SCSO: snake optimization with sine-cosine algorithm for parameter extraction of solar photovoltaic models

Abstract

This paper proposes a new hybrid Snake Optimization combined with the Sine–Cosine Algorithm (SCSO) and conducts a qualitative analysis of the improved algorithm using CEC2022 test functions, demonstrating its superior performance. The SCSO is applied to the extraction of unknown parameters in six solar photovoltaic module models, including the Single Diode Model (SDM), Double Diode Model (DDM), and PV module model. Compared to other metaheuristic algorithms, the SCSO achieves faster and more precise parameter extraction, as demonstrated on two commercial PV models, TFST 40 and MCSM 55.