scholarly journals Optimal tuning of PI controllers using adaptive particle swarm optimization for doubly-fed induction generator connected to the grid during a voltage dip

2021 ◽  
Vol 10 (5) ◽  
pp. 2367-2376
Author(s):  
Elmostafa Chetouani ◽  
Youssef Errami ◽  
Abdellatif Obbadi ◽  
Smail Sahnoun
Keyword(s):  
Particle Swarm Optimization ◽  
Wind Energy ◽  
Maximum Power ◽  
Induction Generator ◽  
Doubly Fed Induction Generator ◽  
Swarm Optimization ◽  
Adaptive Particle Swarm Optimization ◽  
Voltage Dip ◽  
Pi Controllers ◽  
Doubly Fed

This paper proposes the adaptive particle swarm optimization (APSO) technique to control the active and reactive power produced by a variable wind energy conversion system and the exchanged power between the electric grid and the system during a voltage dip (VD). Besides, to get the variable speed wind energy maximum power, a maximum power point (MPP) methodology is utilized. The system under study is a 5 MW wind turbine connected via a gearbox to a doubly-fed induction generator (DFIG). The DFIG stator is branched directly to the electrical network, while the Back-to-Back converters couple the rotor to the grid. The decoupled vector control of the rotor side converter and the grid side converter is established primarily by a conventional proportional-integral (PI) and a second level by an intelligent PI whose gains are tuned using the proposed control. The performances and results obtained by APSO tuned PI controllers are analyzed and compared with those attained by classical PI controllers through the MATLAB/Simulink. The superiority of the advised technique is examined during a two-phase short-circuit fault condition and confirmed by the reduced oscillations.

scholarly journals Hybrid Control using Adaptive Particle Swarm Optimization and Integral Backstepping Control of Grid-connected Doubly Fed Induction Generator

2021 ◽  
Vol 18 (23) ◽  
pp. 712
Author(s):  
Elmostafa Chetouani ◽  
Youssef Errami ◽  
Abdellatif Obbadi ◽  
Smail Sahnoun
Keyword(s):  
Particle Swarm Optimization ◽  
Wind Energy ◽  
Hybrid Control ◽  
Particle Swarm ◽  
Backstepping Control ◽  
Induction Generator ◽  
Doubly Fed Induction Generator ◽  
Swarm Optimization ◽  
Adaptive Particle Swarm Optimization ◽  
Doubly Fed

We proposed an analysis of a hybrid control of active and reactive power for a doubly-fed induction generator for variable velocity wind energy injection into the electrical grid using a combination of adaptive particle swarm optimization and integral backstepping control in this paper. The stability of the Lyapunov function is utilized to establish the latter. Six controllers are developed as part of the proposed control process: The first is concerned with the maximum PowerPoint. The stator powers are managed by the second and third regulators, which are performed by the optimal PI controller using adaptive particle swarm optimization. The DC link voltage is kept constant by the fourth controller. The fifth and sixth are employed to pilot the rotor powers and ensure that the power factor is maintained to 1. These three controllers are synthesized by using the nonlinear integral backstepping control. These control strategies show excellent results compared to field-oriented control under a variable wind speed profile and changing generator settings in a Matlab/Simulink environment. According to the test findings, using integral backstepping, the overshoot of the DC-link voltage is decreased by 99.16 %. Furthermore, the particle swarm optimization reduces its time to reach the equilibrium state to 4.3 m s and demonstrates robustness against parameter generator changes. HIGHLIGHTS The regulation of the produced power by the wind energy conversion system (WECS) based on a doubly-fed induction generator is becoming increasingly important to researchers. This system is modeled and simulated in the Matlab/Simulink software environment to apply the proposed control In order to extract the maximum power from the variable wind source, a maximum power point tracking method is developed based on the PI controller For piloting the wind energy system conversion (WECS) based on a DFIG, a combination of the integrated Backstepping controller and adaptive PSO is proposed and realized in this paper Robustness tests are established by adjusting the generator parameters, and a comparative study is conducted to verify the superiority of the suggested control over the indirect vector control GRAPHICAL ABSTRACT

