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<p>Maximum power point tracking (MPPT) is a pivotal technology for photovoltaic (PV) systems. Due to variations in light intensity and temperature, the output characteristic curve of the photovoltaic system exhibits multi-peak phenomena, and traditional MPPT algorithms perform poorly in complex and changing environments. Therefore, this paper proposes an MPPT method grounded on an improved RIME optimization algorithm (IRIME). This approach enhances the algorithm’s exploratory capabilities by incorporating logistic mapping during the initialization stage. Furthermore, it optimizes the algorithm’s parameters through sequences generated by piecewise mapping, thereby realizing a harmonious balance between global exploration and local exploitation. Additionally, the introduction of an adaptive inertia weight dynamically adjusts the search strategy, thereby increasing the adaptability, convergence speed, and search efficiency of algorithm. Compared to PSO-MPPT and RIME-MPPT, the proposed method reduced the average tracking time by 0.085&#xa0;s and 0.425&#xa0;s, respectively. Additionally, in terms of maximum output power, the proposed method achieved an average improvement of 0.97% and 3.48% over the aforementioned methods, respectively. Particularly in PV system simulations under varying irradiance and temperature conditions, the proposed method consistently achieves the best results, verifying its efficient, stable, and fast-converging characteristics in MPPT strategies for PV systems.</p>

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An improved RIME optimization algorithm based maximum power point tracking method for photovoltaic system under partially shading condition

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年6月4日

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  • Yonggang Wang,
  • Wenjia Zhang,
  • Yuanchu Ma,
  • Yanan Yu,
  • Haoran Chen

摘要

Maximum power point tracking (MPPT) is a pivotal technology for photovoltaic (PV) systems. Due to variations in light intensity and temperature, the output characteristic curve of the photovoltaic system exhibits multi-peak phenomena, and traditional MPPT algorithms perform poorly in complex and changing environments. Therefore, this paper proposes an MPPT method grounded on an improved RIME optimization algorithm (IRIME). This approach enhances the algorithm’s exploratory capabilities by incorporating logistic mapping during the initialization stage. Furthermore, it optimizes the algorithm’s parameters through sequences generated by piecewise mapping, thereby realizing a harmonious balance between global exploration and local exploitation. Additionally, the introduction of an adaptive inertia weight dynamically adjusts the search strategy, thereby increasing the adaptability, convergence speed, and search efficiency of algorithm. Compared to PSO-MPPT and RIME-MPPT, the proposed method reduced the average tracking time by 0.085 s and 0.425 s, respectively. Additionally, in terms of maximum output power, the proposed method achieved an average improvement of 0.97% and 3.48% over the aforementioned methods, respectively. Particularly in PV system simulations under varying irradiance and temperature conditions, the proposed method consistently achieves the best results, verifying its efficient, stable, and fast-converging characteristics in MPPT strategies for PV systems.