Maximizing Wind Energy Efficiency Through ACO and ANN-Based MPPT Algorithms

The wind energy sector is experiencing continuous improvement aimed at increasing the exploitation of this type of energy by optimizing its energy efficiency as much as possible. The energy efficiency of wind power systems is study by evaluating two MPPT algorithms is presented. The objective focuses on two approaches: The use of artificial neural networks (ANN) and the ant colony optimization (ACO) algorithm. The adaptability and learning capabilities inherent in these methods and their characteristics is explained. This study aims to provide a performance analysis of these various MPPT algorithms and evaluate their accuracy in tracking the maximum power point, their effectiveness in reducing energy losses and their stability as well as improving energy efficiency.