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Solar energy industry

Enhanced Algorithm for Photovoltaic Model Parameter Identification

Strategic Insights

— 1 min read

Researchers at Nanchang Hangkong University have made significant discoveries in the field of mathematics, specifically in the area of photovoltaic (PV) system modeling. They have developed an enhanced weighted-mean-of-vectors optimization (EINFO) algorithm to efficiently determine the unknown parameters in PV systems. This breakthrough is essential for simulating, controlling, and evaluating PV systems, which are crucial for converting solar energy into electrical energy. The new algorithm has been experimentally applied to three types of PV models, demonstrating its accuracy and stability in parameter identification.

Key Takeaways:

  • The EINFO algorithm introduces a Lambert W-based explicit objective function for the PV model, enhancing the computational accuracy of the algorithm's population fitness.
  • The EINFO algorithm consistently outperforms other methods in terms of convergence speed, accuracy, and stability, achieving root mean square errors (RMSEs) of 7.7301E-04, 6.8553E-04, and 2.0608E-03 for the single-diode, double-diode, and PV-module models, respectively.
  • The EINFO algorithm maintains high accuracy across varying temperatures and irradiation levels, making it a highly competitive and practical approach for parameter identification in diverse types of PV models.
  • The research was supported by Fight for Sight and conducted by Peng Min, Ying Chen, Cheng Tao, Zeye Long, Huiling Chen, Ali Asghar Heidari, Shuihua Wang, and Yudong Zhang from Nanchang Hangkong University.

Statistics:

  • The RMSEs for the single-diode, double-diode, and PV-module models were 7.7301E-04, 6.8553E-04, and 2.0608E-03, respectively.
  • The EINFO algorithm achieved better performance in convergence speed, accuracy, and stability compared to other methods.
  • The research utilized three commercial PV modules (ST40, SM55, and KC200GT) for experimental findings.

Sources:

  • NewsRx. Researchers from Nanchang Hangkong University Describe Findings in Mathematics (Parameter Identification of Photovoltaic Models Using an Enhanced Info Algorithm). Mathematics Week. November 4, 2025; p 398.
  • Peng Min et al. Parameter Identification of Photovoltaic Models Using an Enhanced Info Algorithm. CAAI Transactions on Intelligence Technology, 2025.
  • CAAI Transactions on Intelligence Technology, Wiley, 111 River St, Hoboken 07030-5774, NJ, USA.

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