Voltage Stability Thesis

Voltage Stability Thesis-33
Voltage stability margin is defined as the distance with respect to the bifurcation parameter, from the current operating point to bifurcations point i.e. In this work this voltage stability margin is referred to as the loadability margin and used as performance index for voltage stability analysis.Conventional power flow fails to give solution at the point of collapse, because of the power flow Jacobian becoming singular at the collapse point.The results obtained from the indices were compared with each other,and the conclusions on the performance of the indices were discussed.

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It is generated from the basic power flow equations and/or energy functions.

The research is very timely and current and would be a substantial contribution to the present body of knowledge in programming and voltage stability assessment.

The second one was to apply Radial Basis Function Neural Network and Multi-Layer Perceptron Neural Network for all the indices in order to improve the indices performance in terms of computational time and accuracy.

While the third one was touse feature selection on the input features of artificial neural network to decide the most important features.

It is appeared that difference between the prediction computed by ANNs, and conventional methods of voltage stability indices tests is considered almost negligible.

The analysis of features sensitivity of the ANN has been investigated and found out that the selection of features affect the performance of the ANN.

The methods developed in this research would be faster than presently available voltage stability indices.

In this study, five voltage stability indices previously developed, namely, Fast Voltage Stability Index (FVSI), On Line Voltage Stability Index (LVSI), Line Stability Index (Lmn), Line Stability Factor (LQP), and Power Transfer Stability Index (PTSI) were utilized by using MATLAB software.

In this thesis voltage stability assessment is done for the power systems with SVC as well as for the systems with STATCOM.

The steady state models of SVC and STATCOM are presented.

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