source locations, which are used to rotate the horizontal components to obtain the maximum amplitude. By surrounding the known source area with surface geophones, we achieve a favorable geometry for locating the detected seismic events with the backprojection method. To test our new detection method, we used a dense circular array, consisting of 151 5 Hz three-component geophones, over a 5 km aperture that was in operation at the Utah Frontier Observatory for Research in Geothermal Energy (FORGE) in southcentral Utah. We apply the new detection method during a small-scale test injection phase at FORGE, and during an aftershock sequence of an Mw 4.1 earthquake located ∼30 km north of the geophone array, within the Black Rock volcanic field. We are able to detect and locate microseismic events (Mw<0) during injections, despite the high level of anthropogenic activity, and several aftershocks that are missing from the regional catalog. By comparing our method with known algorithms that operate both in the time and frequency domain, we show that our proposed method performs better in the case of the FORGE injection monitoring, and equally well for the off-array aftershock sequence. Our new method has the potential to improve microseismic event detections even in extremely noisy environments, and the proposed location scheme serves as a direct discriminant between true and false detections.

Research on Identification Algorithm of Fragile Nodes: Based on Static and Dynamic Combination of Uncertainty in New Energy

<p>In this work, <span style="font-family: 'Times New Roman';">t</span>aking the coupled 54-node power distribution system and 25-node power flow system as examples, the effectiveness of this method is verified. In addition, a multi-objective ADN joint planning model is established by means of Wasserstein distance measurement and K-medoid scenario analysis. The location, size RES, BESS and expansion schemes of distribution network based on this model are analyzed in detail, in order to provide scientific, reliable, and cost-maximized EVCS’s charging service capabilities. More importantly, we propose a multi-objective optimization algorithm−MONAA algorithm to solve the model.</p>

An FTU-Based Method for Locating Single-Phase High-Impedance Faults Using Transient Zero-Sequence Admittance in Resonant Grounding Systems

A novel fault location scheme using feeder terminal units (FTUs) for high-impedance grounding faults in resonant grounding systems (RGSs) is presented. The parallel resonance for a high-impedance fault (HIF) in an RGS with inverter-interfaced distributed generators (IIDGs) is analyzed. The process exhibits unique distribution features for transient zero-sequence components involving underdamped and overdamped states. We conclude that the transient zero-sequence admittances (TZSAs) from FTUs upstream of the fault point have the maximum value, while the TZSAs obtained from FTUs downstream of the fault point are small for HIFs. Therefore, the proposed location scheme uses FTUs to calculate the maximum values of the TZSA. By comparing with action criteria, the distribution automation (DA) master station utilizes the above results of each FTU to locate the faulty feeder section. The accuracy of the fault characteristics and the proposed method are validated by applying a real-time digital simulator (RTDS) and an FTU-based monitoring system. Additionally, the proposed scheme demonstrates an excellent and reliable performance, considering various faulty feeder sections, fault resistances, arcing faults, fault inception angles, imbalances and the presence of IIDGs and noise.

A Dual-Population Based Evolutionary Algorithm for Multi-Objective Location Problem Under Uncertainty of Facilities

Due to natural disasters or system failures, the facility has the risk of disruption, and thus improving the location reliability under uncertainty of facilities becomes an important issue. In this paper, we propose a multi-objective facility location problem under uncertainty of facilities, where two objectives on reliability are constructed and multiple coverage with variable radius is imposed to reduce the influence caused by the facility disruption. A dual-population based evolutionary algorithm is also suggested to address this problem, where one population is for the location optimization and the other population is for the radius optimization. These two populations iteratively exchange the information obtained from elite solutions during the evolution to collaboratively search for the optimal solutions of the problem. The location population provides the high-quality location schemes for radius population in evaluating the quality of radii of each location, whereas the radius population equips the proper radii for location population in determining the good location schemes. Experimental results indicate that the proposed model can effectively improve the location reliability and the proposed method can obtain higher quality optimal solutions in comparison with four state-of-the-art algorithms. Moreover, the proposed method is applied to a real-world facility location with uncertainty of express cabinets in Tianjin, China, and it produces satisfactory location schemes.

Real-World case studies on transmission line fault location feasibility by using M-Class phasor measurement units

Transmission line fault location is of paramount importance to speed up the power system restoration after outages. Among the existing fault location methods, the most widespread are those based on fundamental phasors, whose estimations must converge to the fault steady-state regime before the line circuit breakers open. Thereby, traditional fault locators usually consider phasor estimations obtained from protective relays or P-class Phasor Measurement Units, which present filtering latency times shorter than those of M-class Phasor Measurement Units. However, although it is commonly assumed that M-class phasor samples are not suitable for fault location applications due to their intrinsic filtering delay, studies on the feasibility of M-class data-based fault location applications are not yet available in the literature. Therefore, this work aims to investigate if M-class Phasor Measurement Units could be used in real fault location schemes, taking advantage of already deployed measurement systems. To do so, actual fault events occurred on the Brazilian power grid are analyzed, and the performance of four different phasor-based fault location algorithms are evaluated when phasor samples obtained from a traditional protective relay algorithm and from M-class Phasor Measurement Units are used as inputs. Unlike the preliminary expectations, the obtained results highlight evidences that M-class phasor measurements can be used in fault location applications, since they resulted in errors within the expected levels for phasor-based fault location methods.

