A Novel Adaptive Control Method for Performance Enhancement of Grid-Connected Variable-Speed Wind Generators

Soliman, Mahmoud A.; Hasanien, Hany M.; Al‐Durra, Ahmed; Alsaidan, Ibrahim

doi:10.1109/access.2020.2991689

Cited by 38 publications

(20 citation statements)

References 52 publications

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“…− → X p represents the prey position vector, t denotes the current iteration, A and C express coefficient vectors, and X signifies a gray wolf location vector. The vectors C and A are computed using Equation (20).…”

Section: Carrier Signalmentioning

confidence: 99%

“…Nevertheless, the PI controllers are acutely susceptible to uncertainty, nonlinearity, and parameters variations of the system [19]. Various approaches for properly designing the gains of cascaded PI controllers have been introduced in the literature [20]. Creating such a controller in most of those approaches relied on trial-and-error criteria, which is time-consuming, takes a lot of effort, and is mostly dependent on the designer's competence.…”

Section: Introductionmentioning

confidence: 99%

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Towards Enhancing the Performance of Grid-Tied VSWT via Adopting Sine Cosine Algorithm-Based Optimal Control Scheme

et al. 2021

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The expanding trend of wind power technology motivates scholars to pursue more investigation on optimising energy extraction from the wind and integrating high-quality power into the utility grid. This paper is aimed at introducing a novel application of the sine cosine algorithm (SCA) which attempts to find the optimal gains of proportional-integral (PI) controllers used to control the power electronic converter (PEC) equipped with the Variable speed Wind turbine (VSWT) such that a maximum power extraction and performance enhancement can be realized. The PEC equipped with the VSWT combines a machine side converter (MSC) and a grid-side inverter (GSI). Both the MSC and GSI are controlled by the proposed SCA-based PI controllers through cascaded vector control schemes. The MSC is responsible for controlling the wind generator's rotational speed, active power, and reactive power. The GSI is used to regulate the dc-link voltage and to keep the terminal voltage at the desired frame set by the operator. To obtain the optimum PI gains, the SCA is applied to minimize the sum of the integral squared error (ISE) of twelve PI controllers error inputs in the control schemes simultaneously. Performances of the proposed SCA-PI control schemes are assessed under severe grid disturbance and random wind speed variation to mimic more realistic conditions. The effectiveness of the proposed SCA-PI is verified in the MATLAB/Simulink environment, and the results are compared to those obtained using a grey wolf optimizer and particle swarm algorithm-based optimal PI controller. The simulation findings confirm the SCA-PI can be regarded as an efficacious way to enhance the performance of the VSWT.INDEX TERMS Wind turbine control, power electronic converter, MPPT, PMSG, PI controller, sine cosine algorithm.

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Section: Carrier Signalmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Towards Enhancing the Performance of Grid-Tied VSWT via Adopting Sine Cosine Algorithm-Based Optimal Control Scheme

et al. 2021

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“…The frequency responses, voltage, and current waveforms at the PCC, and harmonic spectra are compared in Figs. [11][12][13], respectively, among the L, LC, iterative LCL, and modified LCL filters. It is clear from Fig.…”

Section: ) Performance Of Modified Lcl Filtermentioning

confidence: 99%

“…The existing popular classical control methods include virtual flux-oriented control [7], direct power control [8], and decoupled voltage-oriented control (VOC) [9] - [11]. These controllers employ multiple proportional-integral (PI) regulators that can cause instability owing to the system nonlinearity and the variation of system variables [12], [13]. Moreover, tuning these regulators for suitable gain is a tedious and time-consuming task.…”

Section: Introductionmentioning

confidence: 99%

Modeling, Parameter Measurement, and Control of PMSG-based Grid-connected Wind Energy Conversion System

