Accurate parameter identification of solar cells and photovoltaic modules under real conditions using a new Differential Evolution approach

This is the authors' abstract. We don't add key points for this paper.

The global shift towards solar energy has intensified the need for advanced research on high-efficiency photovoltaic (PV) systems. Accurate extraction of PV parameters from current-voltage curves is critical for precise simulation, evaluation, and optimization of PV systems. Although numerous methods exist, many suffer from instability, premature convergence, or limited applicability to complex models. In this paper Progressive Differential Evolution with Adaptive Mutation (Pro-DEAM) is presented which eliminates the aforementioned limitations and introduces a new optimization algorithm generation. Pro-DEAM integrates two novel mutation operators: a hybrid DE/rand-to-best/1/bin to strengthen local exploitation and diversity, and a modified DE/rand/2/bin equipped with random scaling factors to dynamically promote exploration. These two strategies are adaptively weighted with exponential increasing to achieve the best trade-off between exploration and exploitation. The efficiency of Pro-DEAM is proved by extensive experiments of parameter extraction of various PV models, including complex multijunction solar cells (15 parameters) as opposed to many more complex five parameters models in traditional. The results indicate that the proposed Pro-DEAM algorithm consistently attains the lowest root mean square error (RMSE) among existing state-of-the-art approaches, highlighting its remarkable accuracy and computational efficiency. Additionally, detailed statistical analysis results confirm that it is highly robust and reliable for various PV module complexities and climates. The proposed algorithm addresses key limitations of existing methods and establishes a new benchmark for stability and convergence in PV parameter extraction. Its adaptive and dynamic framework makes it a powerful tool for both standard and advanced PV technologies, paving the way for more accurate and efficient solar energy systems.