Authors : Sunday Oluwafemi Oladoye; Agbo Ogloji James; Otugene Victor Bamigwojo; Onuh Matthew Ijiga

Volume/Issue : Volume 11 - 2026, Issue 1 - January

Google Scholar : https://tinyurl.com/2zazc968

Scribd : https://tinyurl.com/5euusbeb

DOI : https://doi.org/10.38124/ijisrt/26jan890

Note : A published paper may take 4-5 working days from the publication date to appear in PlumX Metrics, Semantic Scholar, and ResearchGate.

Abstract : The increasing penetration of non-linear and power-electronic-based loads in industrial distribution systems has led to a growing prevalence of power quality (PQ) disturbances such as voltage sags, harmonics, transients, and mixed events, which adversely affect equipment reliability and operational efficiency. Conventional PQ assessment techniques based on time-domain indices and Fourier analysis are limited in their ability to accurately characterize non-stationary and transient disturbances commonly observed in industrial environments. This study presents an advanced PQ assessment framework that integrates wavelet-based signal processing with machine learning (ML) classification to enable automated, high-resolution disturbance analysis. Multi-level wavelet decomposition is employed to extract discriminative time–frequency features, including energy distribution, statistical measures, and entropy, which effectively capture the intrinsic characteristics of diverse PQ events. These features are subsequently used to train and evaluate supervised ML classifiers, including support vector machines, random forest models, artificial neural networks, and convolutional neural networks. The proposed framework is validated using representative industrial distribution system data under varying operating conditions, including noisy and mixed PQ scenarios. Comparative results demonstrate that the wavelet–ML approach significantly outperforms traditional RMS-, FFT-, and STFT-based methods in terms of classification accuracy and robustness. The findings highlight the suitability of the proposed framework for real-time industrial PQ monitoring, predictive maintenance, and intelligent decision support, contributing to enhanced reliability and resilience of modern industrial power systems.

Keywords : Power Quality (PQ); Wavelet Transform; Machine Learning Classification; Industrial Distribution Systems; Time– Frequency Analysis; Non-Stationary Disturbances.

References :

