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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...
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...
In this paper dynamic ATC has been calculated using energy function based potential energy boundary surface (PEBS) method. For the effective use of power system under the deregulated environment, it is important to make a fast and accurate evaluation of the maximum available transfer capability (ATC). Transient stability assessment by time domain simulation method is a time consuming process. A novel...
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...
This paper presents auto-reclosing algorithms with reference to power system stability based on MAS (multi agent system) using JADE (Java agent development framework). Autoreclosure provides a means of improving power transmitting ability and system stability. Also it demonstrates an auto-reclosing algorithm (considering power system stability) used for the purposes of restoring the power system after...
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