LI Suo, HUANG Lingling, LIU Yang, MIAO Yuzhi. An Offshore Wind Farm Maintenance Strategy Based on Wind Turbine Condition Information[J]. Modern Electric Power, 2022, 39(1): 26-35. DOI: 10.19725/j.cnki.1007-2322.2021.0004
Citation: LI Suo, HUANG Lingling, LIU Yang, MIAO Yuzhi. An Offshore Wind Farm Maintenance Strategy Based on Wind Turbine Condition Information[J]. Modern Electric Power, 2022, 39(1): 26-35. DOI: 10.19725/j.cnki.1007-2322.2021.0004

An Offshore Wind Farm Maintenance Strategy Based on Wind Turbine Condition Information

  • In allusion to underutilizing status messages of wind generation units during the operation and maintenance of offshore wind farm, an offshore wind farm maintenance strategy based on condition information of wind generation units was proposed. Firstly, considering the affection of environmental factors and the interaction among components on the condition information, the definition of dynamic deterioration degree was given and utilized to describe the deterioration degree of each component of wind power unit, and a fuzzy comprehensive evaluation method was used to establish the state assessment model for wind power units. Secondly, according to the actually measured operating data of each wind generation unit the wind farm’s generation units to be maintained were determined. Thirdly, in allusion to the selected generation units to be maintained and combining with the predicted results of the wind speed within the subsequent maintenance period, a short-term offshore wind farm preventive maintenance decision model, in which the minimum maintenance cost in a single maintenance period was taken as the objective and the limited offshore maintenance time and the accessibility were taken as the constraints, was constructed to optimize the maintenance time and the path of the wind power generation units of the offshore wind farm. Finally, combining with the instance data of a certain offshore wind farm in China the case study was performed. The effectiveness of the constructed model is verified.
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