Design and Control of Grid-Connected PWM Rectifiers by Optimizing Fractional Order PI Controller Using Water Cycle Algorithm

Kakkar, Sushma; Maity, Tanmoy; Ahuja, Rajesh Kumar; Walde, Pratima; Saket, R. K.; Khan, Baseem; Padmanaban, Sanjeevikumar

doi:10.1109/access.2021.3110431

Cited by 19 publications

(14 citation statements)

References 33 publications

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“…V qref = E q + V * q + ωL f I d (9) where: E d , E q the voltages of the common connection points to the grid; L f is the coupling inductance of the filter device. In recent years, researchers have been interested in a new design of the PID controller to be applied in many domains, especially control theories compared to classical PID controllers because of their advantages, which are to increase the performance of non-linear, dynamic systems and to be less sensitive to changes in system parameters [9,39].…”

Section: Inverter Control Systemmentioning

confidence: 99%

“…For grid connected systems, a DC/AC converter is used. Such converter requires a robust control to respect power quality conditions such as lower harmonic content [9]. A reversibility of this converter is required in some installations [10].…”

Section: Introductionmentioning

confidence: 99%

“…A detailed comparison between classical PID controllers and FOPID ones has been presented by Jain and Saravanakumar [23]. Kakkar et al [9] have used the FOPID for manage the fluxoriented virtual control of PWM rectifier connected to power grid. Their simulation results have shown that fractional order is less sensitive to load and parameter variations, on the other hand injected power quality has been improved when comparing to the obtained using classical PID controller.…”

Section: Introductionmentioning

confidence: 99%

“…A satisfactory response of the converter requires a tunning of controller parameters whatever its type: PID or FOPID. In literature, many algorithms have been proposed for tunning controller parameters such as Genetic Algorithm (GA) [25], Cuckoo Search Algorithm (CS) [26], Chaotic Ant Swarm Algorithm (CAS) [27], grey wolf optimization (GWO) [28], Water Cycle Algorithm (WCA) [9], sine cosine algorithm (SCA) [29], Gradient-Based Optimization (GBO) [21] and Particle Swarm Optimization (PSO) [30]. Among the cited algorithms, PSO has been chosen for the control of our converter.…”

Section: Introductionmentioning

confidence: 99%

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Optimization of Fractional Order PI Controller by PSO Algorithm Applied to a Grid-Connected Photovoltaic System

Bouderres¹,

Kerdoun²,

Djellad³

et al. 2022

JESA

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With the increasing integration of renewable energies into power grids, their control and power quality are becoming the main focus of many research efforts. In a grid-connected photovoltaic system, the control strategy is necessary to efficiently use the solar energy as well as to ensure high power quality. This paper presents a study on the robustness of a Fractional Order PI controller based on the Particle Swarm Optimization algorithm (PSO-FOPI) in a grid-connected PV system. The controller used was integrated into the inverter to apply voltage-oriented control (VOC). Fractional order controllers have an additional degree of freedom, so that a wider range of parameters is available to provide better control. Parameter optimization of the FOPI and classical PI controllers are performed using the PSO algorithm. The performance of the FOPI controller is compared with that of the classical PI controller. A complete study of the behavior of the grid connected PV system is tested using MATLAB/Simulink. The simulation results show the performance and efficiency of the PSO-FOPI controller compared to the classical PI controller in terms of rapidity, stability and precision, as well as the THD reduction of the current injected to the grid for any variation of solar irradiance.

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Section: Inverter Control Systemmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Optimization of Fractional Order PI Controller by PSO Algorithm Applied to a Grid-Connected Photovoltaic System

Bouderres¹,

Kerdoun²,

Djellad³

et al. 2022

JESA

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show abstract

“…The resolution was presented by MATLAB, where the PI controller [30] obtained the following transfer function, according to…”

Section: Experimental Data Used In Pi Controller Simulationmentioning

confidence: 99%

Computational Validation of the Best Tuning Method for a Vehicle-Integrated PID Controller

Manuel

Santos

Lenzi

et al. 2022

Modelling and Simulation in Engineering

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This paper validates and analyzes the robustness of the proportional-integral-derivative (PID) action controller from an open transfer function that integrates a proportional-integral (PI) action controller to obtain the response of a robust action control during the automatic parking maneuver of a vehicle where the simulations are based on 3 adjustment methods: Ziegler-Nichols (ZN), Chien-Hrones-Reswick (CHR), and Cohen-Coon (CC), and as a result of the computer simulations, it is determined the best performance index of the PID controller represented by mathematical and graphic equations with the help of MATLAB/Simulink software.

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Integration of charging station to the smart grid power network by using robust immune feedback adaptive and Rao optimization approaches

Jaraniya

Kumar

2022

Int J Numerical Modelling

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The adoption of electrical vehicles (EVs) is nowadays a center of attraction, which reduces the carbon footprint and adds to the economic growth of a country. However, providing a proper charging facility to the customers is still a challenging task. This paper presents the mix (AC‐DC) charging station (CS) integrated with the PV array and the smart distribution grid. The acceleration of the EV causes the power quality burden on the grid and this can be taken care of by using advanced adaptive controls. In this paper, the control strategy used for the CS is the immune feedback‐based adaptive (IFA) control technique. It reduces the ripples in the fundamental load current extraction under steady‐state and produces fast response under dynamic conditions and helps to synchronize CS with the grid. The multi‐functional capabilities of the CS are presented with different voltage levels DC fast off‐board chargers and AC onboard slow chargers. Moreover, the Rao optimization technique is utilized to select the gains for the cascaded proportional‐integral (PI) controllers which are used to regulate the DC bus voltage and battery charging/discharging currents. The optimized fitness values of integral time square error (ITSE) by using Rao1, Rao2, and Rao3 techniques are 297.341, 285.023, and 282.924 respectively. The simulated and test results depict the efficacy of the CS. Moreover, the mixed charging facilities with multi DC fast chargers avoid the rush and burden on the grid, which reduces the power outage across the load and rapidly rising energy cost.

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Design and Control of Grid-Connected PWM Rectifiers by Optimizing Fractional Order PI Controller Using Water Cycle Algorithm

Cited by 19 publications

References 33 publications

Optimization of Fractional Order PI Controller by PSO Algorithm Applied to a Grid-Connected Photovoltaic System

Optimization of Fractional Order PI Controller by PSO Algorithm Applied to a Grid-Connected Photovoltaic System

Computational Validation of the Best Tuning Method for a Vehicle-Integrated PID Controller

Integration of charging station to the smart grid power network by using robust immune feedback adaptive and Rao optimization approaches

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