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Multiple-to-single maximum power point tracking for empowering conventional MPPT algorithms under partial shading

Njimboh Henry Alombah1, Ambe Harrison2,3, Wulfran Fendzi Mbasso4,5

  • 1Department of Electrical and Electronics Engineering, College of Technology, University of Bamenda, P.O. Box 39, Bambili, Cameroon. henry.alombah@gmail.com.

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|April 25, 2025
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Summary

Partial shading in photovoltaic systems is solved by a new framework that converts multi-peak power curves to single-peak curves. This enables conventional algorithms to reliably find the global maximum power point, boosting energy harvest and system reliability.

Keywords:
Maximum power point (MPP)Multiple-to-single MPP conversionMultiple-to-single maximum power point tracking (MSMPPT)Partial shading conditions (PSC)Photovoltaic (PV)

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Area of Science:

  • Electrical Engineering
  • Renewable Energy Systems
  • Power Electronics

Background:

  • Partial shading conditions (PSC) in photovoltaic (PV) systems create multi-peak power-voltage (P-V) curves.
  • Conventional maximum power point tracking (MPPT) algorithms often get trapped in local maxima under PSC, reducing energy yield.
  • Existing solutions may require hardware modifications or complex algorithms.

Purpose of the Study:

  • To present a novel Multi-Peak to Single-Peak Conversion (MSMPPT) framework.
  • To enable conventional MPPT algorithms (e.g., Perturb & Observe, Incremental Conductance) to reliably track the global maximum power point (GMPP) under PSC without modifications.
  • To enhance PV system performance and reliability in shading environments.

Main Methods:

  • The MSMPPT framework uses dynamic estimation of optimal voltage boundaries to reduce the GMPP search space.
  • Active voltage regulation is employed to enforce operation within the narrowed zone, transforming the P-V curve.
  • The framework is integrated with conventional MPPT algorithms (MSMPP-P&O, MSMPP-INC).

Main Results:

  • MSMPP algorithms achieved 50% faster tracking speeds (64 ms) compared to conventional P&O (122 ms).
  • Power losses were reduced to below 2% under static shading and less than 1.5 W under dynamic shading.
  • The framework demonstrated robustness and outperformed conventional methods significantly in dynamic shading scenarios.

Conclusions:

  • The MSMPPT framework effectively transforms multi-peak P-V curves into single-peak profiles for reliable GMPP tracking.
  • It offers a simple, hardware-independent solution to improve PV system efficiency and reliability under partial shading.
  • This approach provides a cost-effective and scalable method to enhance PV energy harvest in complex environments.