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<p>When maximum power point tracking (MPPT) is implemented in practical photovoltaic systems, rapid variations in irradiance and temperature, as well as partial shading conditions, can create multiple local maxima in the power–voltage curve and degrade the performance of conventional tracking methods. In this study, a fuzzy logic–based MPPT controller is adopted and its scaling factors and membership-function spread parameters are optimized using an improved Harris Hawks Optimization (I-HHO) algorithm to avoid subjective parameter tuning. In addition, two practical modifications are introduced: a soft dead zone to reduce steady-state ripple near the maximum power point and a lightweight global scanning mechanism with adaptive resolution to improve tracking under severe irradiance changes and partial shading. The proposed method is evaluated under several operating scenarios, including irradiance and temperature variations and partial shading, and compared with the conventional P&amp;O and INC methods. The results show that the multi-scenario objective function improves from 0.085267 in the baseline fuzzy controller to 0.071317 in the optimized version (about 16.36% improvement). In addition, the ripple in the temperature-step scenario decreases from 16.254% to 9.072%, while the settling time under partial shading improves from 0.078&#xa0;s to 0.066&#xa0;s. These results indicate that the proposed approach provides more stable tracking and improved dynamic performance for MPPT in practical operating conditions.</p>

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Optimal design of a fuzzy MPPT controller using an improved harris hawks optimization for photovoltaic systems

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年6月15日

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  • Tohid Hanafi,
  • Ali Asghar Shojaei,
  • Javad Mashayekhifard,
  • Amin Honarbakhsh

摘要

When maximum power point tracking (MPPT) is implemented in practical photovoltaic systems, rapid variations in irradiance and temperature, as well as partial shading conditions, can create multiple local maxima in the power–voltage curve and degrade the performance of conventional tracking methods. In this study, a fuzzy logic–based MPPT controller is adopted and its scaling factors and membership-function spread parameters are optimized using an improved Harris Hawks Optimization (I-HHO) algorithm to avoid subjective parameter tuning. In addition, two practical modifications are introduced: a soft dead zone to reduce steady-state ripple near the maximum power point and a lightweight global scanning mechanism with adaptive resolution to improve tracking under severe irradiance changes and partial shading. The proposed method is evaluated under several operating scenarios, including irradiance and temperature variations and partial shading, and compared with the conventional P&O and INC methods. The results show that the multi-scenario objective function improves from 0.085267 in the baseline fuzzy controller to 0.071317 in the optimized version (about 16.36% improvement). In addition, the ripple in the temperature-step scenario decreases from 16.254% to 9.072%, while the settling time under partial shading improves from 0.078 s to 0.066 s. These results indicate that the proposed approach provides more stable tracking and improved dynamic performance for MPPT in practical operating conditions.