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Neuro-Fuzzy Wavelet Based Adaptive MPPT Algorithm for Photovoltaic Systems

Author

Listed:
  • Syed Zulqadar Hassan

    (State Key Laboratory of Power Transmission Equipment and System Security and New Technology, School of Electrical Engineering, Chongqing University, Chongqing 400044, China)

  • Hui Li

    (State Key Laboratory of Power Transmission Equipment and System Security and New Technology, School of Electrical Engineering, Chongqing University, Chongqing 400044, China)

  • Tariq Kamal

    (Department of Electrical and Electronics Engineering, Faculty of Engineering, Sakarya University, Serdivan/Sakarya 54050, Turkey)

  • Uğur Arifoğlu

    (Department of Electrical and Electronics Engineering, Faculty of Engineering, Sakarya University, Serdivan/Sakarya 54050, Turkey)

  • Sidra Mumtaz

    (Department of Electrical Engineering, COMSATS Institute of Information Technology, Abbottabad 22060, Pakistan)

  • Laiq Khan

    (Department of Electrical Engineering, COMSATS Institute of Information Technology, Abbottabad 22060, Pakistan)

Abstract

An intelligent control of photovoltaics is necessary to ensure fast response and high efficiency under different weather conditions. This is often arduous to accomplish using traditional linear controllers, as photovoltaic systems are nonlinear and contain several uncertainties. Based on the analysis of the existing literature of Maximum Power Point Tracking (MPPT) techniques, a high performance neuro-fuzzy indirect wavelet-based adaptive MPPT control is developed in this work. The proposed controller combines the reasoning capability of fuzzy logic, the learning capability of neural networks and the localization properties of wavelets. In the proposed system, the Hermite Wavelet-embedded Neural Fuzzy (HWNF)-based gradient estimator is adopted to estimate the gradient term and makes the controller indirect. The performance of the proposed controller is compared with different conventional and intelligent MPPT control techniques. MATLAB results show the superiority over other existing techniques in terms of fast response, power quality and efficiency.

Suggested Citation

  • Syed Zulqadar Hassan & Hui Li & Tariq Kamal & Uğur Arifoğlu & Sidra Mumtaz & Laiq Khan, 2017. "Neuro-Fuzzy Wavelet Based Adaptive MPPT Algorithm for Photovoltaic Systems," Energies, MDPI, vol. 10(3), pages 1-16, March.
    • Handle: RePEc:gam:jeners:v:10:y:2017:i:3:p:394-:d:93552
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    References listed on IDEAS

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    1. Chendi Li & Yuanrui Chen & Dongbao Zhou & Junfeng Liu & Jun Zeng, 2016. "A High-Performance Adaptive Incremental Conductance MPPT Algorithm for Photovoltaic Systems," Energies, MDPI, vol. 9(4), pages 1-17, April.
    2. Gupta, A.K. & Ray, S. Saha, 2015. "An investigation with Hermite Wavelets for accurate solution of Fractional Jaulent–Miodek equation associated with energy-dependent Schrödinger potential," Applied Mathematics and Computation, Elsevier, vol. 270(C), pages 458-471.
    3. Paula Andrea Ortiz Valencia & Carlos Andres Ramos-Paja, 2015. "Sliding-Mode Controller for Maximum Power Point Tracking in Grid-Connected Photovoltaic Systems," Energies, MDPI, vol. 8(11), pages 1-25, November.
    4. Suliang Ma & Mingxuan Chen & Jianwen Wu & Wenlei Huo & Lian Huang, 2016. "Augmented Nonlinear Controller for Maximum Power-Point Tracking with Artificial Neural Network in Grid-Connected Photovoltaic Systems," Energies, MDPI, vol. 9(12), pages 1-24, November.
    5. Messalti, Sabir & Harrag, Abdelghani & Loukriz, Abdelhamid, 2017. "A new variable step size neural networks MPPT controller: Review, simulation and hardware implementation," Renewable and Sustainable Energy Reviews, Elsevier, vol. 68(P1), pages 221-233.
    6. Hong, Chih-Ming & Ou, Ting-Chia & Lu, Kai-Hung, 2013. "Development of intelligent MPPT (maximum power point tracking) control for a grid-connected hybrid power generation system," Energy, Elsevier, vol. 50(C), pages 270-279.
    7. Ray, S. Saha & Gupta, A.K., 2015. "A numerical investigation of time-fractional modified Fornberg–Whitham equation for analyzing the behavior of water waves," Applied Mathematics and Computation, Elsevier, vol. 266(C), pages 135-148.
    8. Tanaselan Ramalu & Mohd Amran Mohd Radzi & Muhammad Ammirrul Atiqi Mohd Zainuri & Noor Izzri Abdul Wahab & Ribhan Zafira Abdul Rahman, 2016. "A Photovoltaic-Based SEPIC Converter with Dual-Fuzzy Maximum Power Point Tracking for Optimal Buck and Boost Operations," Energies, MDPI, vol. 9(8), pages 1-17, July.
    9. Mukerjee, A.K. & Dasgupta, Nivedita, 2007. "DC power supply used as photovoltaic simulator for testing MPPT algorithms," Renewable Energy, Elsevier, vol. 32(4), pages 587-592.
    10. Eltawil, Mohamed A. & Zhao, Zhengming, 2013. "MPPT techniques for photovoltaic applications," Renewable and Sustainable Energy Reviews, Elsevier, vol. 25(C), pages 793-813.
    11. Ou, Ting-Chia & Hong, Chih-Ming, 2014. "Dynamic operation and control of microgrid hybrid power systems," Energy, Elsevier, vol. 66(C), pages 314-323.
    12. Lin, Chia-Hung & Huang, Cong-Hui & Du, Yi-Chun & Chen, Jian-Liung, 2011. "Maximum photovoltaic power tracking for the PV array using the fractional-order incremental conductance method," Applied Energy, Elsevier, vol. 88(12), pages 4840-4847.
    13. Po-Chen Cheng & Bo-Rei Peng & Yi-Hua Liu & Yu-Shan Cheng & Jia-Wei Huang, 2015. "Optimization of a Fuzzy-Logic-Control-Based MPPT Algorithm Using the Particle Swarm Optimization Technique," Energies, MDPI, vol. 8(6), pages 1-23, June.
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    Cited by:

