Results of a Wind Turbine FDI Competition

Odgaard, Peter Fogh; Stoustrup, Jakob

doi:10.3182/20120829-3-mx-2028.00015

Cited by 42 publications

(31 citation statements)

References 28 publications

(29 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…It can be seen that the LPV ESO method can provide very good fault estimation, which is a significant result even though it is claimed that a 100 Nm fault is too small to be detected [13]. From the simulation results, there is no obvious improvement obtained by using the AFTC scheme.…”

Section: Actuator Fault In Generator Subsystemmentioning

confidence: 79%

An active fault tolerant control approach to an offshore wind turbine model

Shi

Patton

2015

Renewable Energy

View full text Add to dashboard Cite

a b s t r a c tThe paper proposes an observer based active fault tolerant control (AFTC) approach to a non-linear large rotor wind turbine benchmark model. A sensor fault hiding and actuator fault compensation strategy is adopted in the design. The adapted observer based AFTC system retains the well-accepted industrial controller as the baseline controller, while an extended state observer (ESO) is designed to provide estimates of system states and fault signals within a linear parameter varying (LPV) descriptor system context using linear matrix inequality (LMI). In the design, pole-placement is used as a time-domain performance specification while H ∞ optimization is used to improve the closed-loop system robustness to exogenous disturbances or modelling uncertainty. Simulation results show that the proposed scheme can easily be viewed as an extension of currently used control technology, with the AFTC proving clear "added value" as a fault tolerant system, to enhance the sustainability of the wind turbine in the offshore environment.

show abstract

Section: Actuator Fault In Generator Subsystemmentioning

confidence: 79%

An active fault tolerant control approach to an offshore wind turbine model

Shi

Patton

2015

Renewable Energy

View full text Add to dashboard Cite

show abstract

“…At wind turbine level, this fault could be detected monitoring changes in the frequency spectra of the vibration measurements. However, the solutions provided in the Wind Turbine FDI competition suggest that it is hard to detect changes in the drive train damping only at the wind turbine level [40]. Hence, it is interesting to investigate if this fault could be detected at the wind farm level.…”

Section: B Fault Scenariosmentioning

confidence: 99%

An Interval NLPV Parity Equations Approach for Fault Detection and Isolation of a Wind Farm

Blesa

Jiménez

Rotondo

et al. 2014

IEEE Trans. Ind. Electron.

View full text Add to dashboard Cite

Abstract-In this paper, the problem of fault diagnosis of a wind farm is addressed using interval nonlinear parameter varying (NLPV) parity equations. Fault detection is based on the use of parity equations assuming unknown but bounded description of the noise and modeling errors. The fault detection test is based on checking the consistency between the measurements and the model by finding if the formers are inside the interval prediction bounds. The fault isolation algorithm is based on analyzing the observed fault signatures on-line, and matching them with the theoretical ones obtained using structural analysis. Finally, the proposed approach is tested using the wind farm benchmark proposed in the context of the wind farm FDI/FTC competition.

show abstract

“…The problem of model-based fault diagnosis in wind turbines has recently been addressed (Odgaard & Stoustrup, 2012b), the main motivation being the importance gained in many countries by this technology for electricity generation. So far, revising the literature, methods ranging from Kalman filters (Wei et al, 2008), observers (Odgaard et al, 2009), parity equations (Dobrila & Stefansen, 2007), dynamic weighting ensembles (Razavi-Far & Kinnaert, 2013) and fuzzy modeling and identification methods (Badihi et al, 2013) have already been suggested as possible model-based techniques for fault diagnosis of wind turbines.…”

Section: Introductionmentioning

confidence: 99%

FDI and FTC of wind turbines using the interval observer approach and virtual actuators/sensors

Blesa

Rotondo

Puig

et al. 2014

Control Engineering Practice

123

View full text Add to dashboard Cite

In this work, the problem of Fault Detection and Isolation (FDI) and Fault Tolerant Control (FTC) of wind turbines is addressed. Fault detection is based on the use of interval observers and unknown but bounded description of the noise and modeling errors. Fault isolation is based on analyzing the observed fault signatures on-line and matching them with the theoretical ones obtained using structural analysis and a row-reasoning scheme. Fault tolerant control is based on the use of virtual sensors/actuators to deal with sensor and actuator faults, respectively. More precisely, these FTC schemes, that have been proposed previously in state space form, are reformulated in input/output form. Since an active FTC strategy is used, the FTC module uses the information from the FDI module to replace the real faulty sensor/actuator by activating the corresponding virtual sensor/actuator. Virtual actuators/sensors require additionally a fault estimation module to compensate the fault. In this work, a fault estimation approach based on batch least squares is used. The performance of the proposed FDI and FTC schemes is assessed using the proposed fault scenarios considered in the wind turbine benchmark proposed at IFAC SAFEPROCESS 2009. Satisfactory results have been obtained in both FDI and FTC.

show abstract

Results of a Wind Turbine FDI Competition

Cited by 42 publications

References 28 publications

An active fault tolerant control approach to an offshore wind turbine model

An active fault tolerant control approach to an offshore wind turbine model

An Interval NLPV Parity Equations Approach for Fault Detection and Isolation of a Wind Farm

FDI and FTC of wind turbines using the interval observer approach and virtual actuators/sensors

Contact Info

Product

Resources

About