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Simulation and Analysis of Perturbation and Observation-Based Self-Adaptable Step Size Maximum Power Point Tracking Strategy with Low Power Loss for Photovoltaics

Author

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  • Yinxiao Zhu

    (Department of Electrical and Electronic Engineering, Xi’an Jiaotong–Liverpool University, Suzhou 215123, China)

  • Moon Keun Kim

    (Department of Architecture, Xi’an Jiaotong–Liverpool University, Suzhou 215123, China)

  • Huiqing Wen

    (Department of Electrical and Electronic Engineering, Xi’an Jiaotong–Liverpool University, Suzhou 215123, China)

Abstract

Photovoltaic (PV) techniques are widely used in daily life. In addition to the material characteristics and environmental conditions, maximum power point tracking (MPPT) techniques are an efficient means to maximize the output power and improve the utilization of solar power. However, the conventional fixed step size perturbation and observation (P&O) algorithm results in perturbations and power loss around the maximum power point in steady-state operation. To reduce the power loss in steady-state operation and improve the response speed of MPPT, this study proposes a self-adaptable step size P&O-based MPPT algorithm with infinitesimal perturbations. This algorithm combines four techniques to upgrade the response speed and reduce the power loss: (1) system operation state determination, (2) perturbation direction decision, (3) adaptable step size, and 4) natural oscillation control. The simulation results validate the proposed algorithm and illustrate its performances in operational procedures.

