Tuning PI Controller Based on Multiobjective Optimization Approaches for Speed Control of PMSG Wind Turbine

Putri, Ratna Ika; Jasa, Lie; Pujiantara, Margo; Priyadi, Ardyono; Purnomo, Mauridhi Hery

doi:10.15866/ireaco.v8i4.7201

Cited by 13 publications

(7 citation statements)

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“…The performance of each particle is measured using a predefined objective (fitness) function, which define the characteristics of the optimization problem [25].…”

Section: Particle Swarm Optimization Algorithmmentioning

confidence: 99%

A robust nonlinear control strategy of a PV System connected to the three-phase grid based on backstepping and PSO technique

Zouga

Benchagra

Ailane

2021

IJPEDS

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This article presents a robust non-linear control technique of the three-phase photovoltaic system. The structure chosen for this PV system is that of two power converters and DC voltage intermediate bus. The two power converters are: the DC-DC converter and the three-phase inverter, which requires two main controllers. These controllers have three main objectives. The first objective is to impose the PV voltage generated by the photovoltaic panel, in order to follow a maximum reference voltage provided by the MPPT block. The second one is to maintain the DC link voltage to a constant value, in order to optimize the transfer of energy between the two power converters. The last objective is to inject a three-phase sinusoidal current into the grid, while respecting a unit power factor. With the intention to achieve these three objectives, we designed cascading nonlinear controllers by using the technique of non-linear backstepping control in the synthesis of these two controllers, based on the Lyapunov function, with regard to maximise the PVG output voltage, in order to have a unitary power factor at the grid side. In order to regulate DC-link voltage, we developed an integral proportional controller (PI) with parameters that are optimized by the Particle Swarm Optimization (PSO) method. The robustness of the controller designed approach is tested by a simulation in MATLAB/Simulink software, that improves the performances of each controller whatever conditions of climate.

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“…The performance of each particle is measured using a predefined objective (fitness) function, which define the characteristics of the optimization problem [25].…”

Section: Particle Swarm Optimization Algorithmmentioning

confidence: 99%

A robust nonlinear control strategy of a PV System connected to the three-phase grid based on backstepping and PSO technique

Zouga

Benchagra

Ailane

2021

IJPEDS

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“…Each particle is associated with the best possible objective function on the path of best position (Pbest). Then its group path becomes the best position for all particles [26] [14].…”

Section: Maximum Power Extraction Based On Psomentioning

confidence: 99%

“…PSO is also used to adjust the tuning of the proportional integral controller (PI) which is used to adjust the PMSG speed in WTS. Compared to PI controllers, the use of PSO -PI controllers results in better performance [26].…”

Section: Introductionmentioning

confidence: 99%

Maximum Power Extraction For Hybrid Solar Wind Renewable Energy System Based on Swarm Optimization

Putri

Ronilaya

Syamsiana

2021

IJRER

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This paper aims to extract maximum power for a hybrid solar wind renewable energy system using the Particle Swarm Optimization (PSO) for standalone applications. Maximum power extraction based on PSO works to achieve optimal power on HRES by adjusting the duty cycle for the boost converter for each energy source system based on current and voltage measurements. The inverter connects the DC boost and load, and the DC bus voltage is kept constant by the inverter's duty cycle adjustment using PI controller. PSO performance is analyzed through the changes in wind speed and solar irradiation, as maximum power extraction. According to simulation result, PSO can track the maximum power against changes in wind speed and solar irradiation. PSO has a better performance compared to P&O methods, and constant DC bus voltage can be maintained.

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“…Based on the type of the wind turbine and generator used, variable speed wind turbines (VSWTs) with permanent magnet synchronous generators (PMSGs) have advantages compared to fixed speed wind turbines (FSWTs). The VSWT is more effective than the FSWT because it offers optimised wind energy conversion, increased captured wind energy, operation at the maximum power point (MPP) for wide range, and less mechanical stress [6][7][8]. Wind energy is highly unpredictable and intermittent [4]; thus, VSWTs are widely used to convert wind energy into electricity because they are designed to produce output power that follows the changes in the wind speed [3,[9][10][11][12].…”

Section: Introductionmentioning

confidence: 99%

“…Wind energy is highly unpredictable and intermittent [4]; thus, VSWTs are widely used to convert wind energy into electricity because they are designed to produce output power that follows the changes in the wind speed [3,[9][10][11][12]. Further, PMSGs are widely used in VSWTs owing to their reliability, high torque density, simple structure, and high reliability because a gearbox is not required [8,13]. Besides, VSWTs are widely used for small-scale wind turbine off-grid applications in remote areas [1,4].…”

Section: Introductionmentioning

confidence: 99%

Maximum power extraction improvement using sensorless controller based on adaptive perturb and observe algorithm for PMSG wind turbine application

Putri¹,

Pujiantara²,

Priyadi³

et al. 2018

IET Electric Power Applications

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Wind energy conversion systems (WECSs) can extract maximum power by controlling the wind turbine rotational speed. This study presents a novel sensorless maximum power extraction control for small-scale WECS using a permanent magnet synchronous generator (PMSG), to improve the maximum power extraction. The proposed method uses the output voltage and current of a rectifier to determine the duty cycle of the boost converter, without requiring the wind speed information and turbine characteristics. The step size of the duty cycle is changed adaptively, based on the difference between the rectifier output power and the previous duty cycle to obtain fast convergence, until the maximum power point is attained. The performance of the proposed sensorless maximum power extraction control is evaluated both by simulation, using PowerSIM and laboratory experiments, for variable wind speed conditions. The proposed maximum power extraction controller has a simple structure, low cost, and a good response to wind speed variations. The proposed method can extract a higher maximum power and has a higher efficiency of 93.87%, than the conventional perturb and observe method.

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Tuning PI Controller Based on Multiobjective Optimization Approaches for Speed Control of PMSG Wind Turbine

Cited by 13 publications

References 0 publications

A robust nonlinear control strategy of a PV System connected to the three-phase grid based on backstepping and PSO technique

A robust nonlinear control strategy of a PV System connected to the three-phase grid based on backstepping and PSO technique

Maximum Power Extraction For Hybrid Solar Wind Renewable Energy System Based on Swarm Optimization

Maximum power extraction improvement using sensorless controller based on adaptive perturb and observe algorithm for PMSG wind turbine application

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