Multi Variation Reactive Power Management Using Artificial Neural Network for Loss Prediction in Power System

Authors

  • Nur Asyikin Abd Jamel, Ismail Musirin, Norziana Aminuddin, Siti Rafidah Abdul Rahim, Nor Azwan Mohamed Kamari, Muhammad Murtadha Othman, A. V. Senthil Kumar

Abstract

Reactive power management plays vital roles in power transmission system as it affects the power system status. Variations in load in a power system network can possibly lead to voltage instability condition or voltage collapse phenomena. This can become worse, especially when the relevant power system operators do not know early information on the system status. Thus, a reliable technique should be utilized or implemented so that the current or forecasted status of the system can be known before any undesired event is experienced. This paper presents, “Multi Variation Reactive Power Management Using Artificial Neural Network for Loss Prediction in Power System”. In this study, the various models of load bus were designed in order to analyze and compare how the different number of input features, can affect the regression results of ANN. The comparison of the performance results of regression is conducted in terms of Mean-Squared Error (MSE) for all the models designed.

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Published

2022-05-30

How to Cite

Siti Rafidah Abdul Rahim, Nor Azwan Mohamed Kamari, Muhammad Murtadha Othman, A. V. Senthil Kumar, N. A. A. J. I. M. N. A. (2022). Multi Variation Reactive Power Management Using Artificial Neural Network for Loss Prediction in Power System. Mathematical Statistician and Engineering Applications, 71(3), 123–138. Retrieved from https://philstat.org.ph/index.php/MSEA/article/view/111

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Articles