Table 2.

Modern algorithms utilized in recent years for the purpose of PV parameter estimation problems.

Reference	Algorithm	Diode models	Remark
[63]	Cuckoo Search Optimizer (CSO), improved CSO (ICSO) and modified CSO (MCSO)	SDM and DDM	ICSO achieves better accuracy and dependability than CSO and MCSO.
[50]	Supply-Demand-Based Optimization Algorithm (SDOA)	TDM	In the process of PV parameter extraction, SDOA is frequently used as a competitive optimizer.
[64]	Turbulent Flow of Water-Based Optimization (TFWO)	SDM, DDM and TDM	The suggested TFWO achieves close (IV) curves compared to other optimization techniques.
[65]	Harris Hawk Optimization (HHO)	TDM	The outcome presents that the recommended approach can quickly notice the electrical constraints of any marketable PV panel.
[66]	Gorilla Troops Optimization (GTO)	SDM and DDM	GTO is proven using a variety of irradiations and temperatures, all of which result in an extremely high degree of similarity among the emulated and investigational (IV) curves.
[67]	Forensic-Based Investigation Algorithm (FBIA),	SDM, DDM and TDM	The FBIA results are remarkably consistent because the SD of fitness values across 30 runs is fewer than 1 × 106 for all three models.
[68]	Closed-loop PSO (CLPSO) and elephant herd-optimization (EHO)	DDM and TDM	The EHO is superior to the CLPSO with regards to the quality of the solutions it generates and the merging rates it achieves when viewed from the perspective of soft computing standards.
[69]	Metaphor-Less Rao-ii and Rao-iii Algorithms	SDM, DDM and TDM	As per the findings of the statistical analysis, the suggested algorithms, R-ii and R-iii, demonstrate a superior level of performance to those of well-established approaches.
[70]	Grasshopper Optimization Algorithm (GOA)	TDM	The usefulness of the GOA photovoltaic (PV) model is estimated by contrasting the results of the simulation with the outcomes of PV models that are based on other optimization approaches. The results are within a range that is considered acceptable. The suggested GOA can be used to optimize RE systems, and smart grids.
[71]	Improved Bonobo Optimizer (IBO)	SDM, DDM and TDM	All of the suggested IBO's results outperformed those of other algorithms when compared.
[72]	Grey Wolf Optimization (GWO)	SDM	GWO outperforms PSO in fitness. The model has the lowest I–V and P–V errors.
[73]	Slime Mould Algorithm (SMA)	SDM, DDM and TDM	Given the observations and comments, the suggested SMA may provide superior parameter estimates and merging speed, as evidenced in the converging curve for every PV model.
[74]	Adaptive Compass Search (ACS)	DDM	The ACS method can significantly increase the capacity to conduct global exploration by generating an adaptable sequence of exploration directions based on prior searching results.
[75]	Fuzzy Adaptive Differential Evolution Algorithm (FADE)	SDM	According to the findings, the FADE algorithm is an efficient way for evaluating the elements of PV module models and has a higher level of robustness when it comes to identifying parameters.
[76]	Genetic Algorithm Based on Non-Uniform Mutation (GAMNU)	SDM, DDM	The statistical outcomes states that the suggested method overtakes existing advanced algorithms in accuracy and reliability. The suggested approach can extract solar PV model parameters.
[77]	Modified-Stochastic-Fractal-Search Algorithm (MSFS)	SDM, DDM	RMSE values among models and actual data are 10−2 or 10−3. Therefore, suggested approach is utilized to estimate solar cell and PV module parameters due to its efficacy and practicability.
[78]	Northern Goshawk Optimization (NGO)	TDM	The outcomes of the simulation demonstrate that the NGO is higher to other competed optimization algorithms in terms of how quickly and accurately they converge on a solution.
[79]	Performance-Guided JAYA (PGJAYA)	SDM, DDM	The PGJAYA approach for PV module model parameters appears promising. Additionally, the PGJAYA method can be considered an effective strategy for dealing with several other optimization issues in the energy system.
[80]	Enhanced Gradient Based Optimizer (EGBO)	SDM, DDM	The findings point to the newly presented EGBO as being superior to the original GBO algorithm, and it does rather well when compared against some of the other approaches that are described in the relevant academic literature.
[81]	Coyote Optimization Algorithm (COA)	SDM, DDM	Both models had fitness standard deviations (STDs) less than 1 × 10−5. This shows the algorithm's consistent outcomes.
[82]	Marine Predators Algorithm (MPA)	SDM, DDM and TDM	The MPA achieves outcomes that are comparable to those achieved by other optimization methods described in the research literature. The suggested MPA has strong statistical support and convergence for a variety of operational situations, including those with low and high irradiance.
[83]	Supply-Demand-Based Optimization (SDO)	SDM, DDM and TDM	The SD of the fitness values are lower than 1 × 10−18, 10−17, and 10−6, respectively, for three models, which indicates that the SDO is superior. These values were calculated using a total of 30 runs.