    1. Kamran Zeb & Muhammad Saqib Nazir & Iftikhar Ahmad & Waqar Uddin & Hee-Je Kim, 2021. "Control of Transformerless Inverter-Based Two-Stage Grid-Connected Photovoltaic System Using Adaptive-PI and Adaptive Sliding Mode Controllers," Energies, MDPI, vol. 14(9), pages 1-15, April.
    2. Muhammad Awais & Laiq Khan & Saghir Ahmad & Sidra Mumtaz & Rabiah Badar, 2020. "Nonlinear adaptive NeuroFuzzy feedback linearization based MPPT control schemes for photovoltaic system in microgrid," PLOS ONE, Public Library of Science, vol. 15(6), pages 1-36, June.
    3. Maen Takruri & Maissa Farhat & Oscar Barambones & José Antonio Ramos-Hernanz & Mohammed Jawdat Turkieh & Mohammed Badawi & Hanin AlZoubi & Maswood Abdus Sakur, 2020. "Maximum Power Point Tracking of PV System Based on Machine Learning," Energies, MDPI, vol. 13(3), pages 1-14, February.
    4. Tariq Kamal & Murat Karabacak & Vedran S. Perić & Syed Zulqadar Hassan & Luis M. Fernández-Ramírez, 2020. "Novel Improved Adaptive Neuro-Fuzzy Control of Inverter and Supervisory Energy Management System of a Microgrid," Energies, MDPI, vol. 13(18), pages 1-22, September.
    5. Touqeer Ahmed Jumani & Mohd Wazir Mustafa & Nawaf N. Hamadneh & Samer H. Atawneh & Madihah Md. Rasid & Nayyar Hussain Mirjat & Muhammad Akram Bhayo & Ilyas Khan, 2020. "Computational Intelligence-Based Optimization Methods for Power Quality and Dynamic Response Enhancement of ac Microgrids," Energies, MDPI, vol. 13(16), pages 1-22, August.
    6. Dan Craciunescu & Laurentiu Fara, 2023. "Investigation of the Partial Shading Effect of Photovoltaic Panels and Optimization of Their Performance Based on High-Efficiency FLC Algorithm," Energies, MDPI, vol. 16(3), pages 1-28, January.
    7. Julie Viloria-Porto & Carlos Robles-Algarín & Diego Restrepo-Leal, 2018. "A Novel Approach for an MPPT Controller Based on the ADALINE Network Trained with the RTRL Algorithm," Energies, MDPI, vol. 11(12), pages 1-17, December.
    8. Musong L. Katche & Augustine B. Makokha & Siagi O. Zachary & Muyiwa S. Adaramola, 2023. "A Comprehensive Review of Maximum Power Point Tracking (MPPT) Techniques Used in Solar PV Systems," Energies, MDPI, vol. 16(5), pages 1-23, February.
    9. Nima Amjady & Oveis Abedinia, 2017. "Short Term Wind Power Prediction Based on Improved Kriging Interpolation, Empirical Mode Decomposition, and Closed-Loop Forecasting Engine," Sustainability, MDPI, vol. 9(11), pages 1-18, November.
    10. Sidra Mumtaz & Saima Ali & Saghir Ahmad & Laiq Khan & Syed Zulqadar Hassan & Tariq Kamal, 2017. "Energy Management and Control of Plug-In Hybrid Electric Vehicle Charging Stations in a Grid-Connected Hybrid Power System," Energies, MDPI, vol. 10(11), pages 1-21, November.
    11. Carlos Robles Algarín & John Taborda Giraldo & Omar Rodríguez Álvarez, 2017. "Fuzzy Logic Based MPPT Controller for a PV System," Energies, MDPI, vol. 10(12), pages 1-18, December.
    12. Sidra Mumtaz & Saghir Ahmad & Laiq Khan & Saima Ali & Tariq Kamal & Syed Zulqadar Hassan, 2018. "Adaptive Feedback Linearization Based NeuroFuzzy Maximum Power Point Tracking for a Photovoltaic System," Energies, MDPI, vol. 11(3), pages 1-15, March.

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