Integrated Predictive Analytics and Optimization for Opportunistic Maintenance and Operations in Wind Farms
Integrated Predictive Analytics and Optimization for Opportunistic Maintenance and Operations in Wind Farms
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DOI：
10.1109/tpwrs.2017.2666722
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发表时间：
2017-02
影响因子：
6.6
通讯作者：
M. Yildirim;N. Gebraeel;X. Sun
中科院分区：
文献类型：
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作者：
M. Yildirim;N. Gebraeel;X. Sun
本文提出了一种风电场维护的综合框架，该框架结合了i）预测分析方法，该方法使用实时传感器数据来预测风力涡轮机的未来退化和剩余寿命，ii）一种新颖的优化模型，该模型将这些预测转化为风电场的利润最佳维护和运营决策。迄今为止，预测分析的大多数应用集中在单个涡轮机系统上。相比之下，本文提供了一个无缝集成的预测分析与决策的一队风力涡轮机。操作决策确定调度配置文件。维护决策考虑传感器驱动的最佳维护计划之间的权衡，并通过将风力涡轮机维护分组在一起而产生的显着成本降低-一个称为机会性维护的概念。我们专注于两种类型的风力涡轮机。对于运行中的风力涡轮机，我们找到了一个最佳的车队级基于状态的维护计划由传感器数据驱动。对于出现故障的风力涡轮机，我们确定进行纠正性维护以开始发电的最佳时间。还考虑了运营和维护决策之间的经济和随机相关性。在i）100-涡轮机风电场案例和ii）200-涡轮机多个风电场案例上进行的实验证明了我们的建议相对于传统政策的优势。
This paper proposes an integrated framework for wind farm maintenance that combines i) predictive analytics methodology that uses real-time sensor data to predict future degradation and remaining lifetime of wind turbines, with ii) a novel optimization model that transforms these predictions into profit-optimal maintenance and operational decisions for wind farms. To date, most applications of predictive analytics focus on single turbine systems. In contrast, this paper provides a seamless integration of the predictive analytics with decision making for a fleet of wind turbines. Operational decisions identify the dispatch profiles. Maintenance decisions consider the tradeoff between sensor-driven optimal maintenance schedule, and the significant cost reductions arising from grouping the wind turbine maintenances together—a concept called opportunistic maintenance. We focus on two types of wind turbines. For the operational wind turbines, we find an optimal fleet-level condition-based maintenance schedule driven by the sensor data. For the failed wind turbines, we identify the optimal time to conduct corrective maintenance to start producing electricity. The economic and stochastic dependence between operations and maintenance decisions are also considered. Experiments conducted on i) a 100-turbine wind farm case, and ii) a 200-turbine multiple wind farms case demonstrate the advantages of our proposal over traditional policies.