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Research Article |

Harmonic Mitigation in Power Systems Using an ANN-Driven Shunt Active Power Filter: A Simulation-Based Study

Author(s): Mohammed Taha Yunis1, Raghad Hameed Ahmed 2*, and Seham Ahmed Hashem3

Published In : International Journal of Electrical and Electronics Research (IJEER)        Volume 14, Issue 3

Publisher : FOREX Publication

Published : 30 September 2026

e-ISSN : 2347-470X

Page(s) : 789-795

DOI: https://doi.org/10.37391/IJEER.140310

Abstract

This paper proposal a design-based artificial neural network (ANN) control approach for a shunt active power filter (SAPF) implemented to a three-phase nonlinear load system. Harmonic variables are extracted from the load current by a Fast Fourier Transform (FFT) and provide to a feed forward ANN that generates three phase compensating current references. The ANN-SAPF is implementation in MATLAB/design under steady-state sudden load fluctuation and asymmetrical load conditions. Using the consistent harmonic result set reported in the results section the source the current total harmonic distortion (THD) is decrease from 7.82% to 2.28%, while the PCC-voltage THD reduce from 3.59% to 1.69%. The dominant 5th and 7th order current harmonics are decreased from 4.85% and 2.35% to 0.92% and 0.66%, respectively. The ANN test the stat regression coefficient is 0.999996 as well as a test MSE of 1.2×10⁻5. The method is presented strictly as simulation validation no experimental processor in the loop hardware in the loop or monitoring real time execution claim is made. IEEE 519 is interpreted according to PCC for voltage and current distortion criteria rather than as a universal 5% current THD limit. The results refer that the integration ANN-driven SAPF provides effective harmonic compensation over the simulated operating conditions.

Keywords: Shunt Active Power Filter, Artificial Neural Network, Harmonic Mitigation, Fast Fourier Transform, Power Quality, Nonlinear Load.




Mohammed Taha Yunis , Southern Technical University, Basra, Iraq; Email: Mohammed.taha@stu.edu.iq

Raghad Hameed Ahmed , Middle Technical University, Baghdad, Iraq; Email: raghad.hammed@mtu.edu.iq

Seham Ahmed Hashem, Middle Technical University, Baghdad, Iraq; Email: dr.seham.ahmed@mtu.edu.iq

