Analysis of wind turbine degradation via the nacelle transfer function

Shin, Dongheon; Kim, Hyeonwu; Ko, Kyungnam

doi:10.1007/s12206-015-0846-y

Cited by 7 publications

(4 citation statements)

References 11 publications

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“…The relationship between the weighting factors and the reference value is expressed as

k_{1} r_{p} + k_{2} r_{e} + k_{3} r_{T} + k_{4} r_{f} = R

where

k_{1}

k_{2}

k_{3}

, and

k_{4}

are the weighting factors, which are positive numbers to ensure that the function monotonically increases. In reference [15], the value of the aging assessment criterion is equal to unity in the absence of aging. The comprehensive indicators of the two turbines within one year were 1.014 and 1.085, respectively.…”

Section: Comprehensive Aging Assessment Methodsmentioning

confidence: 99%

“…The average load factor declined from 28.5% when the wind turbine was new to 21% after 19 years; this level of degradation increased the levelized cost of electricity by 9%. To identify and compare the annual degradation rates of inland and seaside wind turbines, other studies calculated the capacity factor annual degradation rate by applying power curves to the Rayleigh distribution [14,15]. Power curves were drawn for each year according to IEC 61400-12-1 [16] using raw nacelle wind data covering five to six consecutive years.…”

Section: Performance Degradationmentioning

confidence: 99%

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Comprehensive aging assessment of pitch systems combining SCADA and failure data

Wei

Zheng

Zareipour

et al. 2021

IET Renewable Power Gen

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Due to the recent rapid development of the wind energy industry, many wind turbines that have been operational over long periods will face degradation caused by aging effects; hence, an appropriate aging assessment method for wind turbines and their components is essential for optimizing the asset management and maintenance strategy of a wind farm. An aging assessment method is proposed for wind‐turbine electric‐pitch systems by introducing four individual aging indicators based on the examination of supervisory control and data acquisition (SCADA) and failure data, i.e. function, energy‐consumption, temperature, and reliability indicators. To obtain a reliable comprehensive assessment, an information‐fusion method has been developed based on a given reference value; the weighting factors in the information fusion were calculated based on the reference value, while reliability and robustness were verified using the SCADA and failure data from a wind farm over three years.

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“…The relationship between the weighting factors and the reference value is expressed as

k_{1} r_{p} + k_{2} r_{e} + k_{3} r_{T} + k_{4} r_{f} = R

where

k_{1}

k_{2}

k_{3}

, and

k_{4}

Section: Comprehensive Aging Assessment Methodsmentioning

confidence: 99%

Section: Performance Degradationmentioning

confidence: 99%

Comprehensive aging assessment of pitch systems combining SCADA and failure data

Wei

Zheng

Zareipour

et al. 2021

IET Renewable Power Gen

View full text Add to dashboard Cite

show abstract

“…Therefore, reliable monitoring for detection, diagnosis, and prediction of faults arising on such parts is of great importance. An insightful review on the technical challenges related to nacelles is conducted by Islam et al, 68 while Shin et al 69 determined the machine degradation by means of the capacity factor (CF), via the identification of nacelle transfer function, and Helsen et al 70 captured grid loss events through the investigation of drivetrain vibrations. A special category of contributions in this discipline comprises studies on gearboxes and components interacting therewith.…”

Section: Introductionmentioning

confidence: 99%

Vibration‐based monitoring of a small‐scale wind turbine blade under varying climate conditions. Part I: An experimental benchmark

Tatsis

Dertimanis

et al. 2020

Struct Control Health Monit

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Structural health monitoring (SHM) has been increasingly exploited in recent years as a valuable tool for assessing performance throughout the life cycle of structural systems, as well as for supporting decision-making and maintenance planning. Although a great assortment of SHM methods has been developed, only a limited number of studies exist serving as reference basis for the comparison of different techniques. In this paper, the vibration-based assessment of a small-scale wind turbine (WT) blade is experimentally investigated, with the aim of establishing a benchmark case study for the SHM community. The structure under consideration, provided by Sonkyo Energy as part of the Windspot 3.5 kW WT model, is tested in both healthy and damaged states under varying environmental, that is, temperature, conditions as imposed by means of a climatic chamber. This study offers a thorough documentation of the configuration of this experimental benchmark, including the types of deployed sensors, the nature of excitation and available measurements, and the investigated damage scenarios and environmental variations enforced. Lastly, an overview of the raw and processed measurement data, made available to researchers via an open access Zenodo repository, is herein provided.

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“…Kim et al [9] conducted power performance testing for two 3-MW wind turbines in compliance with the IEC 61400-12-2 procedure. Shin et al [10][11][12] proposed a method for identifying wind turbine degradation using NTF and analysed the annual capacity factor reduction rate for multiple wind turbines.…”

Section: Introductionmentioning

confidence: 99%

Application of the Nacelle Transfer Function by a Nacelle-Mounted Light Detection and Ranging System to Wind Turbine Power Performance Measurement

Shin

2019

Energies

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To examine the applicability of the nacelle transfer function (NTF) derived from nacelle light detection and ranging (LIDAR) measurements to wind turbine power performance testing without a met mast, wind turbine power performance measurement was carried out at the Dongbok wind farm on Jeju Island, South Korea. A nacelle LIDAR was mounted on the nacelle of a 2-MW wind turbine to measure wind conditions in front of the turbine rotor, and an 80-m-high met mast was installed near another wind turbine to measure the free-stream wind speed. The power measurement instruments were installed in the turbine tower base, and wind speeds measured by the nacelle anemometer of the turbine were collected by the SCADA (Supervisory control and data acquisition) system. The NTF was determined by the table method, and then the power curve drawn using the NTF by the nacelle LIDAR (PCNTF, NL) was compared with the power curves drawn in compliance with International Electrotechnical Commission (IEC) standards, 61400-12-1 and 61400-12-2. Next, the combined standard uncertainties of the power curves were calculated to clarify the magnitude of the components of the uncertainties. The uncertainties of annual energy production (AEP) were also estimated by assuming that wind speed is a Rayleigh cumulative distribution. As a result, the PCNTF, NL was in good agreement with the power curves drawn in accordance with the IEC standards. The combined standard uncertainty of PCNTF, NL was almost the same as that of the power curve based on IEC 61400-12-2.

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Analysis of wind turbine degradation via the nacelle transfer function

Cited by 7 publications

References 11 publications

Comprehensive aging assessment of pitch systems combining SCADA and failure data

Comprehensive aging assessment of pitch systems combining SCADA and failure data

Vibration‐based monitoring of a small‐scale wind turbine blade under varying climate conditions. Part I: An experimental benchmark

Application of the Nacelle Transfer Function by a Nacelle-Mounted Light Detection and Ranging System to Wind Turbine Power Performance Measurement

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