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Adaptive Opportunistic Predictive Maintenance Strategy and Dynamic Scheduling System for Utility-Scale Onshore Wind Farms
编号：133 访问权限：仅限参会人 更新：2026-10-14 23:47:47 浏览：6次 口头报告

报告开始：暂无开始时间（Asia/Shanghai）

报告时间：暂无持续时间

所在会场：[暂无会议] [暂无会议段]

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摘要
Unscheduled downtime and operational inefficiency significantly increase the Levelized Cost of Electricity (LCOE) in utility-scale onshore wind farms. Maintenance practice in commercial wind farms is generally divided into reactive corrective maintenance and calendar-based preventive servicing, which leads to redundant tower climbing and prolonged idle waiting, while technician skills are often mismatched to task complexity. To address these limitations, this paper proposes an end-to-end Adaptive Opportunistic Predictive Maintenance (APdOM) strategy and closed-loop dynamic scheduling system. We establish a multi-attribute dynamic pricing space mapping maintenance tasks into four operational quadrants based on failure risk and downtime financial loss. An opportunistic time-window bundling mechanism is mathematically formulated to dynamically aggregate secondary servicing during mandatory turbine trips or forecast low-wind intervals. In addition, an industrial-grade cyber-physical dynamic scheduling engine is developed, which couples multi-source Supervisory Control and Data Acquisition (SCADA) telemetry with mobile field execution. Trace-driven replay on a full-year operational dataset from a 200 MW wind farm (100 wind turbines, 276 historical work orders) demonstrates that the proposed system reduces cumulative idle waiting downtime by 29.3% (saving 4,603 hours) and lowers the technician skill tier mismatch penalty by 52.7%. Continuous 30-day online deployment validates 100% automated dispatching with sub-second event-driven rescheduling, recovering an estimated 9.2 GWh of clean energy annually.
关键词
Onshore wind farms,predictive maintenance,opportunistic maintenance,dynamic scheduling,SCADA telemetry,cyber-physical systems
报告人
Fang Wang
Student Xi'an Jiaotong University

稿件作者
Fang Wang Xi'an Jiaotong University
Shibo Shang Xi'an Jiaotong University
Siyu Lin Xi'an Jiaotong University
Yaoyu Zhang Xi'an Jiaotong University
Pengcheng Zhang Xi'an Jiaotong University
Yalin Zhao Xi’an Jiaotong University
Siyu Du Xi'an Jiaotong University
Gangli Fang Xi’an Thermal Power Research Institute Co. Ltd
Bin Jiang Huaneng Gansu Energy Development Co., Ltd
Min Zhang Northwest University； China
Yong Zhao Xi’an Thermal Power Research Institute Co. Ltd
Yu Chen Xi'an Jiaotong University
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重要日期

  • 会议日期

    11月06日

    2026

    至

    11月08日

    2026

  • 10月15日 2026

    初稿截稿日期

主办单位
IEEE Instrumentation and Measurement Society
承办单位
Sichuan University
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