Application research of improved red tailed eagle algorithm inspired by biomechanics in parameter identification of photovoltaic cells
Abstract
In response to the problems of insufficient accuracy, slow speed, and poor stability in the current parameter identification process of photovoltaic cells, this study designs a parameter identification method based on Improved Red-tailed Hawk (IRTH) algorithm optimization. Firstly, four photovoltaic cell models and one photovoltaic module model are constructed, and corresponding objective functions are established. Secondly, combining Gaussian mutation and cuckoo search ideas, a Gaussian cuckoo mutation mechanism is proposed to reprocess positional information, thereby optimizing the algorithm population and improving solving efficiency. And further analogize photovoltaic cell units as biomaterial units with specific mechanical response characteristics. By studying its current voltage characteristics, the dynamic response of its photoelectric conversion unit under different lighting and load conditions is revealed, similar to the nonlinear and time-dependent characteristics exhibited by biomaterials under external forces. Again, based on the idea of individual extinction in the white whale algorithm, a red-tailed hawk descent mechanism is proposed to improve the convergence speed. The results of the effectiveness test on the proposed IRTH algorithm showed that it converged the fastest and obtained significantly smaller root mean square errors than other optimization algorithms. Finally, the IRTH was further utilized to parameter identification in RTC France photovoltaic cells and photovoltaic modules Photowatt-PWP 201, with an average improvement rate of 79.94%. Therefore, the improved algorithm has better parameter identification effect and higher reliability.
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