1. Arrillaga, J., Watson, N. R., & Chen, S. (2000). Power system quality assessment. John Wiley & Sons.
2. Bollen, M. H. J. (2000). Understanding power quality problems: Voltage sags and interruptions. IEEE Press.
3. Dash, P. K., Panigrahi, B. K., & Panda, G. (2003). Power quality analysis using S-transform. IEEE Transactions on Power Delivery, 18(2), 406–411. https://doi.org/10.1109/TPWRD.2003.809624
4. Dugan, R. C., McGranaghan, M. F., Santoso, S., & Beaty, H. W. (2012). Electrical power systems quality (3rd ed.). McGraw-Hill.
5. IEEE Standards Association. (2019). IEEE recommended practice for monitoring electric power quality (IEEE Std 1159-2019). IEEE.
6. Mallat, S. (1999). A wavelet tour of signal processing (2nd ed.). Academic Press.
7. Ribeiro, M. V., Duque, C. A., Silveira, P. M., & Cerqueira, A. S. (2014). Power quality disturbance detection, classification, and location using signal processing techniques. IEEE Signal Processing Magazine, 31(6), 24–35. https://doi.org/10.1109/MSP.2014.2330816
8. Santoso, S., Powers, E. J., Grady, W. M., & Hofmann, P. (2000). Power quality assessment via wavelet transform analysis. IEEE Transactions on Power Delivery, 15(2), 654–660. https://doi.org/10.1109/61.852984
9. IEC. (2014). IEC 61000-4-30: Testing and measurement techniques—Power quality measurement methods. International Electrotechnical Commission.
10. Watson, N. R., & Arrillaga, J. (2003). Power systems harmonic analysis. John Wiley & Sons.
11. Bollen, M. H. J. (2000). Understanding power quality problems: Voltage sags and interruptions. IEEE Press.
12. Dugan, R. C., McGranaghan, M. F., Santoso, S., & Beaty, H. W. (2012). Electrical power systems quality (3rd ed.). McGraw-Hill.
13. IEEE Standards Association. (2014). IEEE recommended practice and requirements for harmonic control in electric power systems (IEEE Std 519-2014). IEEE.
14. IEC. (2014). IEC 61000-4-30: Testing and measurement techniques—Power quality measurement methods. International Electrotechnical Commission.
15. Ribeiro, M. V., Duque, C. A., Silveira, P. M., & Cerqueira, A. S. (2014). Power quality disturbance detection, classification, and location using signal processing techniques. IEEE Signal Processing Magazine, 31(6), 24–35. https://doi.org/10.1109/MSP.2014.2330816
16. Dash, P. K., Panigrahi, B. K., & Panda, G. (2003). Power quality analysis using S-transform. IEEE Transactions on Power Delivery, 18(2), 406–411. https://doi.org/10.1109/TPWRD.2003.809624
17. Mallat, S. (1999). A wavelet tour of signal processing (2nd ed.). Academic Press.
18. Ribeiro, M. V., Duque, C. A., Silveira, P. M., & Cerqueira, A. S. (2014). Power quality disturbance detection, classification, and location using signal processing techniques. IEEE Signal Processing Magazine, 31(6), 24–35. https://doi.org/10.1109/MSP.2014.2330816
19. Santoso, S., Powers, E. J., Grady, W. M., & Hofmann, P. (2000). Power quality assessment via wavelet transform analysis. IEEE Transactions on Power Delivery, 15(2), 654–660. https://doi.org/10.1109/61.852984
20. Zhang, Y., Xiao, X., & Wang, Y. (2015). Power quality disturbance classification using wavelet transform and support vector machine. International Journal of Electrical Power & Energy Systems, 73, 394–402. https://doi.org/10.1016/j.ijepes.2015.05.013
21. Arrillaga, J., Watson, N. R., & Chen, S. (2000). Power system quality assessment. John Wiley & Sons.
22. Bollen, M. H. J. (2000). Understanding power quality problems: Voltage sags and interruptions. IEEE Press.
23. Dugan, R. C., McGranaghan, M. F., Santoso, S., & Beaty, H. W. (2012). Electrical power systems quality (3rd ed.). McGraw-Hill.
24. IEEE Standards Association. (2019). IEEE recommended practice for monitoring electric power quality (IEEE Std 1159-2019). IEEE.
25. IEC. (2014). IEC 61000-4-30: Testing and measurement techniques—Power quality measurement methods. International Electrotechnical Commission.
26. Arrillaga, J., Watson, N. R., & Chen, S. (2000). Power system quality assessment. John Wiley & Sons.
27. Bollen, M. H. J. (2000). Understanding power quality problems: Voltage sags and interruptions. IEEE Press.
28. Dash, P. K., Panigrahi, B. K., & Panda, G. (2003). Power quality analysis using S-transform. IEEE Transactions on Power Delivery, 18(2), 406–411. https://doi.org/10.1109/TPWRD.2003.809624
29. Dugan, R. C., McGranaghan, M. F., Santoso, S., & Beaty, H. W. (2012). Electrical power systems quality (3rd ed.). McGraw-Hill.
30. Gabor, D. (1946). Theory of communication. Journal of the Institution of Electrical Engineers – Part III: Radio and Communication Engineering, 93(26), 429–457. https://doi.org/10.1049/ji-3-2.1946.0074
31. Mallat, S. (1999). A wavelet tour of signal processing (2nd ed.). Academic Press.
32. Misiti, M., Misiti, Y., Oppenheim, G., & Poggi, J.-M. (2009). Wavelet toolbox™ user’s guide. MathWorks.
33. Ribeiro, M. V., Duque, C. A., Silveira, P. M., & Cerqueira, A. S. (2014). Power quality disturbance detection, classification, and location using signal processing techniques. IEEE Signal Processing Magazine, 31(6), 24–35. https://doi.org/10.1109/MSP.2014.2330816
