Condition monitoring benefit for onshore wind turbines: sensitivity to operational parameters

The economic case for condition monitoring (CM) applied to wind turbines is currently not well quantified and the factors involved are not fully understood. In order to make more informed decisions regarding whether deployment of CM for wind turbines is economically justified, a refined set of probabilistic models capturing the processes involved are presented. Sensitivity of the model outputs with respect to variables of interest are investigated within the bounds of published data and expert opinion. The results show that the levels of benefit are dependent on a variety of factors including wind profile, typical downtime duration and wind turbine sub-component replacement cost.

[1]  Krzysztof Pawlikowski,et al.  On credibility of simulation studies of telecommunication networks , 2002, IEEE Commun. Mag..

[2]  M. Marseguerra,et al.  Simulation modelling of repairable multi-component deteriorating systems for 'on condition' maintenance optimisation , 2002, Reliab. Eng. Syst. Saf..

[3]  R. Poore,et al.  Alternative Design Study Report: WindPACT Advanced Wind Turbine Drive Train Designs Study; November 1, 2000 -- February 28, 2002 , 2003 .

[4]  Peter Tavner,et al.  Reliability analysis for wind turbines , 2007 .

[5]  E. Becker,et al.  Keeping the blades turning: Condition monitoring of wind turbine gears , 2006 .

[6]  Peter Tavner,et al.  Machine and Converter Reliabilities in Wind Turbines , 2006 .

[7]  Jochen Giebhardt,et al.  Rotor Condition Monitoring for Improved Operational Safety of Offshore Wind Energy Converters , 2005 .

[8]  Andrew T. Brint,et al.  Modelling the degradation of condition indices , 1999 .

[9]  L. Bertling,et al.  Maintenance Management of Wind Power Systems Using Condition Monitoring Systems—Life Cycle Cost Analysis for Two Case Studies , 2007, IEEE Transactions on Energy Conversion.

[10]  Faisal Khan,et al.  Development of a risk-based maintenance (RBM) strategy for a power-generating plant , 2005 .

[11]  Roy Billinton,et al.  Monte Carlo Simulation , 1992 .

[12]  G. J. Anders,et al.  A PROBABILISTIC MODEL FOR EVALUATING THE REMAINING LIFE OF ELECTRICAL INSULATION IN ROTATING MACHINES , 1990 .

[13]  Luca Podofillini,et al.  Condition-based maintenance optimization by means of genetic algorithms and Monte Carlo simulation , 2002, Reliab. Eng. Syst. Saf..

[14]  D. Jayaweera,et al.  Computing the value of security , 2002 .

[15]  Ronald N. Allan,et al.  Generation availability assessment of wind farms , 1996 .

[16]  J. Endrenyi,et al.  The Present Status of Maintenance Strategies and the Impact of Maintenance on Reliability , 2001, IEEE Power Engineering Review.

[17]  George J. Anders,et al.  A probabilistic model for evaluating the remaining life of evaluating the remaining life of electrical insulation in rotating machines , 1990 .

[18]  Mohammed Kishk,et al.  The Selection of a Suitable Maintenance Strategy for Wind Turbines , 2006 .

[19]  G. Kuczera,et al.  Markov Model for Storm Water Pipe Deterioration , 2002 .

[20]  David McMillan,et al.  Towards quantification of condition monitoring benefit for wind turbine generators , 2007 .

[21]  M. B. Zaayer,et al.  Reliability, availability and maintenance aspects of large-scale offshore wind farms, a concepts study , 2001 .

[22]  B. Bak-Jensen,et al.  Aspects of Relevance in Offshore Wind Farm Reliability Assessment , 2007, IEEE Transactions on Energy Conversion.

[23]  Roy Billinton,et al.  Incorporating multistate unit models in composite system adequacy assessment , 2004 .

[24]  Miguel A. Sanz-Bobi,et al.  SIMAP: Intelligent System for Predictive Maintenance: Application to the health condition monitoring of a windturbine gearbox , 2006, Comput. Ind..

[25]  Armin Schnettler,et al.  Asset management techniques , 2006 .