Suggested Citation

  • Yinxiao Zhu & Moon Keun Kim & Huiqing Wen, 2018. "Simulation and Analysis of Perturbation and Observation-Based Self-Adaptable Step Size Maximum Power Point Tracking Strategy with Low Power Loss for Photovoltaics," Energies, MDPI, vol. 12(1), pages 1-20, December.
    • Handle: RePEc:gam:jeners:v:12:y:2018:i:1:p:92-:d:193725
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    1. Saravanan, S. & Ramesh Babu, N., 2016. "Maximum power point tracking algorithms for photovoltaic system – A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 57(C), pages 192-204.
    2. Abu Eldahab, Yasser E. & Saad, Naggar H. & Zekry, Abdalhalim, 2017. "Enhancing the tracking techniques for the global maximum power point under partial shading conditions," Renewable and Sustainable Energy Reviews, Elsevier, vol. 73(C), pages 1173-1183.
    3. Daraban, Stefan & Petreus, Dorin & Morel, Cristina, 2014. "A novel MPPT (maximum power point tracking) algorithm based on a modified genetic algorithm specialized on tracking the global maximum power point in photovoltaic systems affected by partial shading," Energy, Elsevier, vol. 74(C), pages 374-388.
    4. Luo, Yongqiang & Zhang, Ling & Liu, Zhongbing & Wang, Yingzi & Meng, Fangfang & Wu, Jing, 2016. "Thermal performance evaluation of an active building integrated photovoltaic thermoelectric wall system," Applied Energy, Elsevier, vol. 177(C), pages 25-39.
    5. Chih-Lung Shen & Cheng-Tao Tsai, 2012. "Double-Linear Approximation Algorithm to Achieve Maximum-Power-Point Tracking for Photovoltaic Arrays," Energies, MDPI, vol. 5(6), pages 1-16, June.
    6. Eduardo Manuel Godinho Rodrigues & Radu Godina & Mousa Marzband & Edris Pouresmaeil, 2018. "Simulation and Comparison of Mathematical Models of PV Cells with Growing Levels of Complexity," Energies, MDPI, vol. 11(11), pages 1-21, October.
    7. Dileep, G. & Singh, S.N., 2015. "Maximum power point tracking of solar photovoltaic system using modified perturbation and observation method," Renewable and Sustainable Energy Reviews, Elsevier, vol. 50(C), pages 109-129.
    8. Osseweijer, Floor J.W. & van den Hurk, Linda B.P. & Teunissen, Erik J.H.M. & van Sark, Wilfried G.J.H.M., 2018. "A comparative review of building integrated photovoltaics ecosystems in selected European countries," Renewable and Sustainable Energy Reviews, Elsevier, vol. 90(C), pages 1027-1040.
    9. Yang Du & Ke Yan & Zixiao Ren & Weidong Xiao, 2018. "Designing Localized MPPT for PV Systems Using Fuzzy-Weighted Extreme Learning Machine," Energies, MDPI, vol. 11(10), pages 1-10, October.
    10. Pi-Yun Chen & Kuei-Hsiang Chao & Zih-Yi Wu, 2018. "An Optimal Collocation Strategy for the Key Components of Compact Photovoltaic Power Generation Systems," Energies, MDPI, vol. 11(10), pages 1-24, September.
    11. Victor Andrean & Pei Cheng Chang & Kuo Lung Lian, 2018. "A Review and New Problems Discovery of Four Simple Decentralized Maximum Power Point Tracking Algorithms—Perturb and Observe, Incremental Conductance, Golden Section Search, and Newton’s Quadratic Int," Energies, MDPI, vol. 11(11), pages 1-25, November.
    12. Belhachat, Faiza & Larbes, Cherif, 2018. "A review of global maximum power point tracking techniques of photovoltaic system under partial shading conditions," Renewable and Sustainable Energy Reviews, Elsevier, vol. 92(C), pages 513-553.
    13. Ishaque, Kashif & Salam, Zainal & Lauss, George, 2014. "The performance of perturb and observe and incremental conductance maximum power point tracking method under dynamic weather conditions," Applied Energy, Elsevier, vol. 119(C), pages 228-236.
    14. 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.
    15. Danandeh, M.A. & Mousavi G., S.M., 2018. "Comparative and comprehensive review of maximum power point tracking methods for PV cells," Renewable and Sustainable Energy Reviews, Elsevier, vol. 82(P3), pages 2743-2767.
    16. Tingting Pei & Xiaohong Hao & Qun Gu, 2018. "A Novel Global Maximum Power Point Tracking Strategy Based on Modified Flower Pollination Algorithm for Photovoltaic Systems under Non-Uniform Irradiation and Temperature Conditions," Energies, MDPI, vol. 11(10), pages 1-16, October.
    17. Sivakumar, P. & Abdul Kader, Abdullah & Kaliavaradhan, Yogeshraj & Arutchelvi, M., 2015. "Analysis and enhancement of PV efficiency with incremental conductance MPPT technique under non-linear loading conditions," Renewable Energy, Elsevier, vol. 81(C), pages 543-550.
    18. Chatzipanagi, Anatoli & Frontini, Francesco & Virtuani, Alessandro, 2016. "BIPV-temp: A demonstrative Building Integrated Photovoltaic installation," Applied Energy, Elsevier, vol. 173(C), pages 1-12.
    19. Bradai, R. & Boukenoui, R. & Kheldoun, A. & Salhi, H. & Ghanes, M. & Barbot, J-P. & Mellit, A., 2017. "Experimental assessment of new fast MPPT algorithm for PV systems under non-uniform irradiance conditions," Applied Energy, Elsevier, vol. 199(C), pages 416-429.
    20. Verma, Deepak & Nema, Savita & Shandilya, A.M. & Dash, Soubhagya K., 2016. "Maximum power point tracking (MPPT) techniques: Recapitulation in solar photovoltaic systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 54(C), pages 1018-1034.
    21. Jordehi, A. Rezaee, 2016. "Maximum power point tracking in photovoltaic (PV) systems: A review of different approaches," Renewable and Sustainable Energy Reviews, Elsevier, vol. 65(C), pages 1127-1138.
    22. Chao, Kuei-Hsiang & Lin, Yu-Sheng & Lai, Uei-Dar, 2015. "Improved particle swarm optimization for maximum power point tracking in photovoltaic module arrays," Applied Energy, Elsevier, vol. 158(C), pages 609-618.
    23. Hassan M. H. Farh & Mohd F. Othman & Ali M. Eltamaly & M. S. Al-Saud, 2018. "Maximum Power Extraction from a Partially Shaded PV System Using an Interleaved Boost Converter," Energies, MDPI, vol. 11(10), pages 1-18, September.
    24. Fathabadi, Hassan, 2016. "Novel fast dynamic MPPT (maximum power point tracking) technique with the capability of very high accurate power tracking," Energy, Elsevier, vol. 94(C), pages 466-475.
    25. Mamarelis, Emilio & Petrone, Giovanni & Spagnuolo, Giovanni, 2014. "A two-steps algorithm improving the P&O steady state MPPT efficiency," Applied Energy, Elsevier, vol. 113(C), pages 414-421.
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