Robust Sliding Mode Control-Based Multi-Objective Particle Swarm Optimization for Harmonic Distortion Mitigation in Wind-Dominated Grids Using Real-Time Tuned Shunt Active Power Filters
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Through the escalating penetration of wind generation in modern power systems, new challenges are imposed on power quality, including harmonic distortion caused by power electronic based interfaces and non-linear loads. To overcome these problems, this paper proposes a new hybrid control strategy of Shunt Active Power Filters (SAPFs) based on the Sliding Mode Control (SMC) and the Multi-Objective Particle Swarm Optimization (MOPSO), to thereby improve the performance of such filters in harmonic compensation in wind-based electrical systems. The robustness and fast dynamic response characteristic of SMC is used to maintain system's stability under variation of wind generation and load. Meanwhile, controller parameters are optimized online based on MOPSO to satisfy various inconsistent control objectives such as Total Harmonic Distortion (THD) reduction, reactive power compensation, and low switching loss.
A dynamic grid connected wind energy system is simulated in MATLAB/Simulink with DFIG, nonlinear loads, and SAPF under various operating conditions. The Pareto-optimal set of controller gains is obtained by MOPSO algorithm that provides trade-off between harmonic compensation performance and control effort. The proposed system is analyzed using different wind speeds and load patterns to check the reliability and adaptability. Simulation comparatives with the classical PI, as well as the non-optimized SMC controller, show an important decrease in THD (attaching the standard IEEE-519) accepting power factor correction and the system stability. The findings validate that, the inclusion of SMC-based tuning with MOPSO improves the real-time efficiency of SAPFs. This work underpins the intelligent and adaptive PQ solutions for future smart grid applications with greater renewable-based generation. The developed approach is scalable, computationally inexpensive, and convenient for on-line application in active distribution networks.
J. Wang, Y. Zhou, Y. Bao, H. Kim, and M. Lee, “Fractional sliding mode harmonic control of an active power filter,” Applied Sciences, vol. 13, no. 6, 2022.
S. Sun, P. Yu, J. Xing, Y. Wang, and S. Yang, “Multi-objective collaborative optimization of active distribution networks based on improved PSO,” Scientific Reports, vol. 15, Art. no. 8999, 2025.
H. Zhou, Z. Li, and T. Zhang, “Improving real-time PI controller gains using PSO for APF switching,” Computers & Electrical Engineering, vol. 108, 2023.
R. Constant Fanjip, H. C. Essouma, and C. N. Kuo, “Fuzzy sliding mode control of SAPF for harmonic reduction in grid-connected PV systems,” Journal of Electrical Engineering, Electronics, Control and Computer Science, vol. 8, no. 27, pp. 43–54, 2021.
A. Cortajarena-Barambones, A. Tzounas, and A. B. Alvarado, “SMC of an APF for reactive-power compensation in PV systems,” Engineering Science, vol. 13, no. 2, pp. 89–102, 2022.
L. Xia, X. Lin, R. Zhou, and K. Zhang, “Multi-objective reactive-power optimization in PV distribution grids using MOPSO,” World Electric Vehicle Journal, vol. 16, no. 2, 2025.
M. T. Mdpi-review, “Machine learning in active power filters: A review,” Applied Machine Learning in Power Systems, vol. 4, pp. 115–130, 2024.
Y. Tang, W. Ma, and C. Jin, “GA-based tuning of SAPF for THD reduction,” Computers & Electrical Engineering, vol. 101, pp. 107–115, 2022.
K. Singh, B. Ghosh, and A. Saxena, “PSO tuning for SAPF harmonic reduction,” Renewable and Sustainable Energy Reviews, vol. 150, 2023.
P. Kumar, S. Nanda, and V. Sharma, “Metaheuristic tuning in power converters for harmonics,” IEEE Transactions on Smart Grid, vol. 15, no. 3, pp. 1752–1761, 2024.
Q.-M. Hoang, T. Le, and V. Le, “PSO-based SMC current control via real-time optimization,” arXiv preprint arXiv:2501.11633, Jan. 2025.
Z. Yuan, “MOPSO for SAPF multi-objective optimization,” IET Renewable Power Generation, vol. 15, no. 9, pp. 1760–1770, 2021.
A. Gupta, P. Rawat, and R. Maheshwari, “Real-time MOPSO in smart grids,” Frontiers in Energy Research, vol. 12, pp. 101–115, 2024.
