Roozbeh Bakhshi and Peter Sandborn
CALCE, Center for Advanced Life Cycle Engineering, Department of Mechanical Engineering, University of Maryland, College Park, Maryland 20740, USA
With renewable energy and wind energy in
becoming a main stream mean s of energy production , the
reliability aspect of wi nd turbine s and their sub assemblies has
become a topic of interest for owners and manufacturers of
wind turbines. Operation and Maintenance ( O&M costs
account for more than 25 % of total costs of onshore wind
projects. These costs are even higher for offs hore projects.
Effective management of O&M costs of wind turbines depends
on accurate failure prediction for sub assemblies. There are
numerous models that predict failure times and O&M costs of
wind farms. All these models have inputs in the form of
relia bility parameters. These parameters are usually generated
by researchers using field failure data. There are several
databases that report the failure data of operating wind turbines.
Researches use the failure data to generate the reliability
parameters. However, in order to perform the analysis or use the
results of the analysis, one must understand the underlying
assumptions of the database along with information about the
wind turbine population in the database such as their power
rating, age, etc . In t his work, we analyze the relevant
assumptions and discuss what information is required from a
database in order to improve the reliability analysis.