Parameter Recognition of Solar Cell Model Based on ICOOT Algorithm

Solar cell model parameter recognition is crucial for accurate photovoltaic power generation prediction, necessitating high accuracy in identification. To tackle this challenge, we introduce the refined Chicken Optimization Algorithm (ICOOT), specifically tailored for solar cell model parameter identification. Initially, we validate the algorithm's superiority by comparing it against existing algorithms, followed by further evaluation using measured data from Radiation Tolerant Cell (RTC) solar cells. After comparing it with four alternative methods, the superiority of the introduced ICOOT model is clearly demonstrated. We demonstrate its practical applicability by selecting French RTC silicon solar cells for parameter identification. A comparative analysis, including Root Mean Square Error (RMSE), is conducted against six other models, highlighting the proposed model's lower RMSE and broader applicability.