Numerical methods for applying onshore failure rate to offshore operational conditions and assessing the benefits of condition monitoring

Xi Yu, David Infield, Sami Barbouchi, Redouane Seraoui

Research output: Contribution to conferencePaper

Abstract

The cost effectiveness of condition monitoring systems for offshore wind energy is uncertain and thus a research concern. Unlike onshore wind turbines, the O&M costs of offshore wind turbines are directly affected by the marine environment, mainly wind and wave conditions, and vessel costs are a main contributor to offshore O&M costs. The lack of offshore O&M data makes wind turbine component failure rates essential for component risk assessment and cost model design. However, the failure rate data, especially from the offshore turbines, are highly protected by the manufacturers and the offshore operators. The method developed in this paper deals with this lack of data by adjusting onshore failure rate data to offshore to account for the different operational conditions. Internal cooperation of a large onshore wind farm in the UK and a large Swedish offshore wind farm has been reached, and three-year-period operational data records are used for this research. Both the sites use Siemens -2.3-93 turbines, which enable the comparison with minimum deviation caused by the types of the turbines between onshore and offshore.Failure Modes Effect and Criticality Analysis (FMECA), which follows the U.S. Military Standard 1629a, has been applied in many industrial areas including onshore wind energy successfully but as yet there are no examples in an offshore wind context. In most cases, the components were ranked using the Risk Priority Number, and in one instance, a cost priority number.A statistical cost model with specific concern for offshore vessel cost and marine access thresholds is presented in this paper and compared with other cost models in the research domain. A sensitivity analysis is applied to the selected offshore wind farm through the cost model in terms of changing the failure detectability of the condition monitoring system, and compares the effectiveness of maintenance with and without condition monitoring.
LanguageEnglish
Number of pages12
Publication statusPublished - 18 May 2015
EventWINDPOWER 2015 - Orlando, United States
Duration: 18 May 201521 May 2015

Conference

ConferenceWINDPOWER 2015
CountryUnited States
CityOrlando
Period18/05/1521/05/15

Fingerprint

Condition monitoring
Numerical methods
Costs
Offshore wind farms
Turbines
Wind turbines
Wind power
Onshore wind farms
Offshore wind turbines
Turbine components
Cost effectiveness
Risk assessment
Failure modes
Sensitivity analysis

Keywords

  • offshore
  • failure rate translation
  • risk priority number
  • FMEA

Cite this

Yu, X., Infield, D., Barbouchi, S., & Seraoui, R. (2015). Numerical methods for applying onshore failure rate to offshore operational conditions and assessing the benefits of condition monitoring. Paper presented at WINDPOWER 2015, Orlando, United States.
Yu, Xi ; Infield, David ; Barbouchi, Sami ; Seraoui, Redouane. / Numerical methods for applying onshore failure rate to offshore operational conditions and assessing the benefits of condition monitoring. Paper presented at WINDPOWER 2015, Orlando, United States.12 p.
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Yu, X, Infield, D, Barbouchi, S & Seraoui, R 2015, 'Numerical methods for applying onshore failure rate to offshore operational conditions and assessing the benefits of condition monitoring' Paper presented at WINDPOWER 2015, Orlando, United States, 18/05/15 - 21/05/15, .

Numerical methods for applying onshore failure rate to offshore operational conditions and assessing the benefits of condition monitoring. / Yu, Xi; Infield, David; Barbouchi, Sami; Seraoui, Redouane.

2015. Paper presented at WINDPOWER 2015, Orlando, United States.

Research output: Contribution to conferencePaper

TY - CONF

T1 - Numerical methods for applying onshore failure rate to offshore operational conditions and assessing the benefits of condition monitoring

AU - Yu, Xi

AU - Infield, David

AU - Barbouchi, Sami

AU - Seraoui, Redouane

PY - 2015/5/18

Y1 - 2015/5/18

N2 - The cost effectiveness of condition monitoring systems for offshore wind energy is uncertain and thus a research concern. Unlike onshore wind turbines, the O&M costs of offshore wind turbines are directly affected by the marine environment, mainly wind and wave conditions, and vessel costs are a main contributor to offshore O&M costs. The lack of offshore O&M data makes wind turbine component failure rates essential for component risk assessment and cost model design. However, the failure rate data, especially from the offshore turbines, are highly protected by the manufacturers and the offshore operators. The method developed in this paper deals with this lack of data by adjusting onshore failure rate data to offshore to account for the different operational conditions. Internal cooperation of a large onshore wind farm in the UK and a large Swedish offshore wind farm has been reached, and three-year-period operational data records are used for this research. Both the sites use Siemens -2.3-93 turbines, which enable the comparison with minimum deviation caused by the types of the turbines between onshore and offshore.Failure Modes Effect and Criticality Analysis (FMECA), which follows the U.S. Military Standard 1629a, has been applied in many industrial areas including onshore wind energy successfully but as yet there are no examples in an offshore wind context. In most cases, the components were ranked using the Risk Priority Number, and in one instance, a cost priority number.A statistical cost model with specific concern for offshore vessel cost and marine access thresholds is presented in this paper and compared with other cost models in the research domain. A sensitivity analysis is applied to the selected offshore wind farm through the cost model in terms of changing the failure detectability of the condition monitoring system, and compares the effectiveness of maintenance with and without condition monitoring.

AB - The cost effectiveness of condition monitoring systems for offshore wind energy is uncertain and thus a research concern. Unlike onshore wind turbines, the O&M costs of offshore wind turbines are directly affected by the marine environment, mainly wind and wave conditions, and vessel costs are a main contributor to offshore O&M costs. The lack of offshore O&M data makes wind turbine component failure rates essential for component risk assessment and cost model design. However, the failure rate data, especially from the offshore turbines, are highly protected by the manufacturers and the offshore operators. The method developed in this paper deals with this lack of data by adjusting onshore failure rate data to offshore to account for the different operational conditions. Internal cooperation of a large onshore wind farm in the UK and a large Swedish offshore wind farm has been reached, and three-year-period operational data records are used for this research. Both the sites use Siemens -2.3-93 turbines, which enable the comparison with minimum deviation caused by the types of the turbines between onshore and offshore.Failure Modes Effect and Criticality Analysis (FMECA), which follows the U.S. Military Standard 1629a, has been applied in many industrial areas including onshore wind energy successfully but as yet there are no examples in an offshore wind context. In most cases, the components were ranked using the Risk Priority Number, and in one instance, a cost priority number.A statistical cost model with specific concern for offshore vessel cost and marine access thresholds is presented in this paper and compared with other cost models in the research domain. A sensitivity analysis is applied to the selected offshore wind farm through the cost model in terms of changing the failure detectability of the condition monitoring system, and compares the effectiveness of maintenance with and without condition monitoring.

KW - offshore

KW - failure rate translation

KW - risk priority number

KW - FMEA

UR - http://www.windpowerexpo.org/

M3 - Paper

ER -