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Empirical mode decomposition (EMD) approximate entropy and least squares support vector machines (LS-SVM) with bacterial colony chemotaxis (BCC) were used to detect the fault signals in single phase earth, and then distinguish the transient faults and permanent faults on transmission lines. After faults occur, different kinds of faults have different complex levels of voltage transient signals which...
A new technique for fast detection of power islands in a distribution network, which uses transient signals generated during the islanding event is investigated. Performance comparison of several pattern recognition techniques in classifying the transient generating events as islanding or non-islanding is presented. Features for the classifiers are extracted using the Discrete Wavelet Transform of...
This paper presents a support vector regression machine (SVRM) to predict the energy margin (EM) of power systems subjected to severe disturbances. The nonlinear relationship between the pre-fault, during-fault and post-fault power systems parameters and the degree of stability of the system under post-fault state is captured by the SVRM trained offline. Significant generators are selected by feature...
In this paper, application of SVM to classify disturbances in power quality is discussed. Power system transient can pose a serious threat to the reliability of power system apparatus and sensitive loads. There are numerous causes of power system transient namely short circuits, capacitor bank switching, switching of large inductive loads that include motors and transformers as well as lightning....
The paper presents a comparative study of three different 3D-SVM techniques for the control of flying-capacitor multi-level inverters under both balanced and unbalanced operating conditions. Simulation results show that Direct 3D-SVM is the most efficient in computational effort. Application of this scheme to a three-level FCMI is simulated using the Alternative Transients Program (ATP). Output performance...
This paper presents transient stability assessment of a large practical power system using two artificial neural network techniques which are the probabilistic neural network (PNN) and the least squares support vector machine (LS-SVM). The large power system is divided into five smaller areas depending on the coherency of the areas when subjected to disturbances. This is to reduce the number of data...
The internal and external overvoltage in distribution networks are the main reasons of accidents. Based on overvoltage data in distribution network recorded by overvoltage on-line monitoring system, this paper analyzes the characteristics of zero sequence voltage waveform. The maximum amplitude and RMS value of zero sequence voltage, the minimum RMS of low frequency component of three phase voltage...
In the electricity power markets, available transfer capability (ATC) is an important index. Conventional ATC calculation takes much time because it repeats stability analysis many times. This paper proposes a neural network based technique applied to the ATC screening. Using this method no stability analysis is necessary at least in its first stage, and approximate ATC can be evaluated at high speed...
In order to improve the ability of transformer differential protection in the inrush identification, this paper proposes an algorithm based on the magnetic transient for internal fault simulation of single-phase transformer. A new fitting method for the hysteresis loop of transformer based on support vector machine is set forth, which is original optimization of the hysteresis loop test data regression...
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