
Analysis of Failure and Maintenance Records in Aging Wind Farms to Inform End‐of‐Life Asset Management
Author(s) -
Elsahhar Amr U.,
Ezzat Ahmed Aziz,
Elsabbagh Adel,
Elbanhawy Amr Y.
Publication year - 2025
Publication title -
wind energy
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.743
H-Index - 92
eISSN - 1099-1824
pISSN - 1095-4244
DOI - 10.1002/we.70024
ABSTRACT As a considerable number of operational wind farms worldwide approach their end‐of‐life (EOL), critical decisions regarding their future will need to be made, including whether to repower, life‐extend, or decommission wind turbine assets. To aid in derisking this process and provide necessary information for EOL decision‐making and asset management, this paper investigates the failure rates and maintenance records of aging wind farms approaching their EOL. Focusing on two onshore wind farms in North Africa that have reached 20 years of service, we analyze multi‐year operations and maintenance (O&M) records to determine failure rates and downtimes of various wind turbine subassemblies and draw comparisons with key published O&M statistics in the literature. Furthermore, we investigate temporal patterns and correlations in failure rates and provide insights on the various failure modes for subassembilies with the highest contributors to the overall failure rate. Finally, we conduct cost‐criticality analyses to support the quantification of commercial risks as part of the information necessary for EOL decision‐making. A unique aspect of this research is its emphasis on the EOL phase of O&M in wind farms, in contrast to the vast body of literature that focuses on earlier operational phases. The results reveal distinct patterns of failure rates and identify the hydraulic system, sensors, and electrical system to be the most failure‐prone subassemblies. Meanwhile, the gearbox, the generator, and the hydraulic system are found to bear the highest economic risk at EOL. This analysis provides essential insights to aid O&M planners and managers in making better informed asset management decisions during the EOL phase, without directly dictating the optimal course of action.
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