Fast assessment of voltage stability margin of a power system

Abstract EN

In today’s world of rapid growth there is an increase of demand for a reliable and stable power supply.

Power utilities are pressured to cater the rising demand with the existing system.

Thus, monitoring the voltage stability of the system has become crucial.

Conventional methods of performing continuous load flow and stability studies are highly time consuming and infeasible for on-line application.

It necessitates a requirement of a on line tool to calculate the loadability margin under normal condition as well as under contingency cases.

In this paper the voltage stability margin of a power system with and without the FACTS devices under different loading conditions using Support Vector Machine (SVM are determined.

SVM is a powerful and promising data classification and function estimation tool.

In SVM the input vector in the form of real, reactive power load, voltage magnitude, phase angle and the target/output vector is in the form of lambda (loading margin) are considered.

New England 39 bus test system has been used to verify the effectiveness of the proposed SVM method and the performance are compared with Artificial Neural Network (ANN) and Adaptive Neural Fuzzy Inference System (ANFIS).