Abstract
Performance (availability and yield) and reliability of wind turbines can make the difference between success and failure of wind farm projects and these factors are vital to decrease the cost of energy. During the last years, several initiatives started to gather data on the performance and reliability of wind turbines on- and offshore and published findings in different journals and conferences. Even though the scopes of the different initiatives are similar, every initiative follows a different approach and results are therefore difficult to compare. The present paper faces this issue, collects results of different initiatives and harmonizes the results. A short description and assessment of every considered data source is provided. To enable this comparison, the existing reliability characteristics are mapped to a system structure according to the Reference Designation System for Power Plants (RDS-PP®). The review shows a wide variation in the performance and reliability metrics of the individual initiatives. Especially the comparison on onshore wind turbines reveals significant differences between the results. Only a few publications are available on offshore wind turbines and the results show an increasing performance and reliability of offshore wind turbines since the first offshore wind farms were erected and monitored.
Highlights
The installation of wind turbines (WT) is booming
An easy and commonly used indicator to describe the performance of a WT is the capacity factor (CF), which is the ratio of the turbines actual power output over a period of time to its theoretical power output [8,9]
This paper focuses on a holistic view on WT and does not include initiatives dealing with single systems of the turbine like the “Wind Turbine Gearbox
Summary
The installation of wind turbines (WT) is booming. During 2016 more than 54 GW of wind capacity was erected worldwide. Looking backwards at many years of operational experience from various WT, required to use a consistent set of data from the first till the last observation and intended to provide an elemental view on the gained experience rather than exploring innovative approaches to analyze data, most initiatives focus on well know and frequently used metrics. Such innovative approaches are, intensively considered in current research. Dienst and Beseler [7] applied different methods for anomaly detection on SCADA-Data of offshore WT
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