scholarly journals A Survey of Fault Prediction and Location Methods in Electrical Energy Distribution Networks

Measurement ◽  
2021 ◽  
pp. 109947
Author(s):  
Rahman Dashti ◽  
Mohammad Daisy ◽  
Hamid Mirshekali ◽  
Hamid Reza Shaker ◽  
Mahmood Hosseini Aliabadi
Energies ◽  
2019 ◽  
Vol 12 (22) ◽  
pp. 4234 ◽  
Author(s):  
Zhou ◽  
Yang ◽  
Yang ◽  
Yang ◽  
Littler ◽  
...  

Probabilistic Load Flow (PLF) calculations are important tools for analysis of the steady-state operation of electrical energy networks, especially for electrical energy distribution networks with large-scale distributed generators (DGs) and electric vehicle (EV) integration. Traditional PLF has used the Cumulant Method (CM) and Latin Hypercube Sampling (LHS) method. However, traditional CM requires that each input variable be independent of one another, and the Cholesky decomposition adopted by the traditional LHS has limitations in that it is only applicable for positive definite matrices. To solve these problems, taking into account the Q-MCS theory of LHS, this paper proposes a CM PLF algorithm based on improved LHS (ILHS-CM). The cumulants of the input variables are obtained based on sampling results. The probability distribution of the output variables is obtained according to the Gram-Charlier series expansion. Moreover, DGs, such as wind turbines, photovoltaic (PV) arrays, and EVs integrated into the electrical energy distribution networks are comprehensively considered, including correlation analysis and dynamic load flow analysis for EV-coordinated charging. Four scenarios are analyzed based on the IEEE-30 node network, including with/without DGs and EVs, error analysis and performance evaluation of the proposed algorithm, correlation analysis of DGs and EVs, and dynamic load flow analysis with EV integration. The results presented in this paper demonstrate the effectiveness, accuracy, and practicability of the proposed algorithm.


Measurement ◽  
2020 ◽  
Vol 151 ◽  
pp. 107270 ◽  
Author(s):  
Ehsan Gord ◽  
Rahman Dashti ◽  
Mojtaba Najafi ◽  
Athila Quaresma Santos ◽  
Hamid Reza Shaker

Energies ◽  
2019 ◽  
Vol 12 (6) ◽  
pp. 1145 ◽  
Author(s):  
Ehsan Gord ◽  
Rahman Dashti ◽  
Mojtaba Najafi ◽  
Hamid Reza Shaker

: Fault location in electrical energy distribution networks is an important task, as faults in distribution grids are among the main causes of electricity supply disruption. Fault location in the distribution systems, however, is a challenging task because of the topology of the distribution networks, as well as the main and side branches. Therefore, it is necessary to address these challenges through an intelligent approach to fault location. In this paper, fault location in electric energy distribution networks is addressed considering the changes in fault distance and fault resistance in the presence of different fault types. A new method for fault location is developed for conditions where the minimum information is available and only information at the beginning of the feeder is used. This facilitates wide adoption of the technique as it does not require significant investments in instrumentation and measurement. The proposed intelligent method is based on the impedance and transient state estimation. This technique employs a specific impedance analysis for determining possible fault locations considering the unbalanced performance of distribution systems, distances, and different fault resistances. To determine the real faulty section, real fault frequency component analysis and the simulated faults at possible fault locations are used. At this stage of the process, it is possible to eliminate multiple estimations with the help of comparison and identification of the similarities. Therefore, a real faulty section is determined. It is observed that some conditions of electric energy distribution networks affect the accuracy and performance of the proposed method significantly; thus, a detailed investigation is conducted to neutralize these conditions. Simulation results and calculations based on MATLAB along with a practical test of the proposed method in power network simulator confirm a satisfactory performance.


Energies ◽  
2021 ◽  
Vol 14 (11) ◽  
pp. 3242
Author(s):  
Hamid Mirshekali ◽  
Rahman Dashti ◽  
Karsten Handrup ◽  
Hamid Reza Shaker

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.


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