Improved Maximum Power Point Tracking Control for D-PMSG Systems: Fuzzy Gradient Step Approach

  • Muhammad Qasim Nawaz Department of Electrical Engineering and Automation, Yangzhou University, Yangzhou, China
  • Wei Jiang Department of Electrical Engineering and Automation, Yangzhou University, Yangzhou, China https://orcid.org/0000-0003-0178-2270
  • Muhammad Usman Department of Electrical Engineering and Automation, Yangzhou University, Yangzhou, China
  • Aimal Khan Department of Electrical Engineering and Automation, Yangzhou University, Yangzhou, China https://orcid.org/0000-0002-2260-6869

Abstract

This study introduces an enhanced Maximum Power Point Tracking (MPPT) control strategy for Direct Drive Permanent Magnet Synchronous Generators (D-PMSG) utilizing a Fuzzy Gradient Step Approach. By comparing with traditional MPPT methodologies, this approach demonstrates significant improvements in tracking accuracy, efficiency, and response time to fluctuating environmental conditions. The fuzzy logic control method adapts dynamically, optimizing power output under variable wind speeds. The comparative analysis reveals that our method not only surpasses conventional techniques in performance but also offers a cost-effective solution with less complexity. Implications of these advancements suggest potential applications in optimizing wind energy systems, enhancing the viability of renewable energy sources. By examining the relationship between Boost duty cycle changes and wind turbine output characteristics, a fuzzy gradient step hill-climbing search method is proposed to calculate the wind turbine output speed in order to improve the maximum power point tracking control performance of the direct-drive permanent magnet wind power generation system. The fuzzy controller employs the duty cycle of the Boost converter as its output quantity and its input quantity to accomplish the maximum power point tracking control of the wind turbine. A model was developed and verified through simulation for use in system modeling. The results show that the fuzzy gradient step hill-climbing search approach is more effective at regulating the maximum power point tracking control of the direct-drive permanent magnet wind power producing system than the traditional variable step-size hill-climbing search algorithm. This research paves the way for future exploration in smart grid integration and scalability of fuzzy logic-based MPPT controllers, marking a pivotal step towards sustainable energy solutions.

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References

New installed wind energy capacity worldwide 2022 |Statista." New installed wind energy capacity worldwide 2022 | Statista. October 2023.

Global installed wind energy capacity 2022 | Statista. (2023c,). Global cumulative wind energy installed capacity. August 29.

Alex. (2023b, October 9). Global Offshore Wind Report. Global Wind Energy Council. https://gwec.net/gwecs-global-offshore-wind-report-2023

S. Honarbari, S. Najafi, M. Saffari Pour, S. Mousavi Ajarostaghi, and A. Hassannia, ‘MPPT Improvement for PMSG-Based Wind Turbines Using Extended Kalman Filter and Fuzzy Control System’, Energies, vol. 14, p. 7503, 11 2021.

S. Vig, ‘Modeling of MPPT-Based Solar Eco-System Using Fuzzy Logic Controller’, IOP Conference Series: Earth and Environmental Science, vol. 1110, p. 012079, 02 2023

M. Aly, E. A. Mohamed, H. Rezk, A. M. Nassef, M. A. Elhosseini, and A. Shawky, ‘An Improved Optimally Designed Fuzzy Logic-Based MPPT Method for Maximizing Energy Extraction of PEMFC in Green Buildings’, Energies, vol. 16, no. 3, 2023.

S. Tao, L. Zhao, Y. Liu, and K. Liao, ‘Impedance Network Model of D-PMSG Based Wind Power Generation System Considering Wind Speed Variation for Sub-Synchronous Oscillation Analysis’, IEEE Access, vol. 8, pp. 114784–114794, 2020

S. Yang et al., ‘PLL Based Sub-/Super-Synchronous Resonance Damping Controller for D-PMSG Wind Farm Integrated Power Systems’, IEEE Transactions on Energy Conversion, vol. 37, no. 4, pp. 2370–2384, 2022.

