Economics of online structural health monitoring of wind turbines: Cost benefit analysis

Van Dam, Jeremy
Bond, Leonard
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Aerospace Engineering
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Mechanical Engineering
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Operations and maintenance (O&M) costs have an average share over the lifetime of the turbine of approximately 20%-25% of the total levelized cost per kWh of electricity produced. Online structural health monitoring (OSHM) and condition-based maintenance (CBM) of wind turbine blades has the potential to reduce O&M costs and hence reduce the overall cost of wind energy. OSHM and CBM offer the potential to improve turbine blade life cycle management, limit the number of physical inspections, and reduce the potential for missed significant defects. An OSHM system would reduce the need for physical inspections, and have inspections occur only after problem detection takes place. In the economics of wind energy, failures and unplanned outages can cause significant downtime, particularly while waiting for the manufacturing and shipping of major parts. This paper will report a review and assessment of SHM technologies and a cost benefit analysis, which will examine whether the added costs associated with an OSHM system will give an adequate return on the investment. One method in which OSHM reduces costs is, in part, by converting corrective maintenance to preventative maintenance. This paper shows that under both best and worse conditions implementing an OSHM system is cost effective in more than 50% of the trials, which have been performed. Opportunities appear to exist to improve the economic justification for implementing OSHM.


This proceeding may be downloaded for personal use only. Any other use requires prior permission of the author and AIP Publishing. This proceeding appeared in Van Dam, Jeremy, and Leonard J. Bond. "Economics of online structural health monitoring of wind turbines: Cost benefit analysis." AIP Conference Proceedings 650, no. 1 (2015): 899-908. DOI: 10.1063/1.4914695. Posted with permission.

Cost-benefit analysis, Wind turbines, Educational assessment, Wind energy