Adaptive Harris hawks optimization with persistent trigonometric differences for photovoltaic model parameter extraction

In this paper, an adaptive Harris hawk optimization with persistent trigonometric (sine-cosine)-differences (ADHHO) is proposed for parameter identification of Photovoltaic (PV) systems. In the optimized version of HHO, we innovatively propose the persistent-trigonometric-differences mechanism for improving the global search capability of HHO; moreover, we improve the energy factor in the original algorithm so that ADHHO obtains a better balance between exploration and exploitation. Note that the proposed method can obtain lower CPU time in parameter extraction for the three-diode and PV module models with an enhanced parameter extraction performance. To validate the performance of ADHHO, we verified the parameter extraction capability of the single-diode model (SDM), double-diode model (DDM), triple-diode model (TDM), and PV module model (PVM), respectively. Further, we verified the parameter extraction effect of ADHHO in three commercial cells with different light intensity and temperature conditions. Experiments show that the method proposed in this paper can reasonably simulate the output performance of solar PV cells and can be used as a trustworthy method for the extraction of unknown parameters of solar PV systems.