DOI: 10.5937/jaes10-2130
This is an open access article distributed under the CC BY-NC-ND 4.0 terms and conditions.
Volume 10 article 225 pages: 85 - 92
Nowadays, the availability of wind turbines usually
approaches the 98%. The objective is to increase the turbines availability, by
improving the wind turbine reliability especially for offshore plants. The wind
turbines reliability is a pivotal factor in the successfully function of a wind
power plant. High reliability can be achieved by understanding and minimizing
the failures of the system. Maintenance planning could make maintenance more
efficient and could lead to a reduction of failure events. In order to decide the
most effective maintenance strategy, it should be identified the most critical
components of the wind turbines, which are prone to failures. The maintenance strategy should take into both the
reliability improvement and the reduction of maintenance cost. It is
essential to determine and record the main cause that provokes the failure
event. The data logging and statistical processing of failure information could
improve the reliability of the system components. A wind turbine is a complex
power generating system consisting of several structural, electrical and
mechanical components. Its efficiency depends largely on its reliability level.
In the present study, the factors that affect the reliability of a wind turbine
are presented, as well as the analytical way of calculating its reliability. The reliability analysis of the wind turbine is
based on the systemic approach of the wind turbine subsystems, as its total
reliability depends directly on the reliability of the subsystems. It
is based on a technical analysis of the reliability of complex systems. The
model used is the Fault Tree Analysis (FTA), which is an identification method
for probable causes of system failure. The relation of reliability,
maintainability and availability is also presented and explained by the example
of a small wind farm.
The
authors wish to thank ROKAS S.A. for providing valuable information regarding
the technical characteristics and access to the failure data base of their
wind turbines.
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