34. Santoso, S., Powers, E. J., Grady, W. M., & Hofmann, P. (2000). Power quality assessment via wavelet transform analysis. IEEE Transactions on Power Delivery, 15(2), 654–660. https://doi.org/10.1109/61.852984
35. Zhang, Y., Xiao, X., & Wang, Y. (2015). Power quality disturbance classification using wavelet transform and support vector machine. International Journal of Electrical Power & Energy Systems, 73, 394–402. https://doi.org/10.1016/j.ijepes.2015.05.013
36. Dash, P. K., Panigrahi, B. K., & Panda, G. (2003). Power quality analysis using S-transform. IEEE Transactions on Power Delivery, 18(2), 406–411. https://doi.org/10.1109/TPWRD.2003.809624
37. Mallat, S. (1999). A wavelet tour of signal processing (2nd ed.). Academic Press.
38. Ribeiro, M. V., Duque, C. A., Silveira, P. M., & Cerqueira, A. S. (2014). Power quality disturbance detection, classification, and location using signal processing techniques. IEEE Signal Processing Magazine, 31(6), 24–35. https://doi.org/10.1109/MSP.2014.2330816
39. Santoso, S., Powers, E. J., Grady, W. M., & Hofmann, P. (2000). Power quality assessment via wavelet transform analysis. IEEE Transactions on Power Delivery, 15(2), 654–660. https://doi.org/10.1109/61.852984
40. Zhang, Y., Xiao, X., & Wang, Y. (2015). Power quality disturbance classification using wavelet transform and support vector machine. International Journal of Electrical Power & Energy Systems, 73, 394–402. https://doi.org/10.1016/j.ijepes.2015.05.013
41. Bollen, M. H. J. (2000). Understanding power quality problems: Voltage sags and interruptions. IEEE Press.
42. Dugan, R. C., McGranaghan, M. F., Santoso, S., & Beaty, H. W. (2012). Electrical power systems quality (3rd ed.). McGraw-Hill.
43. Ribeiro, M. V., Duque, C. A., Silveira, P. M., & Cerqueira, A. S. (2014). Power quality disturbance detection, classification, and location using signal processing techniques. IEEE Signal Processing Magazine, 31(6), 24–35. https://doi.org/10.1109/MSP.2014.2330816
44. Santoso, S., Powers, E. J., Grady, W. M., & Hofmann, P. (2000). Power quality assessment via wavelet transform analysis. IEEE Transactions on Power Delivery, 15(2), 654–660. https://doi.org/10.1109/61.852984
45. Zhang, Y., Xiao, X., & Wang, Y. (2015). Power quality disturbance classification using wavelet transform and support vector machine. International Journal of Electrical Power & Energy Systems, 73, 394–402. https://doi.org/10.1016/j.ijepes.2015.05.013
46. Dugan, R. C., McGranaghan, M. F., Santoso, S., & Beaty, H. W. (2012). Electrical power systems quality (3rd ed.). McGraw-Hill.
47. Mallat, S. (1999). A wavelet tour of signal processing (2nd ed.). Academic Press.
48. Santoso, S., Powers, E. J., Grady, W. M., & Hofmann, P. (2000). Power quality assessment via wavelet transform analysis. IEEE Transactions on Power Delivery, 15(2), 654–660. https://doi.org/10.1109/61.852984
49. Mallat, S. (1999). A wavelet tour of signal processing (2nd ed.). Academic Press.
50. Ribeiro, M. V., Duque, C. A., Silveira, P. M., & Cerqueira, A. S. (2014). Power quality disturbance detection, classification, and location using signal processing techniques. IEEE Signal Processing Magazine, 31(6), 24–35. https://doi.org/10.1109/MSP.2014.2330816
51. Santoso, S., Powers, E. J., Grady, W. M., & Hofmann, P. (2000). Power quality assessment via wavelet transform analysis. IEEE Transactions on Power Delivery, 15(2), 654–660. https://doi.org/10.1109/61.852984
52. Mallat, S. (1999). A wavelet tour of signal processing (2nd ed.). Academic Press.
53. Ribeiro, M. V., Duque, C. A., Silveira, P. M., & Cerqueira, A. S. (2014). Power quality disturbance detection, classification, and location using signal processing techniques. IEEE Signal Processing Magazine, 31(6), 24–35. https://doi.org/10.1109/MSP.2014.2330816
54. Dash, P. K., Panigrahi, B. K., & Panda, G. (2003). Power quality analysis using S-transform. IEEE Transactions on Power Delivery, 18(2), 406–411. https://doi.org/10.1109/TPWRD.2003.809624
55. Ribeiro, M. V., Duque, C. A., Silveira, P. M., & Cerqueira, A. S. (2014). Power quality disturbance detection, classification, and location using signal processing techniques. IEEE Signal Processing Magazine, 31(6), 24–35. https://doi.org/10.1109/MSP.2014.2330816
56. Santoso, S., Powers, E. J., Grady, W. M., & Hofmann, P. (2000). Power quality assessment via wavelet transform analysis. IEEE Transactions on Power Delivery, 15(2), 654–660. https://doi.org/10.1109/61.852984
57. Zhang, Y., Xiao, X., & Wang, Y. (2015). Power quality disturbance classification using wavelet transform and support vector machine. International Journal of Electrical Power & Energy Systems, 73, 394–402. https://doi.org/10.1016/j.ijepes.2015.05.013
58. Zhang, Y., Xiao, X., & Wang, Y. (2015). Power quality disturbance classification using wavelet transform and support vector machine. International Journal of Electrical Power & Energy Systems, 73, 394–402. https://doi.org/10.1016/j.ijepes.2015.05.013