This paper proposes a fault-location method based on smart feeder meters with voltage sag monitoring capability. The main idea is to explore voltage measurements from monitors placed in different ...buses of distribution systems to estimate the fault location. The estimation is achieved by relating the voltage deviation measured by each meter to the fault current calculated based on the bus impedance matrix, considering the fault in different points. In order to improve the method accuracy, the loads are represented by constant impedance models and included into the bus impedance matrix. The performance of the proposed method is demonstrated by using a real distribution system. Sensitivity studies results show that the method is robust since it has good performance for different values of fault resistance, quantity, and location of the smart meters.
Faults in distribution networks can result in severe transients, equipment failure, and power outages. The quick and accurate detection of the faulty section enables the operator to avoid prolonged ...power outages and economic losses by quickly retrieving the network. However, the occurrence of diverse fault types with various resistances and locations and the highly non-linear nature of distribution networks make fault section detection challenging for numerous conventional techniques. This study presents a cutting-edge deep learning-based algorithm to distinguish fault sections in distribution networks to address these issues. The proposed gated recurrent unit model utilizes only two samples of the angle between the voltage and current on either side of the feeders, which record by smart feeder meters, to detect faulty sections in real time. When a network fault occurs, the protection relays trigger the trip command for the breakers. Immediately, the angle data are obtained from all smart feeder meters of the network, which comprises a pre-fault sample and a post-fault sample. The data are then employed as an input to the pre-trained gated recurrent unit model to determine the faulted line. The performance of this novel algorithm was validated through simulations of various fault types in the IEEE-33 bus system. The model recognizes the faulty section with competitive performance in terms of accuracy.
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.
Since feeders have complicated laterals connected with unbalanced loads, the location of a ground fault is a challenge in radial distribution networks. Furthermore, lower short-circuit current due to ...the high value of fault resistance, which is common in the distribution network, will make it even more challenging to identify the fault location. Taking advantage of increasing number of intelligent electronic devices installed in the modern distribution network, the monitoring, and automation of distribution systems can be improved by smart feeder meters. On the basis of the voltage information from the downstream sub-laterals, a novel fault location method involving distributed voltage measurement is proposed in this study. The first step in the proposed method is to identify the fault lateral in the main lateral. In a zero-sequence components network, the position of nodes in the main lateral is iterated to judge if the calculated voltage at the end matches the measured one by a smart feeder meter. The second step is to identify the fault section accurately by combining the voltage information from main lateral or other sub-laterals. Finally, a precise fault location can be attained via an iteration search in the fault section. Two distribution test systems simulated in power systems computer-aided design/electro-magnetic transient design and control with 34-node and 134-node have been employed to evaluate the effectiveness of the proposed algorithm under various ground fault scenarios. The simulation results show that the proposed method is robust since it offered a good performance for ground faults identification with low and high values of impedance occurring at different locations. Furthermore, it is also suitable for the system with distributed generations and dynamic loads.
The increasing of distributed generators and high demand of customer service quality of recent years keep challenging the design and operation of electric power distribution systems. The future smart ...distribution grid is envisioned to be a large complex cyber-physical distribution system (CPDS), where physical grid components are monitored and controlled based on the interactions on the cyber space. As sensors and controllers, smart feeder remote terminal units (FRTUs) transfer necessary data to the control centre for situational awareness, and receive orders from the control centre for dynamic controlling. This study introduces an analytical FRTU deployment approach for the reliability improvement of integrated CPDSs. The FRTU deployment problem is modelled as a mixed-integer non-linear programming problem, which aims to minimise the total cost with the reliability index of average service available index as the constraint. Two kinds of distribution feeders (overhead and underground) are considered. The total cost includes the life cycle cost of FRTUs in addition to customer interruption cost. The proposed model can be solved by large-scale commercial solvers in an efficient manner. Test results of the RBTS-BUS4 distribution system and a China Southern Power Grid 62-bus distribution system validate the accuracy and effectiveness of the approach. Comparison with the genetic algorithm also shows its great efficiency.
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