    [1] P. Farhadi, M. Navidi, M. Gheydi, M. Pazhoohesh, and H. Bevrani, "Online selective harmonic minimization for cascaded Half-bridge multilevel inverter using artificial neural network," 2015 Intl Aegean Conference on Electrical Machines & Power Electronics (ACEMP), 2015 Intl Conference on Optimization of Electrical & Electronic Equipment (OPTIM) & 2015 Intl Symposium on Advanced Electromechanical Motion Systems (ELECTROMOTION), Side, Turkey, 2015, pp. 331-335,doi: 10.1109/OPTIM.2015.7426985.
    [2] A. Sharma, V. Nagar, and D. K. Palwalia, "Analysis and design of Artificial Neural Network Based Droop Control for Autonomous Hybrid Microgrid," 2024 IEEE Third International Conference on Power Electronics, Intelligent Control and Energy Systems (ICPEICES), Delhi, India, 2024, pp. 593-598, doi: 10.1109/ICPEICES62430.2024.10719091.
    [3] T. Penthia, A. K. Panda, S. K. Sarangi, and M. Mangaraj, "ANN-controlled4-leg VSC-based DSTATCOM for power quality enhancement," 2015 Annual IEEE India Conference (INDICON), New Delhi, India, 2015, pp. 1-6, doi: 10.1109/INDICON.2015.7443194.Buonomo, A., & DiBello, C. (1996). Asymptotic formulas in nearly sinusoidal nonlinear oscillators. IEEE Transactions on Circuits and Systems I: Fundamental Theory and Applications, 43(12), 953–963. https://doi.org/10.1109/81.545836
    [4] Q. Qiang, F. Yunwen, and L. Feng, “Structural reliability analysis using an enhanced cuckoo search algorithm and an artificial neural network,” in Journal of Systems Engineering and Electronics, vol. 29, no. 6, pp. 1317-1326, Dec. 2018, doi: 10.21629/JSEE.2018.06.19.
    [5] M. Balasubramonian and V. Rajamani, "Design and real-time implementation of SHEPWM in a single-phase inverter using generalized Hopfield neural network," IEEE Transactions on Industrial Electronics, vol. 61, no. 11, pp. 6327-6336, 2014, doi: 10.1109/TIE.2014.2304919.
    [6] A. D. Ayad, A. Gouichiche, Y. Badaoui, and A. Safa, "Optimized ripple prelearning process for phase-shift control of interleaved multiphase DC-DC converters," IEEE Transactions on Industrial Electronics, vol. 72, no. 3, pp. 3103-3113, 2025, doi: 10.1109/TIE.2024.3447735
    [7] A. Jose and P. A., "Analysis of DPC Techniques Used in DFIG Based WECS," 2025 IEEE 1st International Conference on Smart and Sustainable Developments in Electrical Engineering (SSDEE), Dhanbad, India, 2025, pp. 1-5, doi: 10.1109/SSDEE64538.2025.10968422
    [8] P. Katta, S. R. D. Joseph, A. P. S. V., and M. E., "CNN Assisted SRF Theory with Firefly Optimized Single-Phase UPQC System for PQ Improvement," 2023 International Conference on Circuit Power and Computing Technologies (ICCPCT), Kollam, India, 2023, pp. 755-760, doi: 10.1109/ICCPCT58313.2023.10244928.
    [9] Dixant Bikal Sapkota, Puskar Neupane, Kajal Pokharel, Shahabuddin Khan. "An artificial neural network based approach for harmonic component prediction in a Distribution Line, Energy Reports, Volume 12,2024, pp. 3861-3873,ISSN 2352-4847, https://doi.org/10.1016/j.egyr.2024.09.060..
    [10] Junxiao Chang, Junda Zhang, Xiaobing Liao, Ji Lu. "Distributed reactive power optimization of flexible distribution network based on Probability Scenario-Driven, Energy Reports, Volume 13,2025, pp. 68-81,ISSN 2352-4847, https://doi.org/10.1016/j.egyr.2024.12.002.
    [11] M. S. Bhutta, Y. Li, M. Abubakar, F. M. Almasoudi, K. S. S. Alatawi, M. R. Altimania, and M. Al-Barashi, "Optimizing solar power efficiency in smart grids using hybrid machine learning models for accurate energy generation prediction," Scientific Reports, vol. 14, Art. no. 17101, 2024, doi: 10.1038/s41598-024-68030-5.
    [12] M. L., N., Vital., Srinu Ejjipurapu, Daya Sagar Battu, A. M., Mohammad., Uday Annaparedddy. (2024). Performance Evaluation of Machine Learning Algorithms for Stability Prediction in Smart Grids." https://doi.org/10.1109/ICSSES62373.2024.10561434.
    [13] A. Lakshmanarao, A. Srisaila, T. S. Ravi Kiran, K. Vasanth Kumar, and C. S. Koppireddy, "An efficient smart grid stability prediction system based on machine learning and deep learning fusion model," Indonesian Journal of Electrical Engineering and Computer Science, vol. 33, no. 2, pp. 1293-1301, 2024, doi: 10.11591/ijeecs.v33.i2.pp1293-1301.
    [14] A.Jaya, Mabel Rani B., Kalpana., A., Srinivasan., Sangar Subramaniam, Msc, Cybersecurity S. A., Shiney., V.Samuthira Pandi. (2023). Artificial Intelligence- Enabled Smart Grids: Enhancing Efficiency and Sustainability. https://doi.org/10.1109/ICECA58529.2023.10395590
    [15] S. I. Ewad, M. T. Yunis, B. T. Dawood, and H. D. Atiyah, “Hybrid ANN-FLC Based Fault Detection in PV Systems,” 2025 IEEE 22nd International Conference on Sciences and Techniques of Automatic Control and Computer Engineering (STA), Hammamet, Tunisia, 2025, pp. 616-621, doi: 10.1109/STA66620.2025.11364813.
    [16] S. M. Sajjadi Mohammadabadi, M. Entezami, A. Karimi Moghaddam, M. Orangian, and S. Nejadshamsi, "Generative artificial intelligence for distributed learning to enhance smart grid communication," International Journal of Intelligent Networks, vol. 5, pp. 267-274, 2024, doi: 10.1016/j.ijin.2024.05.007.
    [17] Sana Dahmani. (2024). Energy Optimization and Smart Grids. Advances in Systems Analysis, Software Engineering, and High-performance Computing book series, doi: 10.4018/979-8-3693-1794-5.ch013
    [18] Ahmed, R. H., & Nouri, A. S. (2023). Improvement of the Power System's Transient Stability Using the Unified Power Flow Controller with a Fuzzy Logic Technique. Journal of Techniques, 5(3), 61-72. DOI: 10.51173/jt.v5i3.1249.
    [19] Chaitanya Agarwal, Kabir., Vinod Kumar Yadav. (2023). Machine Learning-Aided Techniques for Constraints Elimination in the Optimal Power Flow Problem. https://doi.org/10.1109/SPIN57001.2023.10116165 .
    [20] Priyanka Chandani; Sandip Vijay. (2023). The Implementation of Integration of ML Algorithm for the Design of a Stability System for a Grid System. https://doi.org/10.1109/PEEIC59336.2023.10451018 .
    [21] IEEE, "IEEE Standard for Harmonic Control in Electric Power Systems," IEEE Std 519-2022, 2022.

Mohammed Taha Yunis, Raghad Hameed Ahmed, and Seham Ahmed Hashem (2026), Harmonic Mitigation in Power Systems Using an ANN-Driven Shunt Active Power Filter: A Simulation-Based Study. IJEER 14(3), 789-795. DOI: 10.37391/IJEER.140312.