A growing trend of introducing new metaheuristic algorithms and their improvements is
observed with almost the same inherited weaknesses. The main reason is that a few studies …

In this paper, a novel nature-inspired meta-heuristic known as Crested Porcupine Optimizer
(CPO) and inspired by various defensive behaviors of crested porcupine (CP) is proposed …

One of the greatest challenges for widespread utilization of solar energy is the low
conversion efficiency, motivating the needs of developing more innovative approaches to …

The parameter identification problem of photovoltaic (PV) models is classified as a complex
nonlinear optimization problem that cannot be accurately solved by traditional techniques …

Accurately estimating the unknown parameters of the photovoltaic (PV) models based on the
measured voltage-current data is a challenging optimization problem due to its high …

This study presents the parameter extraction of photovoltaic (PV) cells and modules using a
new hybrid metaheuristic algorithm developed based on the white shark optimizer (WSO) …

Abstract Model parameters estimation of solar photovoltaic (PV) cells/modules using real
current–voltage (I–V) data is a critical task for the performance of PV systems. Therefore …

Optimization problems are prevalent in a variety of real-world applications, including
medical, engineering, chemical, and others, and must be precisely solved to enhance the …

The paper addresses the limitations of the Moth-Flame Optimization (MFO) algorithm, a meta-
heuristic used to solve optimization problems. The MFO algorithm, which employs moths' …

The primary objective of this study is to investigate the effects of the Fractional Order Kepler
Optimization Algorithm (FO-KOA) on photovoltaic (PV) module feature identification in solar …