Voltage stability assessment using a new FSQV method and artificial neural networks

Voltage stability has been of the major concern in power system operation. To prevent these problems, technical staff evaluates frequently the distance of the operation state to the voltage collapse point. This distance normally is calculated with power flow equations. This classic technique is very slow for electric power systems with large dimension. In abnormal exploration situations it may introduce serious limitation in the voltage stability analysis process. So, the application of a fast and reliable evaluation technique is very important to diminish the evaluation time. This paper presents a study of the application of artificial neural network (ANN) to the evaluation of this distance to the voltage collapse point. To detection the point of collapse the new method FSQV was used