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Research Article |

L-M Based ANN for Predicting the Location of DG under Contingency Condition

Author(s): D. Uma Maheswara Rao*, Dr. G. Sambasiva Rao, and Dr. K. Swarnasri

Published In : International Journal of Electrical and Electronics Research (IJEER)        Volume 11, Issue 4

Publisher : FOREX Publication

Published : 24 December 2023

e-ISSN : 2347-470X

Page(s) : 1204-1208

DOI: https://doi.org/10.37391/ijeer.110442

Abstract

The continuing monitoring of online voltage stability and the increased loadability of the transmission lines for the existing electrical power system are the two major challenges that today's energy management systems must deal with. As a result, evaluating online voltage stability under various loading situations is extremely challenging and time-consuming. The line voltage stability indices using an Artificial Neural Network (ANN), the system describes online voltage monitoring and warns the operator before voltage dips. The simulation's findings show that the proposed system may boost system loadability while also lowering the cost of installing an electrical power system and guaranteeing the security of power system operation.

Keywords: Line voltage stability indices, Distributed Generation, Artificial Neural Network, Power system security.




D. Uma Maheswara Rao*, Department of EEE, R.V.R & J.C. College of Engineering, Chowdavaram, Guntur, Andhra Pradesh, India; Email: umamaheswararaodasari22@gmail.com

Dr. G. Sambasiva Rao, Department of EEE, R.V.R & J.C. College of Engineering, Chowdavaram, Guntur, Andhra Pradesh, India; Email: gssr@rvrjc.ac.in

Dr. K. Swarnasri, Department of EEE, R.V.R & J.C. College of Engineering, Chowdavaram, Guntur, Andhra Pradesh, India; Email: swarnasrik@gmail.com

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D. Uma Maheswara Rao, Dr. G. Sambasiva Rao and Dr. K. Swarnasri (2023), L-M Based ANN for Predicting the Location of DG under Contingency Condition. IJEER 11(4), 1204-1208. DOI: 10.37391/ijeer.110442.