Parameter estimation of photovoltaic models based on a novel improved transient search optimization algorithm

Abstract Accurate estimation of the model parameters is of great significance for in-depth insight into the characteristics of photovoltaic (PV) cells and accurate prediction of their performance. However, most existing PV parameter extraction methods suffer from low extraction accuracy and are prone to falling into local optima. To address this issue, we put forward innovative enhancements to transient search optimization (TSO) algorithm, giving rise to a novel ITSO algorithm. Our approach involves proposing an energy storage-step optimization strategy and introducing a terminal optimization mechanism to improve the algorithm’s search efficiency and convergence speed. After evaluation using the CEC2022 benchmark suite, the ITSO method was applied to estimate the parameters of six PV cell and module models based on the three-diode model. A comprehensive comparison of the proposed ITSO algorithm with eight state-of-the-art algorithms as well as eight peer algorithms shows that ITSO excels in estimation accuracy, precisely determining PV model parameters. This validates its effectiveness for PV model parameter estimation.