Novel Wind Turbine reliability model-implementation to estimate Wind Farms capacity credit

B. K. Subramanian, A. B. Attya, T. Hartkopf

Research output: Chapter in Book/Report/Conference proceedingConference contribution

4 Citations (Scopus)

Abstract

The expanded integration of wind energy imposes technical challenges to maintain system reliability. In order to tackle these challenges, comprehensive reliability models for wind turbines and related factors are essential. Proposed algorithm classifies Wind Turbine Generator (WTG) components based on their impact on WTG output. There upon, the WTG has a composite three-state reliability model which aggregates WTG foremost components. The chronological operation conditions of each component is obtained using state duration sampling method. Precise Wind Farms (WFs) reliability assessment requires accurate Wind Speed (WS) forecasting methods which acknowledge WSs propagation through WFs terrains. Thus, WS variations are developed based on Weibull distribution. Offered algorithms are integrated to estimate the capacity factor of some WFs using Monte Carlo simulation method. The implied WS data are recorded in certain locations in Egypt which are candidates to host WFs. The utilized simulation environments are MATLAB and Simulink.

LanguageEnglish
Title of host publication2014 16th International Conference on Harmonics and Quality of Power (ICHQP)
PublisherIEEE
Pages97-101
Number of pages5
ISBN (Electronic)9781467364874
DOIs
Publication statusPublished - 24 Jun 2014
Externally publishedYes
Event16th International Conference on Harmonics and Quality of Power - Bucharest, Romania
Duration: 25 May 201428 May 2014
Conference number: 16

Conference

Conference16th International Conference on Harmonics and Quality of Power
Abbreviated titleICHQP 2014
CountryRomania
CityBucharest
Period25/05/1428/05/14

Fingerprint

Wind turbines
Farms
Turbogenerators
Weibull distribution
Wind power
MATLAB
Sampling
Composite materials

Cite this

Subramanian, B. K., Attya, A. B., & Hartkopf, T. (2014). Novel Wind Turbine reliability model-implementation to estimate Wind Farms capacity credit. In 2014 16th International Conference on Harmonics and Quality of Power (ICHQP) (pp. 97-101). [6842923] IEEE. https://doi.org/10.1109/ICHQP.2014.6842923
Subramanian, B. K. ; Attya, A. B. ; Hartkopf, T. / Novel Wind Turbine reliability model-implementation to estimate Wind Farms capacity credit. 2014 16th International Conference on Harmonics and Quality of Power (ICHQP). IEEE, 2014. pp. 97-101
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abstract = "The expanded integration of wind energy imposes technical challenges to maintain system reliability. In order to tackle these challenges, comprehensive reliability models for wind turbines and related factors are essential. Proposed algorithm classifies Wind Turbine Generator (WTG) components based on their impact on WTG output. There upon, the WTG has a composite three-state reliability model which aggregates WTG foremost components. The chronological operation conditions of each component is obtained using state duration sampling method. Precise Wind Farms (WFs) reliability assessment requires accurate Wind Speed (WS) forecasting methods which acknowledge WSs propagation through WFs terrains. Thus, WS variations are developed based on Weibull distribution. Offered algorithms are integrated to estimate the capacity factor of some WFs using Monte Carlo simulation method. The implied WS data are recorded in certain locations in Egypt which are candidates to host WFs. The utilized simulation environments are MATLAB and Simulink.",
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Subramanian, BK, Attya, AB & Hartkopf, T 2014, Novel Wind Turbine reliability model-implementation to estimate Wind Farms capacity credit. in 2014 16th International Conference on Harmonics and Quality of Power (ICHQP)., 6842923, IEEE, pp. 97-101, 16th International Conference on Harmonics and Quality of Power, Bucharest, Romania, 25/05/14. https://doi.org/10.1109/ICHQP.2014.6842923

Novel Wind Turbine reliability model-implementation to estimate Wind Farms capacity credit. / Subramanian, B. K.; Attya, A. B.; Hartkopf, T.

2014 16th International Conference on Harmonics and Quality of Power (ICHQP). IEEE, 2014. p. 97-101 6842923.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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AU - Subramanian, B. K.

AU - Attya, A. B.

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N2 - The expanded integration of wind energy imposes technical challenges to maintain system reliability. In order to tackle these challenges, comprehensive reliability models for wind turbines and related factors are essential. Proposed algorithm classifies Wind Turbine Generator (WTG) components based on their impact on WTG output. There upon, the WTG has a composite three-state reliability model which aggregates WTG foremost components. The chronological operation conditions of each component is obtained using state duration sampling method. Precise Wind Farms (WFs) reliability assessment requires accurate Wind Speed (WS) forecasting methods which acknowledge WSs propagation through WFs terrains. Thus, WS variations are developed based on Weibull distribution. Offered algorithms are integrated to estimate the capacity factor of some WFs using Monte Carlo simulation method. The implied WS data are recorded in certain locations in Egypt which are candidates to host WFs. The utilized simulation environments are MATLAB and Simulink.

AB - The expanded integration of wind energy imposes technical challenges to maintain system reliability. In order to tackle these challenges, comprehensive reliability models for wind turbines and related factors are essential. Proposed algorithm classifies Wind Turbine Generator (WTG) components based on their impact on WTG output. There upon, the WTG has a composite three-state reliability model which aggregates WTG foremost components. The chronological operation conditions of each component is obtained using state duration sampling method. Precise Wind Farms (WFs) reliability assessment requires accurate Wind Speed (WS) forecasting methods which acknowledge WSs propagation through WFs terrains. Thus, WS variations are developed based on Weibull distribution. Offered algorithms are integrated to estimate the capacity factor of some WFs using Monte Carlo simulation method. The implied WS data are recorded in certain locations in Egypt which are candidates to host WFs. The utilized simulation environments are MATLAB and Simulink.

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Subramanian BK, Attya AB, Hartkopf T. Novel Wind Turbine reliability model-implementation to estimate Wind Farms capacity credit. In 2014 16th International Conference on Harmonics and Quality of Power (ICHQP). IEEE. 2014. p. 97-101. 6842923 https://doi.org/10.1109/ICHQP.2014.6842923