Fault location in the distribution network based on power system status estimation with smart meters data

2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Masoud Dashtdar ◽  
Seyed Mohammad Sadegh Hosseinimoghadam ◽  
Majid Dashtdar
Keyword(s):  
Power Flow ◽  
Fault Location ◽  
Voltage Drop ◽  
Distribution Network ◽  
Smart Meters ◽  
Fault Resistance ◽  
Different Types ◽  
Bus Networks ◽  
Types Of Faults ◽  
Proper Performance

Abstract Due to the existence of different branches in the electricity distribution network and only available voltage and current information at the beginning of the line and lack of access to the information at the end of the network line, the detection of the faulted section in the distribution network has become more important. Today, smart meters are used to measure the voltage and current of network lines, but due to the limitations of the installation sites, these devices are not possible in all network lines. In this paper, two techniques have been used to identify the faulted section and fault location in the network so that the fault distance at the beginning of the line can be estimated by estimating the current at the end of each network line. Therefore, in this project, by installing smart meters in the main branch of the network and also the information obtained from power flow in the network normal mode, it has been tried to practically estimate the voltage and current at the beginning and end of each distribution network line. In this method, more power flow is used to calculate the voltage drop of the lines and estimate the voltage and current at the end of the network lines so that the faulted part can be identified. Finally, the proposed method is implemented on the IEEE_15, 37 bus networks, the results of which show the proper performance of the proposed method in estimating location and Fault resistance for different types of faults in the distribution network.

scholarly journals Detecting the Fault Section in the Distribution Network with Distributed Generators Based on Optimal Placement of Smart Meters

2019 ◽  
Vol 19 (2) ◽  
pp. 28-34 ◽  
Author(s):  
Majid Dashtdar ◽  
Masoud Dashtdar
Keyword(s):  
Fault Location ◽  
Voltage Drop ◽  
Distribution Network ◽  
Distribution Networks ◽  
Optimal Number ◽  
Optimal Placement ◽  
Voltage Distribution ◽  
Smart Meters ◽  
Good Efficiency ◽  
Medium Voltage

AbstractOne of the most important issues in employing distribution networks is detecting the fault location in medium-voltage distribution feeders. Due to the vastness of distribution networks and growing distributed generation (DG) sources in this network, detection is difficult with the common methods. The aim of this paper is to present a method based on voltage distributed meters in a medium-voltage distribution network (by smart meters installed along the feeder) in order to detect the fault location in the presence of DG sources. Due to vastness of distribution network and cost of installing smart meters, it is not economically possible to install meters in all the Buses of the network. That’s why in this article, combination of genetic and locating algorithms and fault-based on voltage drop has been used to suggest a method to optimize the meter locations. In order to evaluate the efficiency of the method suggested, first we determine the optimal number and location of the meters and then we apply the fault that has been simulated in different Buses of the sample network, using PSCAD/EMTDC software. After results analysis, the fault location is estimated by MATLAB. Simulation results show that the fault locating method by optimal number of meters has good efficiency and accuracy in detecting faults in different spots and in different resistance ranges.

scholarly journals Real Fault Location in a Distribution Network Using Smart Feeder Meter Data

Energies ◽  
2021 ◽  
Vol 14 (11) ◽  
pp. 3242
Author(s):  
Hamid Mirshekali ◽  
Rahman Dashti ◽  
Karsten Handrup ◽  
Hamid Reza Shaker
Keyword(s):  
Fault Location ◽  
Network Reliability ◽  
Distribution Network ◽  
Estimation Method ◽  
Electrical Energy ◽  
Distribution Networks ◽  
Active Power ◽  
Financial Loss ◽  
Smart Meters ◽  
The Real

Distribution networks transmit electrical energy from an upstream network to customers. Undesirable circumstances such as faults in the distribution networks can cause hazardous conditions, equipment failure, and power outages. Therefore, to avoid financial loss, to maintain customer satisfaction, and network reliability, it is vital to restore the network as fast as possible. In this paper, a new fault location (FL) algorithm that uses the recorded data of smart meters (SMs) and smart feeder meters (SFMs) to locate the actual point of fault, is introduced. The method does not require high-resolution measurements, which is among the main advantages of the method. An impedance-based technique is utilized to detect all possible FL candidates in the distribution network. After the fault occurrence, the protection relay sends a signal to all SFMs, to collect the recorded active power of all connected lines after the fault. The higher value of active power represents the real faulty section due to the high-fault current. The effectiveness of the proposed method was investigated on an IEEE 11-node test feeder in MATLAB SIMULINK 2020b, under several situations, such as different fault resistances, distances, inception angles, and types. In some cases, the algorithm found two or three candidates for FL. In these cases, the section estimation helped to identify the real fault among all candidates. Section estimation method performs well for all simulated cases. The results showed that the proposed method was accurate and was able to precisely detect the real faulty section. To experimentally evaluate the proposed method’s powerfulness, a laboratory test and its simulation were carried out. The algorithm was precisely able to distinguish the real faulty section among all candidates in the experiment. The results revealed the robustness and effectiveness of the proposed method.