Particle Swarm Optimization for Discrete-Time Inverse Optimal Control of a Doubly Fed Induction Generator

2013 ◽  
Vol 43 (6) ◽  
pp. 1698-1709 ◽  
Author(s):  
Riemann Ruiz-Cruz ◽  
Edgar N. Sanchez ◽  
Fernando Ornelas-Tellez ◽  
Alexander G. Loukianov ◽  
Ronald G. Harley
Keyword(s):  
Optimal Control ◽  
Particle Swarm Optimization ◽  
Discrete Time ◽  
Particle Swarm ◽  
Induction Generator ◽  
Doubly Fed Induction Generator ◽  
Inverse Optimal Control ◽  
Swarm Optimization ◽  
Doubly Fed

scholarly journals Enhancement transient stability of wind power system of doubly-fed induction generator using STATCOM and PI controller

2019 ◽  
Vol 10 (4) ◽  
pp. 1977
Author(s):  
Shaimaa Shukri A. Alhalim ◽  
Lubna A. Alnabi
Keyword(s):  
Particle Swarm Optimization ◽  
Power System ◽  
Wind Power ◽  
Particle Swarm ◽  
Pi Controller ◽  
Induction Generator ◽  
Doubly Fed Induction Generator ◽  
Swarm Optimization ◽  
Wind Power System ◽  
Doubly Fed

Wind energy is a promising source of electricity in the world and fastest-growing. Doubly-Fed Induction Generator (DFIG) systems dominate and widely used in wind power system because of their advantages over other types of generators, such as working at different speeds and not needing continuous maintenance. In this paper used the PI controller and Flexible AC Transmission System (FACTS) device specifically static compensator (STATCOM) to investigate the effect of the controller and FACTS device on the system. PI controller tuning by Particle Swarm Optimization technique (PSO) to limit or reduced the fault current in (DFIG) system. The responses of different kinds of faults have been presented like; two lines to ground faults and three lines to ground faults at different operating conditions. Faults are applied to three proposed controllers; the first controller is the Proportional-Integral (PI), the second controller is PI-controller based on Particle Swarm Optimization (PI-PSO) technique and STATCOM. A reactive power static synchronous compensator (STATCOM) is used, the main aim for the use of STATCOM is to improve the stability of a wind turbine system in addition to this is improving voltages profile, reduce power losses, treatment of power flow in overloaded transmission lines. The simulation programming is implemented using MATLAB program.

scholarly journals Design and investigations of MPPT strategies for a wind energy conversion system based on doubly fed induction generator

2020 ◽  
Vol 10 (5) ◽  
pp. 4770 ◽  
Author(s):  
Bouchaib Rached ◽  
Mustapha Elharoussi ◽  
Elhassane Abdelmounim
Keyword(s):  
Wind Speed ◽  
Wind Energy ◽  
Energy Conversion ◽  
Fuzzy Logic Controller ◽  
Maximum Power ◽  
Induction Generator ◽  
Doubly Fed Induction Generator ◽  
Wind Energy Conversion ◽  
Point Tracking ◽  
Doubly Fed

The purpose of this work is to design and to discuss various strategies to optimize the production of a wind energy conversion chain based on the doubly fed induction generator (DFIG), by capturing the maximum power at the wind turbine, using maximum power point tracking (MPPT) and pitch control. The proposed controls allow the generator to monitor the optimal operating points of the turbines regardless of wind speed variations, system parameters disturbance, and parameters variation. Simulation of WECS based on a 1.5 MW wound rotor induction generator under MATLAB/SIMULINK is carried out using the PI controller (PIC), RST controller and fuzzy logic controller (FLC). Analysis and comparisons are made for different operating scenarios: Reference tracking, robustness under variable wind speed conditions and parameters variation. The application of FLC provides a very interesting outcome for the robustness and the dynamic challenges.

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