Frontiers in Energy Research (Sep 2022)

Comparative study of modern heuristic algorithms for global maximum power point tracking in photovoltaic systems under partial shading conditions

  • Kangshi Wang,
  • Kangshi Wang,
  • Jieming Ma,
  • Ka Lok Man,
  • Kaizhu Huang,
  • Xiaowei Huang

DOI
https://doi.org/10.3389/fenrg.2022.946864
Journal volume & issue
Vol. 10

Abstract

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Under partial shading conditions (PSCs), photovoltaic (PV) generation systems exhibit multiple local and a single global maximum power point. Consequently, global maximum power point tracking (GMPPT) is required to improve the performance of PV systems in such scenarios. This paper comparatively studies and evaluates the tracking performance of modern heuristic-optimization-based GMPPT techniques. Monte Carlo method is used to statistically analyze different methods. Simulation and experimental results indicate that many of the algorithms have difficulties in balancing the explorative and exploitative searching behaviors. Therefore, we propose a variable vortex search (VVS), which is capable of improving the performance of GMPPT by using a variable step size and deterministic starting points. This paper will aid researchers and practical engineers to gain a thorough understanding on how to use modern heuristic algorithms for maximum power out of PV systems. Furthermore, it offers a comprehensive guidance on how to perform efficiently GMPPT in the PV systems under PSCs.

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