L. Xu, G. Wang, L. Fu, Y. Wu, and Q. Shi, ‘General average model of D-PMSG and its application with virtual inertia control’, in 2015 IEEE International Conference on Mechatronics and Automation (ICMA), 2015, pp. 802–807.

M. Karbakhsh, H. Abutorabi, and A. Khazaee, ‘An enhanced MPPT fuzzy control of a wind turbine equipped with permanent magnet synchronous generator’, 10 2012, pp. 77–82.

S. Tao, L. Zhao, K. Liao, and Y. Liu, ‘Probability Assessment of Characteristics of Sub-Synchronous Oscillation in D-PMSG-Based Wind Power Generation System’, IEEE Access, vol. 7, pp. 133159–133169, 2019.

B. Huang, H. Sun, Y. Liu, L. Wang, and Y. Chen, ‘Study on subsynchronous oscillation in D‐PMSGs‐based wind farm integrated to power system’, Iet Renewable Power Generation, vol. 13, no. 1, pp. 16–26, 10 2018.

L. Yan, C. Yongning, W. Zhen, W. Linjun, and L. Chao, ‘Study on LVRT capability of D-PMSG based wind turbine’, in 2011 IEEE Power Engineering and Automation Conference, 2011, vol. 1, pp. 154–157.

G. Feng, H. Qifei, H. Zhiguo, and Z. Baohui, ‘The research of sub synchronous oscillation in PMSG wind farm’, in 2016 IEEE PES Asia-Pacific Power and Energy Engineering Conference (APPEEC), 2016, pp. 1883–1887.

X. Zou, X. Du, and H.-M. Tai, ‘Two-Variable Admittance Model for D-PMSG-Based Wind Turbine and Stability Criterion Based on Magnitude and Phase Contour Plot’, IEEE Transactions on Power Electronics, vol. 35, no. 2, pp. 1484–1498, 2020.

Y.-Z. Sun, Z.-S. Zhang, G.-J. Li, and J. Lin, ‘Review on frequency control of power systems with wind power penetration’, in 2010 International Conference on Power System Technology, 2010, pp. 1–8.

M. Wang-Hansen, R. Josefsson, and H. Mehmedovic, ‘Frequency Controlling Wind Power Modeling of Control Strategies’, IEEE Transactions on Sustainable Energy, vol. 4, no. 4, pp. 954–959, 2013.

J. Hou, Z. Liu, S. Wang, and Z. Chen, ‘Modeling and HIL Test of a D-PMSG Connected to Power System with Damping Control for Real Time Studies’, in 2021 3rd Asia Energy and Electrical Engineering Symposium (AEEES), 2021, pp. 644–649.

J. Chen, H. Wu, M. Sun, W. Jiang, L. Cai, and C. Guo, ‘Modeling and simulation of directly driven wind turbine with permanent magnet synchronous generator’, in IEEE PES Innovative Smart Grid Technologies, 2012, pp. 1–5.

C. Ge, M. Liu, and J. Chen, ‘Modeling of Direct-Drive Permanent Magnet Synchronous Wind Power Generation System Considering the Power System Analysis in Multi-Timescales’, Energies, vol. 15, no. 20, 2022.

N. Rezaei, K. Mehran, and C. Cossar, ‘A model-based implementation of an MPPT technique and a control system for a variable speed wind turbine PMSG’, International Journal of Modelling, Identification and Control, vol. 31, p. 3, 01 2019.

M. Rahimi, ‘Modeling, control and stability analysis of grid connected PMSG based wind turbine assisted with diode rectifier and boost converter’, International Journal of Electrical Power & Energy Systems, vol. 93, pp. 84–96, 2017.

S. Toumi, S. E. Ben Elghali, M. Trabelsi, E. Elbouchikhi, M. E. H. Benbouzid, and M. F. Mimouni, ‘Robustness analysis and evaluation of a PMSG-based marine current turbine system under faulty conditions’, in 2014 15th International Conference on Sciences and Techniques of Automatic Control and Computer Engineering (STA), 2014, pp. 631–636.

