A Comparative Study of Three Fault Diagnosis Schemes for Wind Turbines

Dey, Satadru; Pisu, Pierluigi; Ayalew, Beshah

doi:10.1109/tcst.2015.2389713

Cited by 58 publications

(38 citation statements)

References 18 publications

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“…Model-based FDI schemes are able to deal with unforeseen fault scenarios using model predictions without requiring large sets of data. 17,18 Different model-based fault diagnostic approaches that exist in the literature of wind turbines have mostly addressed the mechanical fault detections. In the work of Ozdemir et al, 19 after generating primary residuals using a model-based approach and physical redundancies, a counter-based thresholding method is used for wind turbine fault diagnosis.…”

Section: Discussionmentioning

confidence: 99%

“…In physical model‐based FDI schemes, a system model is used to detect, isolate, and then accommodate the faults. Model‐based FDI schemes are able to deal with unforeseen fault scenarios using model predictions without requiring large sets of data . Different model‐based fault diagnostic approaches that exist in the literature of wind turbines have mostly addressed the mechanical fault detections.…”

Section: Introductionmentioning

confidence: 99%

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Stator voltage fault detection and optimal rotor current limiting in doubly fed induction generators

Bastami

Abolmasoumi

Ghadimi

2016

Int. Trans. Electr. Energ. Syst.

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Summary Doubly fed induction generators are widely used in wind power plants, yet their performance is vulnerable to grid voltage faults. Recent regulations require the wind generator to have the capability of fault crossing to stay connected even in faulty conditions. This paper investigates the problem of stabilizing the rotor current when the stator voltage is affected by the faults that occurred at the nearby grid. The proposed controller consists of 2 terms: the first is responsible for the internal stability of generator dynamics and the second compensates for the effect of the fault on the stator voltage. The stability of generator circuit is verified by using linear quadratic regulator and pole placement criteria. Also, to enhance the performance of the stabilizers, genetic algorithm is used to adjust the stabilizers. To detect the stator voltage disorders and to determine the suitable time for switching in fault stabilizers, a fault observer is also suggested. The fault detection and stabilization structure is simulated and shows higher levels of performance in faulty conditions than in conventional rotor side converter controllers in faulty grid conditions.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Stator voltage fault detection and optimal rotor current limiting in doubly fed induction generators

Bastami

Abolmasoumi

Ghadimi

2016

Int. Trans. Electr. Energ. Syst.

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“…Subject to: Constraint (25) and (26) being satisfied, that is, the actuator fault input is decoupled from the system estimation error (23) and residual (24). Theorem 1.…”

Section: Individual Robust Estimator Designmentioning

confidence: 99%

“…A lot of research has been started in recent years for the fault diagnosis and isolation of wind turbines [22][23][24][25][26][27][28][29]. Karim [22] designed an observer scheme for FDI, which is integrated with a maximum-shift strategy and a time-varying Kalman filter for the additive and multiplicative measurement failures of voltage and current.…”

Section: Introductionmentioning

confidence: 99%

Stochastic Hybrid Estimator Based Fault Detection and Isolation for Wind Energy Conversion Systems with Unknown Fault Inputs

et al. 2018

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Abstract:In recent years, the wind energy conversion system (WECS) has been becoming the vital system to acquire wind energy. However, the high failure rate of WECSs leads to expensive costs for the maintenance of WECSs. Therefore, how to detect and isolate the faults of WECSs with stochastic dynamics is the pressing issue in the literature. This paper proposes a novel comprehensive fault detection and isolation (FDI) method for WECSs. First, a stochastic model predictive control (SMPC) controller is studied to construct the closed-loop system of the WECS. This controller is based on the Markov-jump linear model, which could precisely establish the stochastic dynamics of the WECS. Meanwhile, the SMPC controller has satisfied control performance for the WECS. Second, based on the closed-loop system with SMPC, the stochastic hybrid estimator (SHE) is designed to estimate the continuous and discrete states of the WECS. Compared with the existing estimators for WECSs, the proposed estimator is more suitable for WECSs since it considers both the continuous and discrete states of WECSs. In addition, the proposed estimator is robust to the fault input. Finally, with the proposed estimator, the comprehensive FDI method is given to detect and isolate the actuators' faults of the WECS. Both the system status and the actuators' faults can be detected by the FDI method and it can effectively quantify the actuators' fault by the fault residuals. The simulation results suggest that the SHE could effectively estimate the hybrid states of the WECS, and the proposed FDI method gives satisfied fault detection performance for the actuators of the WECS.

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“…This is also main issue for artificial intelligent approaches, which cannot provide convincing explanation for various fault features. Sataru [15] uses model based cascaded Kalman filter to show its advances on fault detection and isolation while the nonlinearity of WT system is solved by nonlinear map. This indicates increasing trend of using model-based approaches for WT fault detection.…”

Section: System Modelmentioning

confidence: 99%

Study of Wind Turbine Fault Diagnosis Based on Unscented Kalman Filter and SCADA Data

et al. 2016

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Effective wind turbine fault diagnostic algorithms are crucial for wind turbine intelligent condition monitoring. An unscented Kalman filter approach is proposed to successfully detect and isolate two types of gearbox failures of a wind turbine in this paper. The state space models are defined for the unscented Kalman filter model by a detailed wind turbine nonlinear systematic principle analysis. The three failure modes being studied are gearbox damage, lubrication oil leakage and pitch failure. The results show that unscented Kalman filter model has special response to online input parameters under different fault conditions. Such property makes it effective on fault identification. It also shows that properly defining unscented Kalman filter state space vectors and control vectors are crucial for improving its sensitivity to different failures. Online fault detection capability of this approach is then proved on SCADA data. The developed unsented Kalman filter model provides an effective way for wind turbine fault detection using supervisory control and data acquisition data. This is essential for further intelligent WT condition monitoring.

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A Comparative Study of Three Fault Diagnosis Schemes for Wind Turbines

Cited by 58 publications

References 18 publications

Stator voltage fault detection and optimal rotor current limiting in doubly fed induction generators

Stator voltage fault detection and optimal rotor current limiting in doubly fed induction generators

Stochastic Hybrid Estimator Based Fault Detection and Isolation for Wind Energy Conversion Systems with Unknown Fault Inputs

Study of Wind Turbine Fault Diagnosis Based on Unscented Kalman Filter and SCADA Data

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