Fault location determination in three-terminal transmission lines connected to industrial microgrids without requiring fault classification data and independent of line parameters

The connection of large industrial microgrids to three-terminal transmission lines greatly complicates the protection scheme of the lines due to the uncertainty in generating renewable energy sources, the probability of unintentional islanding, the abrupt switching of sensitive and critical loads, the influence of supply and demand management programs, and bidirectional active and reactive power flow. This paper presents a fault location algorithm for three-terminal transmission lines connected to an industrial microgrid that does not need the detection of faulty section, fault classification, and transmission line parameters. The proposed method uses voltage and current phasors of transmission lines measured by phasor measurement units (PMUs). One of the salient features of the proposed algorithm is that it does not need to determine the faulty section before the fault location operation. Furthermore, since power transmission lines are always exposed to changing climatic conditions and aging, their electrical characteristics vary over time in the long run compared to their rated value. Hence, this leads to the malfunction of protection schemes. This is solved in this study as the proposed fault location algorithm is independent of line impedances. On the other hand, the dependence of conventional fault location algorithms on fault classification data reduces the reliability of fault location schemes, making these algorithms dependent on fault classification data. However, the present study overcomes this problem as the algorithm is independent of the data of the faulty phase(s) detection. The proposed scheme is fully implemented in the MATLAB software environment, and the performance of the algorithm is analyzed for various fault types under different conditions. The validity of the algorithm is shown by various tests and sensitivity analyses.

Solving a multi-objective heterogeneous sensor network location problem with genetic algorithm

In this paper, we consider a multi-purpose two-level location problem introduced by Karatas (2020) to improve the coverage performance of heterogeneous sensor networks. The problem basically seeks to determine the best location scheme of sensors of different types and characteristics in a belt-shaped boundary area with the purpose of providing a sufficient level of field, point and barrier coverage against different types of intruders. To solve the problem, first, the Mixed Integer Linear Programming (MILP) model developed by Karatas (2020) is used together with a commercial solver and a Non-Dominated Sorting Genetic Algorithm-II (NSGA-II), adapted to solve especially large-sized instances of the problem, is applied. Next, we compare the NSGA-II heuristic with the MILP solved via a commercial exact solver on a number of test instances. The experiment results suggest that the heuristic algorithm can produce a large number of diverse and high-quality solutions in very short computation times in comparison to the exact solver.

A Closed-Form Localization Algorithm in Scan-Based Sonar

Multi-station TDOA positioning is a more accurate positioning method, which can locate the acoustic emitter by processing the arrival time of signals collected by three or more measuring stations. This paper presents a closed-form localization algorithm using the angle-of-arrival and difference time of scan time measurements from the scan-based sonar (SBS).The basic principle of multi station TDOA passive location is proposed. Location scheme based on the combination of different platforms is used. The basic principle of TDOA passive location is discussed, as well as the realization scheme of the main problems such as the synchronization of observation station and acoustic target, the selection of ground observation station, error correction and so on.

A multi-point crosstalk attack detection and location Scheme based on distributed PCE in multi-domain optical networks

In order to solve the problem that crosstalk attack propagation leads to a large number of interference alarms in multi domain optical network and difficult positioning, the detection and screening mechanism based on attack optical path state discrimination and the improved MD-PLVM (multi domain parallel and limited vector Matching) algorithm for multi domain optical network are used in this paper, a new crosstalk attack detection and location scheme based on distributed PCE called DP-CADL (distributed PCE crosstalk attack detection and location) is proposed. The experimental results show that this scheme can not only eliminate the interference alarm and screen the original attack optical path accurately, but also realize the fast location of multiple crosstalk attack sources between domains and cross domain optical path, and has high location accuracy.

A multi-point crosstalk attack detection and localization scheme based on hierarchical PCE in multi-domain optical networks

With the limited number of detection devices and the uncertainty of crosstalk attack source localization, how to propose an effective detection and localization scheme for multipoint crosstalk attack problem in multi-domain optical networks is an important problem that needs to be solved. A new multipoint crosstalk attack detection and location scheme HP-CADL (Hierarchical PCE-Crosstalk Attack Detection and Location) for multi-domain optical networks based on hierarchical PCE is proposed by using the monitoring point selection strategy of local immune algorithm and distributed localization considering continuous parametric analysis. VPI simulation results show that the scheme not only achieves low-cost monitoring and detection and accurate localization of multiple crosstalk attack sources, but also achieves higher accuracy and better performance than other similar schemes in the same multi-domain environment.