Prince

Arif

Gargoom

et al. 2021

Journal of Modern Power Systems and Clean Energy

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The design of reliable controllers for wind energy conversion systems (WECSs) requires a dynamic model and accurate parameters of the wind generator. In this paper, a dynamic model and the parameter measurement and control of a direct-drive variable-speed WECS with a permanent magnet synchronous generator (PMSG) are presented. An experimental method is developed for measuring the key parameters of the PMSG. The measured parameters are used in the design of the controllers. The generator-side converter is controlled using a vector control scheme that maximizes the power extraction under varying wind speeds. A model predictive controller (MPC) is designed for the grid-side voltage source converter (VSC) to regulate the active and reactive power flows to the power grid by controlling the d-and q-axis currents in the synchronous reference frame. The MPC predicts the future values of the control variables and takes control actions based on the minimum value of the cost functions. To comply with the grid code requirement, a modified design approach for an LCL filter is presented and incorporated into the system. The design process is simple and incorporates significant filter parameters while avoiding iterative calculations. The comparative analysis of the designed filter with conventional L, LC, and iterative LCL filters demonstrates the effectiveness of the modified design approach. The proposed wind energy system with MPC and LCL filter is simulated in MATLAB/Simulink and experimentally implemented in the laboratory using the dSpace digital signal processor (DSP) system. The simulation and experimental results validate the efficacy of the designed controllers using the measured parameters and show dynamic and steady-state performance under varying wind speeds. Index Terms--Wind energy, permanent magnet synchronous generator (PMSG), parameter measurement, model predictive controller (MPC), LCL filter.

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“…The continuous p-norm mixed technique is presented as a new adaptive control of the VS, which rapidly updates the fuzzy inference system in [25]. In [26], the improved multiband-structured subband adaptive filter (IMSAF) algorithm-based self-tuned PI controller is employed to adjust the interface voltage source converters through a cascaded control structure. In [27], the improved zero attracting quaternion-valued least mean square (IZAQLMS) control approach with high DC offset rejection capability is used to improve the power quality of the grid current and to ensure the unity power factor operation of the grid.…”

Section: B Research Gap and Motivationmentioning

confidence: 99%

LMSRE-Based Adaptive PI Controller for Enhancing the Performance of an Autonomous Operation of Microgrids

et al. 2021

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Microgrids take a large part in power networks thanks to their operational and economic benefits. This research introduces a novel implementation of an adaptive proportional plus integral (PI) controller to boost the autonomous microgrid operation efficiency. The least mean and square roots of the exponential algorithm are utilized in the adaptive PI control strategy. The multi-objective function for both sunflower optimization (SFO) and particle swarm optimization (PSO) algorithms is obtained by The Response Surface Methodology. The system is evaluated under different environments, which are stated as follows: 1) disconnect the system from the grid (islanding), 2) autonomous system exposure to load variability, and 3) autonomous system exposure to a symmetrical fault. The proposed practicality of the control plan is shown by the data of the simulation, which is extracted from PSCAD/EMTDC software. The strength of the suggested adaptive control is confirmed through matching its results with those obtained using the SFO and PSO based optimal PI controllers. INDEX TERMS microgrid; optimization; power systems; renewable energy. Ahmed Al-Durra (S'07-M'10-SM'14) received his PhD in ECE from Ohio State University in 2010.He is a Professor in the EECS Department at Khalifa University, UAE. His research interests are applications of control and estimation theory on power systems stability, micro and smart grids, renewable energy systems and integration, and process control. He has one US patent, one edited book, 12 book chapters, and over 210 scientific articles in top-tier journals and refereed international conference proceedings. He has supervised/co-supervised

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A Novel Adaptive Control Method for Performance Enhancement of Grid-Connected Variable-Speed Wind Generators

Cited by 38 publications

References 52 publications

Towards Enhancing the Performance of Grid-Tied VSWT via Adopting Sine Cosine Algorithm-Based Optimal Control Scheme

Towards Enhancing the Performance of Grid-Tied VSWT via Adopting Sine Cosine Algorithm-Based Optimal Control Scheme

Modeling, Parameter Measurement, and Control of PMSG-based Grid-connected Wind Energy Conversion System

LMSRE-Based Adaptive PI Controller for Enhancing the Performance of an Autonomous Operation of Microgrids

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