A reliable optimization framework for parameter identification of single‐diode solar photovoltaic model using weighted velocity‐guided grey wolf optimization algorithm and Lambert‐W function

Abstract In estimating the parameters of five unknown Single‐Diode Model (SDM) solar photovoltaic (PV) model, a non‐linear equation for PV cell current is typically utilized. Then, error between estimated and measured computed using objective function called Root‐Mean‐Square‐Error (RMSE). order to compute in SDM, an iterative method built on Lambert‐W presented this study. Along with Lamber‐W function, optimization algorithm Weighted Velocity‐Guided Grey Wolf Optimizer (WVGGWO) used identify lumped SDM module. The proposed WVGGWO updated version original (GWO). position update GWO has been modified, weightage provided wolf hierarchy. Additionally, by emphasizing lengthening each leading wolf's steps towards others earlier search while shortening reaching later iterations, improves both exploration exploitation GWO. Four case studies are considered testing validity along function. performance approach compared seven other well‐known algorithms. results demonstrate that suggested produces better outcomes than many