Voltage Stability Assessment using Artificial Neural Networks

Abstract

Objectives: To calculate the load flow analysis by using Artificial Neural Networks (ANN) and the Cascade Architecture (CC) with Levenberg-Marquardt (LM) algorithm is used for this proposed system. Methods/Statistical Analysis: Many conventional methods such as Newton-Raphson method, Gauss-Seidel method, AC load flow analysis etc., are used to estimate the load flow analysis of a power system. The major backdrops in using these methods are, using complex non-linear equations, iterative methods and time consuming. To overcome these problems, this paper discusses using Artificial Neural Networks (ANN) which reduces the time consumption in calculating load flow analysis. Findings: In the real-time planning and operation of a power system the major consideration is voltage stability assessment. The voltage instability in a power system will lead to a blackout condition. The continuous increase in load demand, changes in system conditions causes voltage collapse. So the on-line monitoring of voltage stability is a necessary condition. Application/Improvements: The output of the load flow analysis is used to calculate the Index that is used to maintain the system in stable limits.