Modern methods of maximum power point tracking in photovoltaic systems: classification, comparison, and application under partial shading conditions

Authors

  • Janusz Mroczka Department of Control Science and Engineering, Opole University of Technology, ul. Prószkowska 76, 45-758 Opole, Poland.
  • Kinga Kaczmarek Department of Electronic and Photonic Metrology, Faculty of Electronics, Photonics and Microsystems, Wroclaw University of Science and Technology, Wroclaw, Poland

DOI:

https://doi.org/10.24425/mms.2025.154674

Keywords

Maximum Power Point Tracking, MPPT, photovoltaic systems, PV, partial shading conditions, PSC, global maximum power point, GMPP, optimisation algorithms, artificial intelligence, hybrid methods

Abstract

Maximum Power Point Tracking (MPPT) is essential for optimising the efficiency of photovoltaic (PV) systems. Selecting the appropriate MPPT algorithm allows for better utilisation of solar energy. Under Partial Shading Conditions (PSC), the power-voltage (P-V) curve becomes nonlinear, leading to multiple Local Maximum Power Points (LMPP), which complicates the identification of the Global Maximum Power Point (GMPP) and reduces system efficiency. This paper reviews and classifies MPPT methods into four categories: classical, metaheuristic, AI-based, and hybrid. These approaches are compared in terms of tracking accuracy, speed, adaptability to changing conditions, and robustness. Special focus is placed on methods that maintain performance under PSC, minimising energy losses and improving system stability. The goal is to highlight the strengths and limitations of each method and suggest directions for further optimisation to enhance the reliability and overall efficiency of PV systems in real-world conditions.

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Published

2025-09-30

How to Cite

Mroczka, Janusz, and Kinga Kaczmarek. “Modern Methods of Maximum Power Point Tracking in Photovoltaic Systems: Classification, Comparison, and Application under Partial Shading Conditions”. Metrology and Measurement Systems, vol. 32, no. 3, Sept. 2025, pp. art. no. 5, 1-18, doi:10.24425/mms.2025.154674.

Issue

Vol. 32 No. 3 (2025)

Section

Articles