Condition monitoring of wind generators

Popa, Lucian; Jensen, Bogi Bech; Ritchie, Ewen; Boldea, Ion

doi:10.1109/ias.2003.1257819

Cited by 95 publications

(54 citation statements)

References 13 publications

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“…Those failures mostly present on the stator, rotor and bearings. For induction machines, which are the most common, about 40% of failures occur to bearings, 38% to the stator and 10% to the rotor; as [18] concludes. Some of the major failures of these machines are: opening or shorting inter-turn failures at the stator's or rotor's winding circuits, stator winding abnormal connection, dynamic eccentricity, broken rotor bars, cracked end-rings, static and dynamic air-gap eccentricities, etc.…”

Section: Generatormentioning

confidence: 97%

“…Identifying the ways that a WT can fail is the first stage of the risk management process which will constitute the base of work on future life extension processes, making it a feasible practice. Premature brake activation [21] Unsteady performance [28] Increased torque pulsation [18,31] Inability of excessive operational load mitigation [35] Corrosion [28] Excessive heating in the winding [18] Operation instability due to hydraulic system failure [36] Gearbox (bearings and gears) Ref Increase in losses and efficiency reduction [31] Air contamination in the hydraulic system [37] Gear tooth damage [38] Rotor misalignment [39] Inability of aerodynamic braking [35] Pitting [38] Imbalances and harmonics in the air gap flux [18,40] Hydraulic fluid bulk modulus reduction [37] Cracking [38] Shorted winding coil (reduction in generator reactance) [29] Leakage in the hydraulic system [37] Gear eccentricity [29] Tower and Foundation Ref …”

Section: Service Life Failure Mode Identificationmentioning

confidence: 99%

See 1 more Smart Citation

Failure Mode Identification and End of Life Scenarios of Offshore Wind Turbines: A Review

Luengo

Kolios

2015

Energies

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Abstract:In 2007, the EU established challenging goals for all Member States with the aim of obtaining 20% of their energy consumption from renewables, and offshore wind is expected to be among the renewable energy sources contributing highly towards achieving this target. Currently wind turbines are designed for a 25-year service life with the possibility of operational extension. Extending their efficient operation and increasing the overall electricity production will significantly increase the return on investment (ROI) and decrease the levelized cost of electricity (LCOE), considering that Capital Expenditure (CAPEX) will be distributed over a larger production output. The aim of this paper is to perform a detailed failure mode identification throughout the service life of offshore wind turbines and review the three most relevant end of life (EOL) scenarios: life extension, repowering and decommissioning. Life extension is considered the most desirable EOL scenario due to its profitability. It is believed that combining good inspection, operations and maintenance (O&M) strategies with the most up to date structural health monitoring and condition monitoring systems for detecting previously identified failure modes, will make life extension feasible. Nevertheless, for the cases where it is not feasible, other options such as repowering or decommissioning must be explored.

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Section: Generatormentioning

confidence: 97%

Section: Service Life Failure Mode Identificationmentioning

confidence: 99%

Failure Mode Identification and End of Life Scenarios of Offshore Wind Turbines: A Review

Luengo

Kolios

2015

Energies

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“…The literature collects different critical failures for the generator [30][31][32][33][34][35], and for the power electronics and electric controls failure [30,34,36]. Figure 5 shows the failure root distribution in power electronic systems [37].…”

Section: Electrical/electronic Failures Analysismentioning

confidence: 99%

“…The main electrical faults are due to open-circuits or short-circuits in the rotor or stator [30] that could cause overheating [69]. Previous research work has demonstrated that bearings, rotors and stators involve a high failure rate in WTs [35]. The bearings failures of the generator are usually caused by cracks, asymmetry and imbalance [70].…”

Section: Ft Dynamic Analysis For Converter Generator Electrical Andmentioning

confidence: 99%

Optimal Dynamic Analysis of Electrical/Electronic Components in Wind Turbines

et al. 2017

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Electrical and electronic components are very important subcomponents in modern industrial wind turbines. Complex multimegawatt wind turbines are continuously being installed both onshore and offshore, continuously increasing the demand for sophisticated electronic and electrical components. In this work, most critical electrical and electronic components in industrial wind turbines have been identified and the applicability of appropriate condition monitoring processes simulated. A fault tree dynamic analysis has been carried out by binary decision diagrams to obtain the system failure probability over time and using different time increments to evaluate the system. This analysis allows critical electrical and electronic components of the converters to be identified in different conditions. The results can be used to develop a scheduled maintenance that improves the decision making and reduces the maintenance costs.

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“…Although the popularity of gear-less WTs using permanentmagnet synchronous generators (PMSGs) is more important in offshore, geared WTs with DFIGs still represent about 50 % of that market (65 % including onshore) [5]. By avoiding important downtimes and enabling planned and less frequent maintenance, fault tolerance as well as condition monitoring and early detection of faults are particularly interesting in offshore, due to difficult and expensive access [6], [7]. At sea 20 to 25 % of the total income effectively need to be invested in operation and maintenance compared to 10 to 15 % in onshore [5].…”

Section: Introductionmentioning

confidence: 99%

Rotor-current and position estimator for doubly-fed induction generators - application to sensor-fault detection

Mollet

Gyselinck

2016

2016 IEEE International Energy Conference (ENERGYCON)

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Abstract-A combined encoder and rotor-current-sensor fault detection and isolation algorithm for doubly-fed induction machines is presented. A rotor-position and current estimator based on air-gap power vector computation is used for residual generation. A cumulative-sum function permits detecting and isolating the investigated faults. The algorithm is experimentally tested on a 3 kW generator in steady and transient regimes. Sensor outages as well as current-sensor gain drifts and offsets are investigated. Transients do not significantly affect the algorithm, which also allows for a very short detection time for the most critical faults.

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Condition monitoring of wind generators

Cited by 95 publications

References 13 publications

Failure Mode Identification and End of Life Scenarios of Offshore Wind Turbines: A Review

Failure Mode Identification and End of Life Scenarios of Offshore Wind Turbines: A Review

Optimal Dynamic Analysis of Electrical/Electronic Components in Wind Turbines

Rotor-current and position estimator for doubly-fed induction generators - application to sensor-fault detection

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