Transient Stability Evaluation of Benin Sub-Regional 330kV Grid Network Using Fletcher-Reeves Back Propagation Algorithm

Chizindu Stanley Esobinenwu


Transient stability of Benin Sub-Region 330kV power system was examined using an artificial intelligent algorithm known as Fletcher-Reeves back propagation. Transient stability in recent times has become a huge challenge to power system engineers and operator. The system was first analyzed using modified Euler technique to compute the swing equation and plot the swing curve. Artificial neural network technique shows greater accuracy and speed in solving complex solution than the empirical method. Based on the result obtained, the maximum power outputs for pre-fault, during fault and post-fault condition are [2.2105, 0.6549, and 1.5672] respectively. Similarly, the critical clearing angle and time of the circuit breaker are [77.22 deg, 0.2 seconds] for the empirical method and [77.22 deg, 0.22 seconds] ANN methods. During ANN training the best validation performance is 0.00018754 at epoch 5, while the regression plot is 0.9993. It indicates how much minimized errors occurred during the training and the network procedure of training, testing and validation is significantly acceptable. Transient stability was improved with the use of circuit breaker.

Key words: Critical clearing time, Critical Clearing angle, Modified Euler, Circuit breaker, ANN

Full Text:



  • There are currently no refbacks.

Copyright (c) 2021 Chizindu Stanley Esobinenwu

Copyright CC BY © European Modern Studies Journal 2017-2021   ISSN 2522-9400

Лицензия Creative Commons

To make sure that you can receive messages from us, please add the '' domain to your e-mail 'safe list'. If you do not receive e-mail in your 'inbox', check your 'bulk mail' or 'junk mail' folders.