Multi-objective PSO applied to PI control of DFIG wind turbine under electrical fault conditions

Aguilar, Milton Ernesto Barrios; Coury, Denis Vinicius; Reginatto, Romeu; Monaro, Renato M.

doi:10.1016/j.epsr.2019.106081

Cited by 47 publications

(32 citation statements)

References 12 publications

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“…In wind turbine generator fault detection, the running time of the model is also an important index. How to meet both high fault detection performance and short running time has always been a research hotspot (Barrios Aguilar et al, 2020;Falehi, 2020).The objective function of CS-ERT only focuses on fault detection performance compared to the multiple objective optimization approach. The advantage of the running time is reflected in its unique structure.…”

Section: Comparison Among Different Methodsmentioning

confidence: 99%

Cost-Sensitive Extremely Randomized Trees Algorithm for Online Fault Detection of Wind Turbine Generators

Tang

Zhao

et al. 2021

Front. Energy Res.

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The number of normal samples of wind turbine generators is much larger than the number of fault samples. To solve the problem of imbalanced classification in wind turbine generator fault detection, a cost-sensitive extremely randomized trees (CS-ERT) algorithm is proposed in this paper, in which the cost-sensitive learning method is introduced into an extremely randomized trees (ERT) algorithm. Based on the classification misclassification cost and class distribution, the misclassification cost gain (MCG) is proposed as the score measure of the CS-ERT model growth process to improve the classification accuracy of minority classes. The Hilbert-Schmidt independence criterion lasso (HSICLasso) feature selection method is used to select strongly correlated non-redundant features of doubly-fed wind turbine generators. The effectiveness of the method was verified by experiments on four different failure datasets of wind turbine generators. The experiment results show that average missing detection rate, average misclassification cost and gMean of the improved algorithm better than those of the ERT algorithm. In addition, compared with the CSForest, AdaCost and MetaCost methods, the proposed method has better real-time fault detection performance.

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Section: Comparison Among Different Methodsmentioning

confidence: 99%

Cost-Sensitive Extremely Randomized Trees Algorithm for Online Fault Detection of Wind Turbine Generators

Tang

Zhao

et al. 2021

Front. Energy Res.

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“…The PSO algorithm is a meta-heuristic technique of swarm intelligence approach that simulates the psychosocial behavior of collective organisms (Birds in flight, shoals, etc). It is being used to solve nonlinear and continuous problems and adapt single-objective and multiobjective problems [23], [24]. Consequently, it is a suitable optimization approach for regulator design.…”

Section: A Motivationmentioning

confidence: 99%

Fractional-Fuzzy PID Control Approach of Photovoltaic-Wire Feeder System (PV-WFS): Simulation and HIL-Based Experimental Investigation

et al. 2021

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“…The GSC also employs the sliding mode control technique, in order to exchange with the grid only the active power extracted or injected by the RSC from the rotor, which is indirectly controlled through the DC-link regulator [21], [22]. To this end, the GSC controller involves two control loops.…”

Section: Grid Side Converter Controllermentioning

confidence: 99%

Nonlinear control of grid-connected wind energy conversion system without mechanical variables measurements

Noussi¹,

Abouloifa²,

Katir³

et al. 2021

IJPEDS

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This article addresses the problem of controlling an overall wind energy conversion system (WECS) formed by a wind turbine connected to the grid via a doubly fed introduction generator (DFIG) and an AC/DC/AC converter. The main control objectives are fourfold: (i) designing an output feedback speed controller that makes the DFIG rotate at the optimal value delivered by the MPPT strategy, (ii) controlling the stator reactive power so as to be null, (iii) guaranteeing the DC-link voltage in the grid side converter to be at a given constant value, (iv) ensuring a unitary power factor. A high gain observer is synthesized, in order to provide estimated values of the mechanical variables. To achieve the control objectives, a sliding mode controller involving the mechanical observer is designed. The performance of the system configuration based on the 2MW-DFIG with the proposed controller is evaluated by a numerical simulation under a realistic wind profile using MATLAB/SIMULINK/SimPowerSystems environment.

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Multi-objective PSO applied to PI control of DFIG wind turbine under electrical fault conditions

Cited by 47 publications

References 12 publications

Cost-Sensitive Extremely Randomized Trees Algorithm for Online Fault Detection of Wind Turbine Generators

Cost-Sensitive Extremely Randomized Trees Algorithm for Online Fault Detection of Wind Turbine Generators

Fractional-Fuzzy PID Control Approach of Photovoltaic-Wire Feeder System (PV-WFS): Simulation and HIL-Based Experimental Investigation

Nonlinear control of grid-connected wind energy conversion system without mechanical variables measurements

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