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In the current times, penetration of distributed generation is increasing, which impacts coordination of relays in such a way that it requires change in the relays' settings. Inverse-time protection schemes based on only overcurrent sometimes fail to protect the distribution network with distributed generators (DGs), especially when the fault current is near or below the pickup current of the relay...
Various protection-factors arise due to the introduction of distributed generation, which can create problems in protecting the distribution system with distributed generators (DGs). Therefore, it is necessary to find out and analyze these protection-factors. This paper simulated a 25 KV sample distribution system in order to analyze and discuss these protection-factors, and also find out some new...
This paper presents an application of ANN based Pattern Recognition Technique for the differential protection of a two winding three-phase power transformer. It proposes a variation in feed forward back propagation neural network (FFBPNN) model, which makes the discrimination among normal, magnetizing inrush, over-excitation and internal fault currents efficiently. Fault conditions of the transformer...
In this paper an accurate approach is proposed for classifying and locating faults in series compensated (SC) network utilizing discrete wavelet transform (DWT) and artificial neural network (ANN). In the first phase of the proposed approach, fault current samples acquired from simulation were decomposed using Db5 mother wavelet. Faults signatures are captured in terms of standard deviation of detail...
Distributed Generators (DGs) are gaining popularity due to power industry deregulation and unpredictable growing loads. For every future increment in DG capacity, the relay settings need to be changed. This paper investigates how varying capacity of DG at a bus affects relay coordination. It proposes a new formulation of optimal relay coordination in the presence of variable size DG connected with...
This paper presents a novel approach based on combined wavelet transform and artificial intelligence technique for estimating fault location in a series compensated transmission line. In proposed approach the samples of faulty current signals generated from simulink model are used for fault analysis. Wavelet transform is utilised for the purpose of feature extraction from the faulty current signals...
A precise and advanced approach based on combined wavelet transform and artificial intelligence technique for analysis of the type fault and the faulty phase in a series compensated transmission line is presented in this paper. In proposed algorithm, samples of fault current signals are used for fault diagnosis and wavelets transform (WT) applied for feature extraction from the signals. The faulty...
This paper presents a bibliographical survey and review of research and development in the field of impact of series FACTS (Flexible alternating current transmission system) devices on distance protection of transmission line. FACTS controllers are capable of controlling power flows, reactive power, damping of power system oscillations, transmission voltage and enhancing the usable capacity of existing...
This paper presents survey and review of research and development in the field of faults detection, classification and their location that occurs in the transmission network. Transmission lines are integral part of the power system network and its main aim is to transmit the generated power to the consumer with least interruption. With an ever-increasing demand of electric power day by day because...
The proposed work presents the use of Artificial Neural Network (ANN) as a pattern classifier for differential protection of power transformer, which makes the discrimination among normal, magnetizing inrush, over-excitation and internal fault currents. This scheme has been realized through two separate customized Parallel-Hidden Layered ANN architectures which work in Master-slave mode. The Back...
This paper presents the use of ANN as a pattern classifier for differential protection of power transformer, which makes the discrimination among normal, magnetizing inrush, over-excitation, external fault and internal fault currents. This scheme has been realized through two ANN architectures, which are designed and trained using feed forward back propagation algorithm with experimental data and...
This paper discusses the application of MFNN for the protection of turbogenerator against internal faults in any winding of the stator. The network has been used as pattern classifier for detection, identification and classification of the internal faults. The full cycle data of simulated fault currents in the phases and their parallel paths have been used for training and testing of proposed neural...
The consideration of reliability as an “afterthought” in product development has proven to be “terribly expensive” and “ineffective procedure”. The right time to start considering reliability is the time when system and design concepts are being formulated. This leads a system designer to first choose an appropriate reliability assessment model to evaluate his system, followed by the prognosis of...
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