Performance-based maintenance of gas turbines for reliable control of degraded power systems

被引:19
作者
Mo, Huadong [1 ]
Sansavini, Giovanni [1 ]
Xie, Min [2 ]
机构
[1] Swiss Fed Inst Technol, Dept Mech & Proc Engn, Inst Energy Technol, Reliabil & Risk Engn Lab, Zurich, Switzerland
[2] City Univ Hong Kong, Syst Engn & Engn Management, Hong Kong, Hong Kong, Peoples R China
关键词
Degraded control systems; Performance -based maintenance; Wiener process; Unit-to-unit variability; Load frequency control; REMAINING USEFUL LIFE; MONTE-CARLO METHOD; DEGRADATION DATA; PREDICTIVE MAINTENANCE; WIENER-PROCESSES; FAULT-DETECTION; MODEL; PROGNOSTICS; TIME; RELIABILITY;
D O I
10.1016/j.ymssp.2017.10.021
中图分类号
TH [机械、仪表工业];
学科分类号
0802 ;
摘要
Maintenance actions are necessary for ensuring proper operations of control systems under component degradation. However, current condition-based maintenance (CBM) models based on component health indices are not suitable for degraded control systems. Indeed, failures of control systems are only determined by the controller outputs, and the feedback mechanism compensates the control performance loss caused by the component deterioration. Thus, control systems may still operate normally even if the component health indices exceed failure thresholds. This work investigates the CBM model of control systems and employs the reduced control performance as a direct degradation measure for deciding maintenance activities. The reduced control performance depends on the underlying component degradation modelled as a Wiener process and the feedback mechanism. To this aim, the controller features are quantified by developing a dynamic and stochastic control block diagram-based simulation model, consisting of the degraded components and the control mechanism. At each inspection, the system receives a maintenance action if the control performance deterioration exceeds its preventive-maintenance or failure thresholds. Inspired by realistic cases, the component degradation model considers random start time and unit-to-unit variability. The cost analysis of maintenance model is conducted via Monte Carlo simulation. Optimal maintenance strategies are investigated to minimize the expected maintenance costs, which is a direct consequence of the control performance. The proposed framework is able to design preventive maintenance actions on a gas power plant, to ensuring required load frequency control performance against a sudden load increase. The optimization results identify the trade-off between system downtime and maintenance costs as a function of preventive maintenance thresholds and inspection frequency. Finally, the control performance-based maintenance model can reduce maintenance costs as compared to CBM and pre-scheduled maintenance. (C) 2017 Elsevier Ltd. All rights reserved.
引用
收藏
页码:398 / 412
页数:15
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