Pitch fault diagnosis of wind turbines in multiple operational states using supervisory control and data acquisition data

Wei, Lu; Zheng, Qian; Cong, Yang; Pei, Yan

doi:10.1177/0309524x18791407

Cited by 4 publications

(4 citation statements)

References 19 publications

(17 reference statements)

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“…The MPPT will improve the output power efficiency by tracking the optimum aerodynamic torque by using the conventional MPPT including perturb and observe, optimal torque, and tip speed ratio control. The MPPT algorithms based on the optimal power coefficient of the system can be referred in [78]. As an example, the nonlinear sliding mode control is used to optimize output power for variable DFIG turbine [79].…”

Section: Control Scheme For Co-generation and Complimentary Generationmentioning

confidence: 99%

A Review of Power Co-Generation Technologies from Hybrid Offshore Wind and Wave Energy

et al. 2023

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Renewable energy resources such as offshore wind and wave energy are environmentally friendly and omnipresent. A hybrid offshore wind-wave energy system produces a more sustainable form of energy that is not only eco-friendly but also economical and efficient as compared to use of individual resources. The objective of this paper is to give a detailed review of co-generation technologies for hybrid offshore wind and wave energy. The proposed area of this review paper is based on the power conversions techniques, response coupling, control schemes for co-generation and complimentary generation, and colocation and integrated conversion systems. This paper aims to offer a systematic review to cover recent research and development of novel hybrid offshore wind-wave energy (HOWWE) systems. The current hybrid wind-wave energy structures lack efficiency due to their design and AC-DC-AC power conversion that need to be improved by applying an advanced control strategy. Thus, using different power conversion techniques and control system methodologies, the HOWWE structure can be improved and will be transferrable to the other hybrid models such as hybrid solar and wind energy. The state-of-the-art HOWWE systems are reviewed. Critical analysis of each method is performed to evaluate the best possible combination for development of a HOWWE system.

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Section: Control Scheme For Co-generation and Complimentary Generationmentioning

confidence: 99%

A Review of Power Co-Generation Technologies from Hybrid Offshore Wind and Wave Energy

et al. 2023

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“…In [28], pitch faults were detected based on normal behavior models of operational curves: the selected curves were power-generator speed and pitch angle-generator speed. A similar approach is proposed in [29], where Gaussian mixture model clustering and the analysis of normal performance curves are applied to model the relationship of pitch angle, rotor speed, and wind speed. In [30], a fault detection scheme for the blade pitch of wind turbines was proposed based on the unscented Kalman filter and a decorrelation approach for process and measurement noises.…”

Section: Introductionmentioning

confidence: 99%

A Study of the Impact of Pitch Misalignment on Wind Turbine Performance

Astolfi

2019

Machines

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Pitch angle control is the most common means of adjusting the torque of wind turbines. The verification of its correct function and the optimization of its control are therefore very important for improving the efficiency of wind kinetic energy conversion. On these grounds, this work is devoted to studying the impact of pitch misalignment on wind turbine power production. A test case wind farm sited onshore, featuring five multi-megawatt wind turbines, was studied. On one wind turbine on the farm, a maximum pitch imbalance between the blades of 4.5 ° was detected; therefore, there was an intervention for recalibration. Operational data were available for assessing production improvement after the intervention. Due to the non-stationary conditions to which wind turbines are subjected, this is generally a non-trivial problem. In this work, a general method was formulated for studying this kind of problem: it is based on the study, before and after the upgrade, of the residuals between the measured power output and a reliable model of the power output itself. A careful formulation of the model is therefore crucial: in this work, an automatic feature selection algorithm based on stepwise multivariate regression was adopted, and it allows identification of the most meaningful input variables for a multivariate linear model whose target is the power of the wind turbine whose pitch has been recalibrated. This method can be useful, in general, for the study of wind turbine power upgrades, which have been recently spreading in the wind energy industry, and for the monitoring of wind turbine performances. For the test case of interest, the power of the recalibrated wind turbine is modeled as a linear function of the active and reactive power of the nearby wind turbines, and it is estimated that, after the intervention, the pitch recalibration provided a 5.5% improvement in the power production below rated power. Wind turbine practitioners, in general, should pay considerable attention to the pitch imbalance, because it increases loads and affects the residue lifetime; in particular, the results of this study indicate that severe pitch misalignment can heavily impact power production.