B. N. Alajmi, K. H. Ahmed, S. J. Finney, and B. W. Williams, ‘Fuzzy-Logic-Control Approach of a Modified Hill-Climbing Method for Maximum Power Point in Microgrid Standalone Photovoltaic System’, IEEE Transactions on Power Electronics, vol. 26, no. 4, pp. 1022–1030, 2011.

S. A. Kazarlis, S. E. Papadakis, J. B. Theocharis, and V. Petridis, ‘Microgenetic algorithms as generalized hill-climbing operators for GA optimization’, IEEE Transactions on Evolutionary Computation, vol. 5, no. 3, pp. 204–217, 2001.

R. Boukenoui, R. Bradai, A. Mellit, M. Ghanes, and H. Salhi, ‘Comparative analysis of P&O, modified hill climbing-FLC, and adaptive P&O-FLC MPPTs for microgrid standalone PV system’, in 2015 International Conference on Renewable Energy Research and Applications (ICRERA), 2015, pp. 1095–1099.

Kovacic, Z., & Bogdan, S. (2005). Fuzzy Controller Design: Theory and Applications (1st ed.). CRC Press. https://doi.org/10.1201/9781420026504

S. Huang, G. Zong, N. Zhao, X. Zhao, and A. M. Ahmad, ‘Performance recovery-based fuzzy robust control of networked nonlinear systems against actuator fault: A deferred actuator-switching method’, Fuzzy Sets and Systems, vol. 480, p. 108858, 2024.

M. J. Patyra, J. L. Grantner, and K. Koster, ‘Digital fuzzy logic controller: design and implementation’, IEEE Transactions on Fuzzy Systems, vol. 4, no. 4, pp. 439–459, 1996.

R. Ketata, D. De Geest, and A. Titli, ‘Fuzzy controller: design, evaluation, parallel and hierarchial combination with a PID controller’, Fuzzy Sets and Systems, vol. 71, no. 1, pp. 113–129, 1995.

S.-J. Wu and C.-T. Lin, ‘Optimal fuzzy controller design: local concept approach’, IEEE Transactions on Fuzzy Systems, vol. 8, no. 2, pp. 171–185, 2000.

M. Abdolhosseini and R. Abdollahi, ‘Designing and Implementing a Lighting Control System Based on Constrained Info-Fuzzy, to Save Energy and Satisfy Users’, IEEE Transactions on Industrial Informatics, pp. 1–8, 2024.

M. Allouche, K. Dahech, and J.-P. Gaubert, ‘Maximum Power Point Tracking Control of a Variable Speed Wind Turbine via a T-S Fuzzy Model-based Approach’, pp. 1–13, 2024.

Z. Zemali et al., ‘Robust intelligent fault diagnosis strategy using Kalman observers and neuro-fuzzy systems for a wind turbine benchmark’, Renewable Energy, vol. 205, pp. 873–898, 2023.

A. Al-Odienat and A. Al-Lawama, ‘The Advantages of PID Fuzzy Controllers Over the Conventional Types’, American Journal of Applied Sciences, vol. 5, 06 2008.

A. Bello, K. S. Olfe, J. Rodríguez, J. M. Ezquerro, and V. Lapuerta, ‘Experimental verification and comparison of fuzzy and PID controllers for attitude control of nanosatellites’, Advances in Space Research, vol. 71, no. 9, pp. 3613–3630, 2023.

B. Abdul Basit and J.-W. Jung, ‘Recent developments and future research recommendations of control strategies for wind and solar PV energy systems’, Energy Reports, vol. 8, pp. 14318–14346, 2022.

D. Basha and R. Chinnappa Naidu, ‘Performance Analysis of MPPT Techniques for Dynamic Irradiation Condition of Solar PV’, International Journal of Fuzzy Systems, vol. 22, 10 2020.

Published
2024-04-14
How to Cite
[1]
M. Q. Nawaz, W. Jiang, M. Usman, and Aimal Khan, “Improved Maximum Power Point Tracking Control for D-PMSG Systems: Fuzzy Gradient Step Approach ”, j.electron.electromedical.eng.med.inform, vol. 6, no. 2, pp. 157-168, Apr. 2024.
Section
Research Paper