904 - Multi-Objective Particle Swarm Optimization for Controlling Active and Reactive Power
Elmostafa Chetouani, Youssef Errami, Abdellatif Obbadi, Smail Sahnoun
Title: 904 - Multi-Objective Particle Swarm Optimization for Controlling Active and Reactive Power in a Wind Energy Conversion System
Presented in:
8th International Renewable and Sustainable Energy Conference #IRSEC20
Online, November 25-28, 2020
Special Session 3 – Wind Energy: Electric Production and Grid Integration
Presented by:
Elmostafa Chetouani
Laboratory: Electronics, Instrumentation and Energy, Faculty of Science, Chouaib Doukkali University,
El jadida, Morocco
Abstract:
This work aims to control the active and reactive power of the rotor side converter for doubly-fed induction generator integrated into a wind energy system by using indirect field-oriented control based on the Proportional-Integral controllers. The generator is driven by the output rotation speed of the gearbox and is fed by the aerodynamic generated power by the wind turbine. A maximum power point tracking strategy is used to maximize the mechanical power. However, the vector control shows its limited performances for the system under parameter variations. Multi-Objective Particle Swarm Optimization (MO-PSO) is suggested to enhance the dynamic performances and the robustness of the system. This work highlights the performances of the proposed method for tuning automatically the PI control gains against classical PI adjusted by poles compensation strategy. Simulations are carried out on MATLAB-SIMULINK software."