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Research Article |

Artificial Neural Network based FACTS in a Contingency Situation

Author(s): Rachakonda Raghavendra*, Dr. N.C. Kotaiah and Dr. K. Radha Rani

Published In : International Journal of Electrical and Electronics Research (IJEER)        Volume 12, Issue 1

Publisher : FOREX Publication

Published : 15 January 2024

e-ISSN : 2347-470X

Page(s) : 8-11

DOI: https://doi.org/10.37391/IJEER.120102

Abstract

The two biggest issues facing today's energy management systems are the ongoing monitoring of online voltage stability and the improved loadability of the transmission lines for the current electrical power system. As a result, it is highly difficult and time-consuming to assess online voltage stability under diverse loading conditions. This study describes a practical voltage stability monitoring system that automates online voltage monitoring and alerts the operator before voltage drops by computing line voltage stability indices using an ANN. This study compares evaluations of system voltage stability and loadability at the load with FACTS devices. The results suggest increase in system loadability while ensuring the security of power system operation.

Keywords: Line voltage stability indices, FACTS Devices, ANN, Power system security .




Rachakonda Raghavendra*, Department of EEE, R.V.R & J.C. College of Engineering, Chowdavaram, Guntur, Andhra Pradesh-522019; Email: raghavendra.r.v5121@gmail.com

Dr. N.C. Kotaiah, Department of EEE, R.V.R & J.C. College of Engineering, Chowdavaram, Guntur, Andhra Pradesh-522019; Email: nellurikotaiah@gmail.com

Dr. K. Radha Rani, Department of EEE, R.V.R & J.C. College of Engineering, Chowdavaram, Guntur, Andhra Pradesh-522019; Email: korrapatiradharani@gmail.com

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Rachakonda Raghavendra, Dr. N.C. Kotaiah and Dr. K. Radha Rani (2024), Artificial Neural Network based FACTS in a Contingency Situation. IJEER 12(1), 8-11. DOI: 10.37391/IJEER.120102.