scholarly journals A Fast Protection Scheme for TCSC Compensated Transmission Line Using Wavelet-Alienation-Neural Technique

2021 ◽  
Author(s):  
Bhuvnesh Rathore ◽  
Amit Gangwar ◽  
Om Prakash Mahela ◽  
baseem khan ◽  
Sanjeevikumar *Padmanaban
Keyword(s):  
Cycle Time ◽  
Power Flow ◽  
Fault Location ◽  
Fault Current ◽  
Protection Scheme ◽  
Fault Resistance ◽  
Security Algorithm ◽  
Artificial Neural Network Ann ◽  
Thyristor Controlled Series Compensator ◽  
Frequency Power

This paper proposes a security algorithm based on thewavelet-alienation-neural technique for detecting, classifying, and locating faults on Thyristor-Controlled Series compensator (TCSC) compensated lines. A fault index has been calculated using wavelet transform and alienation coefficients with post-fault current signals measured/ sampled for quarter cycle time at both near and far end buses for fault detection and classification. The location of the fault is predicted using an Artificial Neural Network (ANN) after the fault has been diagnosed. Approximate coefficients (quarter cycle time) of both voltage and current signals, from both buses, were provided as input to ANN. Various case studies, such as variations in TCSC position, fault location, sampling frequency, power flow path, incipient angle of fault, TCSC control strategy, fault resistance, and load switching conditions, have verified the robustness of the proposed safety system.

scholarly journals Using smart meters for checking the topology and power flow calculation of a secondary distribution network

2019 ◽  
Vol 139 ◽  
pp. 01059
Author(s):  
Irina Golub ◽  
Evgeny Boloev ◽  
Yana Kuzkina
Keyword(s):  
Power Flow ◽  
Reactive Power ◽  
Distribution Network ◽  
Smart Meters ◽  
Power Flow Calculation ◽  
Flow Calculation ◽  
Three Phase ◽  
Secondary Distribution ◽  
Linear State ◽  
Selection Of

The paper analyzes options of using smart meters for power flow calculation and for assessing the state of a real three-phase four-wire secondary distribution network based on measurements of average values of active and reactive power and of voltages. The work is based on the authors’ research on allocation of measurements to ensure secondary distribution network observability and on selection of the most efficient method for linear and non-linear state estimation. The paper illustrates solution of a problem on identification composition of load nodes in the phases and reveals challenges related to voltage account in the neutral wire and in its grounding.

Fault Analysis of Distribution Network which Contains Distributed Generation

2013 ◽  
Vol 325-326 ◽  
pp. 624-627 ◽  
Author(s):  
Ming Jun Chen ◽  
Chen Zhu Xuan ◽  
Xin Kai Lian
Keyword(s):  
Power Generation ◽  
Thermoelectric Power ◽  
Power Flow ◽  
Fault Location ◽  
Short Circuit ◽  
Distribution Network ◽  
Wind Farms ◽  
Short Circuit Current ◽  
Fault Analysis ◽  
Photovoltaic Power

when the photovoltaic power generation and thermoelectric power factory connect into the distribution network , the system change from one source to several sources. it will change the construction of the system and the system power flow ,and also the size and direction of short-circuit current. It is harder to prepare the grid protection devices and set value for the protection. This paper studied the complex electronic systems which contains wind farms and thermoelectric power factory, analysis the change of voltage and current of each bus when the fault happen after the photovoltaic power generation connected into the system, and also talk about how the fault location affect the system fault component .Then conduct the expression of the fault current of each line to provide the basis for the study of multiterminal supply network protection strategy.

scholarly journals Fault Location for Multi-source Distribution Network Based on Improved Chaotic Jaya Algorithm

2021 ◽  
Vol 2095 (1) ◽  
pp. 012016
Author(s):  
Jian Zhou ◽  
Shanshan Shi ◽  
Yong Cui ◽  
Yun Su ◽  
Min Wang ◽  
...  
Keyword(s):  
Power Flow ◽  
Fault Location ◽  
Distribution Network ◽  
Flow Distribution ◽  
Source Distribution ◽  
Jaya Algorithm ◽  
Distributed Energy ◽  
Speed Up ◽  
The Individual ◽  
Wide Access

