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Maximum Perturbation Step Size in MPP-Tracking Control for Ensuring Predicted PV Power Settling Behavior

Author

Listed:
  • Teuvo Suntio

    (Electrical Engineering Unit, Tampere University, 33720 Tampere, Finland)

  • Alon Kuperman

    (Applied Energy Laboratory, Department of Electrical and Computer Engineering, Ben-Gurion University of the Negev, 8410501 Beer-Sheva, Israel)

Abstract

The heuristic perturb-and-observe-based maximum-power-point tracking (MPPT) algorithm of photovoltaic (PV) generator is still the most popular technique in use, despite the broad spectrum of developed other MPPT algorithms. The correct direction of the next perturbation step requires that the previous perturbation is settled down properly and the applied perturbation step size is large enough to overcome the PV-power changes induced by the varying irradiation level and/or the power-grid-originated PV-voltage ripple. The requirements for the minimum perturbation step size are well defined in the available literature. The design equations to predict the PV-power settling time are derived by assuming that the PV-interfacing converter operates in continuous conduction mode (CCM). A large perturbation step size may drive the interfacing converter to enter into discontinuous conduction mode (DCM), which will delay the PV-power settling process and destroy the validity of the predicted settling times. In order to avoid confusing the MPPT process, the maximum perturbation step size has to be limited as well. This paper provides theoretical foundations for the proper design of the maximum step size based on the DC-DC interfacing-converter dynamic behavior. The theoretical findings are validated with experiments as well as by simulations by means of a boost-type DC-DC converter and real PV panel.

Suggested Citation

  • Teuvo Suntio & Alon Kuperman, 2019. "Maximum Perturbation Step Size in MPP-Tracking Control for Ensuring Predicted PV Power Settling Behavior," Energies, MDPI, vol. 12(20), pages 1-19, October.
    • Handle: RePEc:gam:jeners:v:12:y:2019:i:20:p:3984-:d:278283
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    References listed on IDEAS

    as
    1. Teuvo Suntio & Tuomas Messo & Aapo Aapro & Jyri Kivimäki & Alon Kuperman, 2017. "Review of PV Generator as an Input Source for Power Electronic Converters," Energies, MDPI, vol. 10(8), pages 1-25, July.
    2. Liu, Yi-Hua & Chen, Jing-Hsiao & Huang, Jia-Wei, 2015. "A review of maximum power point tracking techniques for use in partially shaded conditions," Renewable and Sustainable Energy Reviews, Elsevier, vol. 41(C), pages 436-453.
    3. Eyal Amer & Alon Kuperman & Teuvo Suntio, 2019. "Direct Fixed-Step Maximum Power Point Tracking Algorithms with Adaptive Perturbation Frequency," Energies, MDPI, vol. 12(3), pages 1-16, January.
    4. Jukka Viinamäki & Alon Kuperman & Teuvo Suntio, 2017. "Grid-Forming-Mode Operation of Boost-Power-Stage Converter in PV-Generator-Interfacing Applications," Energies, MDPI, vol. 10(7), pages 1-23, July.
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    Cited by:

    1. Miaomiao Ma & Xiangjie Liu & Kwang Y. Lee, 2020. "Maximum Power Point Tracking and Voltage Regulation of Two-Stage Grid-Tied PV System Based on Model Predictive Control," Energies, MDPI, vol. 13(6), pages 1-16, March.
    2. Gao, Renbo & Wu, Fei & Zou, Quanle & Chen, Jie, 2022. "Optimal dispatching of wind-PV-mine pumped storage power station: A case study in Lingxin Coal Mine in Ningxia Province, China," Energy, Elsevier, vol. 243(C).
    3. Sachin Angadi & Udaykumar R. Yaragatti & Yellasiri Suresh & A. B. Raju, 2021. "System Parameter Based Performance Optimization of Solar PV Systems with Perturbation Based MPPT Algorithms," Energies, MDPI, vol. 14(7), pages 1-20, April.

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