A Markov decision process model case for optimal maintenance of serially dependent power system components

断路器 组分(热力学) 可靠性工程 变压器 最佳维护 马尔可夫模型 马尔可夫链 马尔可夫决策过程 马尔可夫过程 维护措施 计算机科学 电力系统 状态维修 工程类 数学优化 功率(物理) 运筹学 数学 电压 统计 电气工程 机器学习 物理 热力学 量子力学
作者
Daniel Bumblauskas
出处
期刊:Journal of Quality in Maintenance Engineering [Emerald (MCB UP)]
被引量:7
标识
DOI:10.1108/jqme-09-2014-0050
摘要

Purpose – Using a case study for electrical power equipment, the purpose of this paper is to investigate the importance of dependence between series-connected system components in maintenance decisions. Design/methodology/approach – A continuous-time Markov decision model is formulated to find a minimum cost maintenance policy for a circuit breaker as an independent component while considering a downstream transformer as a dependent component. Maintenance of the dependent component is included implicitly in terms of the costs associated with certain state-action pairs. For policy and cost comparisons, a separate model is also formulated that considers only the circuit breaker as the independent component. After uniformizing the continuous-time models to discrete time, standard methods are used to solve for the average-cost-optimal policies of each model. Findings – The optimal maintenance policy and its cost differ significantly depending on whether or not the dependent component is considered. Research limitations/implications – Data used are from manufacturer databases; additional model validation could be conducted if applied to an electric utility asset fleet within their generation, transmission, and/or distribution system. This model and methodology are already being applied in other contexts such as industrial machinery and equipment, jet engines, amusement park rides, etc. Practical implications – The outcome of this model can be utilized by asset and operations managers to make maintenance decisions based on prediction rather than more traditional time- or condition-based maintenance methodologies. This model is being developed for use as a module in a larger maintenance information system, specifically linking condition monitor data from the field to a predictive maintenance model. Similar methods are being applied to other applications outside the electrical equipment case detailed herein. Originality/value – This model provides a structured approach for managers to decide how to best allocate their resources across a network of inter-connected equipment. Work in this area has not fully considered the importance of dependency on systems maintenance, particularly in applications with highly variable repair and replacement costs.
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