This article presents a comparative analysis of the latest swarm-based optimization
approaches under partial shading conditions (PSCs) for maximum power point tracking …

To efficiently and accurately track the Global Maximum Power Point (GMPP) of the PV
system under Varying Environmental Conditions (VECs), numerous hybrid Maximum Power …

This paper proposes an optimal energy management strategy (EMS) for DC microgrid. The
studied system presents a commercial building power system that combines a photovoltaic …

This paper proposes a new Multi-Objective Equilibrium Optimizer (MOEO) to handle
complex optimization problems, including real-world engineering design optimization …

This study presents the K-means clustering-based grey wolf optimizer, a new algorithm
intended to improve the optimization capabilities of the conventional grey wolf optimizer in …

Feature Selection (FS) is an essential process that is implicated in data mining and machine
learning for data preparation by removing redundant and irrelevant features, thereby falling …

Optimization is a key technique for maximizing or minimizing functions and achieving
optimal cost, gains, energy, mass, and so on. In order to solve optimization problems …

Parameter identification and accurate photovoltaic (PV) modeling from basic I–V information
are necessary for simulation, optimization, and control of the PV systems. Therefore, this …

Identifying and estimating uncertain and dynamic photovoltaic characteristics with high
accuracy is important when modeling solar photovoltaic (PV) systems. It is critical to have …

The solar photovoltaic (PV) parameter estimation/identification is a complicated optimization
process that directly affects the performance of PV systems if the internal parameters of PV …