Enhancing Power Quality and Harmonic Analysis for Constant Power Supply Using ANN Based Satic Var Compensator (SVC)
DOI:
https://doi.org/10.54536/ajmri.v4i3.4819Keywords:
Analysis, ANN, Based, COMPENSATOR, svc, Constant, Enhancing, Harmonic, Power, Quality, SATIC VAR, SupplyAbstract
The consistent power failure that has jeopardized business activities in the country are anchored by Harmonic Distortion, Voltage Sag/Surge, Overloading of Transmission Lines, Unbalanced Loads, Electrical Noise (EMI/RFI), Capacitor Switching Transients, Frequency Variations, Power Factor Issues, Poor Grounding and Short Circuits and Electrical Faults. The constant power failure observed was overcome by introducing enhancing power quality and harmonic analysis for constant power supply using ANN BASED SATIC VAR COMPENSATOR (SVC). To achieve this, it was done in this approach, characterizing and establishing the causes of power failure in power quality and harmonic analysis for constant power supply, training ANN in the established causes of power failure in power quality and harmonic analysis for an enhanced power supply. Developing a SIMULINK model for SVC, developing an algorithm that will implement the process, designing a SIMULINK model for enhancing power quality and harmonic analysis for constant power supply using ANN based SATIC VAR COMPENSATOR (svc) validating and justifying percentage improvement in the reduction of causes of power failure with and without power failure. The results obtained are the conventional harmonic distortion that caused power failure in power quality and harmonic analysis for constant power supply was 25%. On the other hand, when an ANN BASED SATIC VAR COMPENSATOR was introduced in the system, it drastically reduced to21.53%., the conventional Voltage Sag/Surge that caused power failure in power quality and harmonic analysis for constant power supply was 20%. Meanwhile, when an ANN BASED SATIC VAR COMPENSATOR was inculcated in the system, it decisively reduced Voltage Sag/Surge that caused power failure to17.23%. However, the percentage improvement in the reduction of Voltage Sag/Surge that caused power failure was 2.77% and the conventional power factor issues that caused power failure in power quality and harmonic analysis for constant power supply was5%. On the other hand, when an ANN BASED SATIC VAR COMPENSATOR was introduced in the system, it automatically reduced power factor issues that caused power failure to 4.3%. Finally, the percentage improvement in the enhancement of power quality and harmonic analysis for constant power supply was 0.7%
Downloads
References
Bollen, M. H. (2003). Understanding power quality problems: Voltage sags and interruptions. IEEE Press.
Chatterjee, A., Ghosh, A., & Ledwich, G. (2013). Power quality enhancement using custom power devices. Springer Science & Business Media.
Ghosh, A., & Ledwich, G. (2002). Power quality enhancement using custom power devices. Kluwer Academic Publishers.
Haykin, S. (1999). Neural networks: A comprehensive foundation (2nd ed.). Prentice Hall.
Hingorani, N. G., & Gyugyi, L. (2000). Understanding FACTS: Concepts and technology of flexible AC transmission systems. IEEE Press.
Miller, T. J. E. (1982). Reactive power control in electric systems. Wiley-Interscience.
Nagrath, I. J., & Kothari, D. P. (2010). Power system engineering (2nd ed.). Tata McGraw-Hill Education.
Patel, R., & Agnihotri, G. (2013). Artificial neural network based static var compensator for reactive power compensation. International Journal of Electrical Power & Energy Systems, 45(1), 70-77.
Salama, M. M., & Chikhani, A. Y. (1999). A simplified network approach for harmonic distortion assessment. IEEE Transactions on Power Delivery, 14(2), 507-511.
Singh, B. (2015). Application of artificial neural networks in power systems. Proceedings of the Institution of Mechanical Engineers, Part A: Journal of Power and Energy, 229(3), 345-353.
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2025 Chukwuagu M. Ifeanyi, Ogbu Gregory, Chukwu Linus
This work is licensed under a Creative Commons Attribution 4.0 International License.