V. Sharma, A. Kapoor, and P. Jain, “Hybrid PSO–SMC for microgrids with PV and wind,” Frontiers in Energy Research, vol. 11, pp. 210–225, 2024.
T. Patel and K. Dasgupta, “MOPSO enhancements for real-time control,” IEEE Transactions on Evolutionary Computation, vol. 28, no. 1, pp. 54–68, 2024.
R. Srilakshmi, M. Arun, and B. R. Kumar, “Fuzzy–SMC with MOPSO for hybrid energy systems,” Frontiers in Energy Research, vol. 12, pp. 310–322, 2024.
S. Boudechiche, M. Boudour, and M. Hamoudi, “Hybrid fuzzy–SMC optimization in microgrids,” Lecture Notes in Networks and Systems, vol. 103, pp. 321–330, 2020.
S. T. Lee, H. M. Kim, and J. H. Ahn, “HIL validation of SAPF control systems,” IEEE Transactions on Industrial Electronics, vol. 66, no. 8, pp. 6502–6511, 2019.
J. Iqbal, S. Khan, and M. H. Ali, “NN control in hybrid microgrids with APFs,” IEEE Access, vol. 12, pp. 18900–18913, 2024.
C. Wang, D. Feng, and K. C. Wang, “DSP implementation of real-time MOPSO control,” IEEE Transactions on Industrial Informatics, vol. 19, no. 4, pp. 4012–4024, 2023.
L. Pao, Y. Chen, and M. Fang, “MPC for wind turbine blade pitch control,” University of Colorado Technical Report, 2025.
Q.-M. Hoang, A. Pham, and T. Le, “PSO–SMC for grid-forming inverters in DFIG systems,” arXiv preprint arXiv:2501.11633, 2025.
S. Trip, M. Mandal, and A. Bose, “Distributed SMC for frequency control in grids,” arXiv preprint arXiv:1704.05267, 2017.
A. Rhif, M. Mnif, and H. B. Kammoun, “SMC strategies for DFIG torque control,” arXiv preprint arXiv:1304.3209, 2013.
G. Adrian, “Design and simulation of a shunt active filter to control harmonics,” arXiv preprint arXiv:1003.4366, 2010.
A. Anwar and A. N. Mahmood, “Swarm intelligence-based OPF for peak reduction in smart grids,” arXiv preprint arXiv:1409.1017, 2014.
J. Yu, L. Deng, M. Liu, and Z. Qiu, “Multi-objective design for hybrid APFs using chaotic PSO,” International Journal of Emerging Electric Power Systems, vol. 18, no. 3, pp. 1–12, 2017.
R. Usman and N. Magaji, “Hybrid SMC–ANN control for UPQC in wind-turbine systems,” Proceedings of the Institution of Engineers, vol. 105, no. 2, pp. 275–285, 2024.
Anonymous, “Synergetic control for three-level VSI-based APF demonstrating dynamic harmonic reduction,” Case Studies in Power and Energy Systems, vol. 8, pp. 120–128, 2023.
Anonymous, “Optimization of grid power quality using third-order sliding mode,” Case Studies in Power and Energy Systems, vol. 9, pp. 22–30, 2024.
A. Smith, K. Brown, and T. Ray, “Comparative evaluation of harmonic mitigation strategies in renewable-rich microgrids,” IEEE Transactions on Power Delivery, vol. 37, no. 5, pp. 4112–4120, 2024.
M. Li, X. Zhang, and Y. Zhao, “Adaptive sliding mode controller for SAPF with uncertainty compensation,” International Journal of Power Electronics and Drive Systems, vol. 14, no. 1, pp. 233–241, 2023.
N. Zhang, F. Yang, and Z. Liu, “Performance evaluation of MOPSO-based controller tuning in distribution systems,” Electronics, vol. 11, no. 8, pp. 1302–1315, 2022.
T. Zhao, W. Ren, and J. Li, “FPGA-based real-time control for harmonic mitigation,” IEEE Transactions on Industrial Electronics, vol. 70, no. 2, pp. 1212–1223, 2023.
K. Alatawi and A. Alghamdi, “Low latency implementation of PSO-based controllers using embedded systems,” IEEE Embedded Systems Letters, vol. 14, no. 1, pp. 24–28, 2023.
Y. Chen and B. Wei, “Energy-efficient harmonic mitigation in smart grids using multi-agent control,” Energy Reports, vol. 10, pp. 1268–1281, 2024.