Abstract Due to the wide access of distributed energy in the distribution network, the structure of the distribution network becomes complex and diverse, and the power flow distribution is flexible and changeable. To optimize the fault location performance of the multisource distribution network, this paper proposes a power grid fault location solution method based on the improved Jaya algorithm. By combining the chaos theory with the Jaya algorithm, the individual position iteration of the algorithm is optimized to improve the algorithm’s global optimization capability and speed up the fault location. Through the example test and comparison with the traditional algorithm, the experimental results verify the effectiveness and superiority of this method.

scholarly journals The Current State of the Art in Research on Predictive Maintenance in Smart Grid Distribution Network: Fault’s Types, Causes, and Prediction Methods—A Systematic Review

Energies ◽  
2021 ◽  
Vol 14 (16) ◽  
pp. 5078
Author(s):  
Moamin A. Mahmoud ◽  
Naziffa Raha Md Nasir ◽  
Mathuri Gurunathan ◽  
Preveena Raj ◽  
Salama A. Mostafa
Keyword(s):  
Smart Grid ◽  
Fault Location ◽  
Deep Understanding ◽  
Predictive Maintenance ◽  
Smart Meters ◽  
Grid Systems ◽  
Current State ◽  
Future Direction ◽  
Growth Of Science ◽  
Types Of Faults

With the exponential growth of science, Internet of Things (IoT) innovation, and expanding significance in renewable energy, Smart Grid has become an advanced innovative thought universally as a solution for the power demand increase around the world. The smart grid is the most practical trend of effective transmission of present-day power assets. The paper aims to survey the present literature concerning predictive maintenance and different types of faults that could be detected within the smart grid. Four databases (Scopus, ScienceDirect, IEEE Xplore, and Web of Science) were searched between 2012 and 2020. Sixty-five (n = 65) were chosen based on specified exclusion and inclusion criteria. Fifty-seven percent (n = 37/65) of the studies analyzed the issues from predictive maintenance perspectives, while about 18% (n = 12/65) focused on factors-related review studies on the smart grid and about 15% (n = 10/65) focused on factors related to the experimental study. The remaining 9% (n = 6/65) concentrated on fields related to the challenges and benefits of the study. The significance of predictive maintenance has been developing over time in connection with Industry 4.0 revolution. The paper’s fundamental commitment is the outline and overview of faults in the smart grid such as fault location and detection. Therefore, advanced methods of applying Artificial Intelligence (AI) techniques can enhance and improve the reliability and resilience of smart grid systems. For future direction, we aim to supply a deep understanding of Smart meters to detect or monitor faults in the smart grid as it is the primary IoT sensor in an AMI.

scholarly journals Optimal Techno-Economic Planning of a Smart Parking Lot—Combined Heat, Hydrogen, and Power (SPL-CHHP)-Based Microgrid in the Active Distribution Network

2021 ◽  
Vol 11 (17) ◽  
pp. 8043
Author(s):  
Hamed Hosseinnia ◽  
Behnam Mohammadi-Ivatloo ◽  
Mousa Mohammadpourfard
Keyword(s):  
Distribution System ◽  
Power Flow ◽  
Voltage Drop ◽  
Smart Meters ◽  
Active Distribution System ◽  
Parking Lot ◽  
Order Preference ◽  
Smart Parking ◽  
Low Efficiency ◽  
Demand Response Programs

By installing distributed generation (DG) sources in a distribution system, there is a change from the inactive state, accompanied by one-way power flow, to the active state, with the possibility of bilateral power flow. Authorities involved in the electricity industry manage the consumption side by bringing in particular programs called demand response programs. To implement these programs, it is crucial to create infrastructure, including the installation of smart measuring units in the consumption sector. In this paper, we investigate the optimal design of smart meters and combined hydrogen, heat, and power in the active distribution system to provide two functions aimed at reducing voltage drop and minimizing the total planning costs by taking different scenarios into account. In the combined hydrogen, heat, and power (CHHP)-based DGs, due to the low efficiency of the electrolyzer, its power is supplied by a smart parking lot (including wind turbines, photovoltaic systems, and batteries). To model the unit’s uncertainties, a long short-time memory (LSTM) model is employed. Utilizing the technique for order preference by similarity to ideal solution (TOPSIS), a state that enhances both functions is acquired from different scenarios. All of the simulations are carried out in two 33-bus systems.

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