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“…To put values, Wilkinson estimates 13%–15% of the turbine failures occur in the mechanical part of the drive train (Wilkinson and Tavner, 2006). In comparison, yaw and pitch control system suffers higher failure rates (Ouanas et al, 2018; Wei et al, 2018) but each such failure gives less downtime than, for example, gearbox when they occur.…”

Section: Introductionmentioning

confidence: 99%

“…In case real measurements are not available, the model can be used to evaluate different operation conditions. Other potential uses include a priori to evaluate different proposed sensor positions or evaluating new control algorithm (Wei et al, 2018) considering the trade-off between energy production and drive train components fatigue life.…”

Section: Introductionmentioning

confidence: 99%

Multibody dynamic modelling of a direct wind turbine drive train

Asadi

Johansson

2019

Wind Engineering

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Wind turbines normally have a long operational lifetime and experience a wide range of operating conditions. A representative set of these conditions is considered as part of a design process, as codified in standards. However, operational experience shows that failures occur more frequently than expected, the more costly of these including failures in the main bearings and gearbox. As modern turbines are equipped with sophisticated online systems, an important task is to evaluate the drive train dynamics from online measurement data. In particular, internal forces leading to fatigue can only be determined indirectly from other locations' sensors. In this contribution, a direct wind turbine drive train is modelled using the floating frame of reference formulation for a flexible multibody dynamics system. The purpose is to evaluate drive train response based on blade root forces and bedplate motions. The dynamic response is evaluated in terms of main shaft deformation and main bearing forces under different wind conditions. The model was found to correspond well to a commercial wind turbine system simulation software (ViDyn).1 data in terms of drive train dynamics and its effect on drive train performance and components' fatigue life, based on blade root forces and moments, as well as bedplate motion. This analysis is crucial in evaluating different operation conditions. It can also be used as a priori to evaluate different proposed sensor positions. Multibody dynamics techniques are commonly used to analyze the component loads in mechanical systems [2,3]. Wind turbine drive trains could be considered to constitute a multibody system with flexible and rigid components interconnected with each other by kinematic constraints, and which experience force during different operating conditions. For instance, in [4], a flexible multibody dynamic system modelling is employed to study the dynamic response of a horizontal wind turbine gearbox composed of planetary and conventional parallel axis gear sets. In [5], the dynamic stability analysis of a horizontal axis wind turbine (HAWT) is presented. The analysis framework is established based on separation of the complete HAWT system model into rigid and flexible body subsystems. The most popular methods within flexible multibody dynamics modelling are floating frame of reference (FFR) formulation [2,6,7,8,9], absolute nodal coordinates formulation (ANCF) [10,11], and corotational frame of reference (CFR) [12,13].The FFR formulation is based on separating the overall motion of the elastic body into a large rigid body motion (or reference motion), and superimposing small deformations by introducing a body fixed coordinate system, which translate and rotate with the body and experience small deformations (measured relative to this coordinate system). In [10], the traditional FFR approach combined with linear elastic finite element (FE) models is illustrated. In contrast, the ANCF does not separate the total elastic body motion into a reference motion and elastic deformations re...

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Pitch fault diagnosis of wind turbines in multiple operational states using supervisory control and data acquisition data

Cited by 4 publications

References 19 publications

A Review of Power Co-Generation Technologies from Hybrid Offshore Wind and Wave Energy

A Review of Power Co-Generation Technologies from Hybrid Offshore Wind and Wave Energy

A Study of the Impact of Pitch Misalignment on Wind Turbine Performance

Multibody dynamic modelling of a direct wind turbine drive train

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