Indian Journal of Science and Technology
DOI: 10.17485/ijst/2016/v9i36/101967
Year: 2016, Volume: 9, Issue: 38, Pages: 1-5
Original Article
K. Selvakumar* , C. S. Boopathi and M. Sri Harsha
Department of EEE, SRM University, Kattankulathur, Chennai - 603203, Tamil Nadu, India; [email protected]
[email protected]
[email protected]
*Author for correspondence
Selvakumar
Department of EEE
Email:[email protected]
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.
Keywords: Artificial Neural Networks (ANN), Cascade Architecture (CC), Levenberg-Marquardt (LM), Stability Index, Voltage Stability
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