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In this paper an improved impedance based fault location method is proposed. In this method, online fault locating is performed using voltage and current information at the beginning of the feeder. Determining precise fault location in a short time increases reliability and efficiency of the system. The proposed method utilizes information about ma...
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... Coefficients A and B in Eq. (4) are as follows (more information is available in [13]): ...
... As mentioned before, in order to test the proposed method, an 11-node feeder is selected according to IEEE standard [13]. A single-line diagram of this feeder along with different sections is designed and presented in Fig. 5. ...
Fault location in medium voltage (MV) electricity distribution networks has always been a challenge, in particular, for the last few years. The existence of information only at the beginning of the feeder and the complexity of the widespread and scattered distribution networks make fault location of MV distribution networks a difficult task. The performance of most of the existing methods for fault location is compromised when dealing with today’s MV distribution grid. In this paper, a new fault location method is introduced for MV distribution networks, using transient frequency analysis. The transient caused by fault in the network is analyzed. The main idea of fault location algorithm is to determine and measure the Analysis Index. The location of fault is identified through the relationship between the proposed Analysis Index and different sections in the distribution feeder. In order to evaluate and analyze the proposed method, at first a standard IEEE 11-node network is simulated and tested in MATLAB software, then the same procedure is repeated for a real 69-node network. The results confirm a good performance.
... In the method presented in [11], only fault distance estimation is considered and a sample network with 11 nodes and p line mode are used. In [12], a 13-node sample network with DG resources, according to the IEEE standard, has been considered for fault location. In [12], the network is first divided into two sections: 1) faults before the section which has DGs and 2) faults after section which has DGs. ...
... In [12], a 13-node sample network with DG resources, according to the IEEE standard, has been considered for fault location. In [12], the network is first divided into two sections: 1) faults before the section which has DGs and 2) faults after section which has DGs. Then, two separate methods are considered where each one uses a separate formula to determine fault location. ...
... The load on each node is calculated based on the method proposed by [12]. In addition, pre-fault current values are used to define the matrix of node impedance for the distributed feeder, where each section is modeled using a distributed line model. ...
Distributed generation resources are becoming more popular in electric energy distribution networks. As more Distributed generation are integrated into the grid, the system performance is challenged by issues such as manifold power injection to the network or nonlinear behavior when a fault occurs. To address this, fault location in electric energy distribution networks in the presence of distributed generation needs particular attention. This is important to reduce the loss of generated energy, reduce interruptions time, increase the reliability of the network and consequently improve the security of electricity supply. In this paper, a novel fault location method is presented applied to distributed networks with distributed generation. The proposed method is a hybrid two-step method which identifies accurate fault location using information stored in the network at pre- and post-fault time. The proposed method employs voltage and current information at the beginning of the feeder to estimate fault distance in the first step. The estimated distance will be associated with several similar sections considering the topology of the distributed networks. In the second step, the proposed method determines accurate fault location through transient analysis based on the frequency component. In this step, the exact fault location is identified. In order to investigate its performance, a standard IEEE-11 network is simulated in MATLAB. Furthermore, experiments are carried out in a network power simulator, showing good results.
... As the types of fault are not considered, this method is not a complete and powerful one. In reference [11] a method was presented for fault location in radial distribution systems in presence of distributed generation units. It locates fault based on voltage and current samples of feeder. ...
... In this part, the location of the fault is determined using the presented impedance method in the work of [11]. In this method, the distributed-parameter line model is used to improve the accuracy of the impedance-based fault location algorithm. ...
... For better understanding, Figure 5 is presented. Equations (15)-(17) are used for updating the voltage and current [11]. ...
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.
In this paper, a new algorithm is presented for assessing the operation of distribution systems using distributed generation resources. The algorithm is proposed based on Probabilistic measures of presence or absence of distributed generation resource in the distribution system. For dynamics of system, Monte Carlo simulation is used with consideration of network restrictions. Random parameters of studied system consist of uncertainty of location, amount of generated power and off or on sections of distributed generation units. Parameters of this algorithm consist of Newton-Raphson load flow equations where Monte Carlo simulation is exploited to analyze and study the all of the possible states of system. The proposed algorithm is used to determine electric current per hour in a normal distribution system with loading distributed generators and explains some normal load curves in various nodes. Also the results are presentable for demonstration of system operation in case of random distributed generators. The proposed algorithm has been tested in a standard 30-nodes IEEE network and the obtained results verify and confirm the validation of proposed method.
