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

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.

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

Trends in Sciences ◽

10.48048/tis.2021.712 ◽

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

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Optimal Design of PID Controller for Doubly-Fed Induction Generator-Based Wave Energy Conversion System Using Multi- Objective Particle Swarm Optimization

Journal of Technology Innovations in Renewable Energy ◽

10.6000/1929-6002.2014.03.01.4 ◽

2014 ◽

Vol 3 (1) ◽

pp. 21-30 ◽

Cited By ~ 1

Author(s):

Adel Elgammal ◽

Keyword(s):

Particle Swarm Optimization ◽

Optimal Design ◽

Pid Controller ◽

Induction Generator ◽

Doubly Fed Induction Generator ◽

Wave Energy Conversion ◽

Swarm Optimization ◽

Conversion System ◽

Energy Conversion System ◽

Doubly Fed

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Discrete-Time Optimal Control of Photovoltaic Grid-Connected Inverter Based on Particle Swarm Optimization

Mathematical Problems in Engineering ◽

10.1155/2014/249312 ◽

2014 ◽

Vol 2014 ◽

pp. 1-10 ◽

Cited By ~ 2

Author(s):

Xinrui Liu ◽

Guangru Zhang ◽

Dongsheng Yang ◽

Tongyu Shi ◽

Xusheng He

Keyword(s):

Optimal Control ◽

Particle Swarm Optimization ◽

Discrete Time ◽

Control Method ◽

Particle Swarm ◽

Control Process ◽

Swarm Optimization ◽

Performance Matrix ◽

Time Optimal ◽

Grid Connected Inverter

This paper is concerned with the problem of optimal control of photovoltaic grid-connected inverter. Firstly, the discrete-time nonlinear mathematical model of single-phase photovoltaic grid-connected inverter in the rotating coordinate system is constructed by the Delta operator, which simplifies the control process and facilitates direct digital realization. Then, a novel optimal control method which is significant to achieve trajectory tracking for photovoltaic grid-connected inverter is developed by constructing a control Lyapunov functional against the difficulty of solving HJB (Hamilton-Jacobi-Bellman) partial differential equations. More importantly, the performance matrix of the controller which is very meaningful to many performance indicators of the system is also optimized via the particle swarm optimization. Finally, two numerical examples are provided to illustrate the effectiveness of the proposed method.

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

Bulletin of Electrical Engineering and Informatics ◽

10.11591/eei.v10i5.2843 ◽

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.

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