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Maintenance Strategy Optimization of a Coal-Fired Power Plant Cooling Tower through Generalized Stochastic Petri Nets

机译:通过广义随机培养网的燃煤电厂冷却塔优化优化

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摘要

Determining the ideal size of maintenance staff is a daunting task, especially in the operation of large and complex mechanical systems such as thermal power plants. On the one hand, a significant investment in maintenance is necessary to maintain the availability of the system. On the other hand, it can significantly affect the profit of the plant. Several mathematical modeling techniques have been used in many different ways to predict and improve the availability and reliability of such systems. This work uses a modeling tool called generalized stochastic Petri net (GSPN) in a new way, aiming to determine the effect that the number of maintenance teams has on the availability and performance of a coal-fired power plant cooling tower. The results obtained through the model are confronted with a thermodynamic analysis of the cooling tower that shows the influence of this system’s performance on the efficiency of the power plant. Thus, it is possible to determine the optimal size of the repair team in order to maximize the plant’s performance with the least possible investment in maintenance personnel.
机译:确定维护人员的理想尺寸是令人生畏的任务,特别是在诸如热电厂等大型和复杂的机械系统的运行中。一方面,需要大量的维护投资来维持系统的可用性。另一方面,它可以显着影响植物的利润。已经以许多不同的方式使用了几种数学建模技术来预测和改善这种系统的可用性和可靠性。这项工作采用了一种以新的方式称为广义随机培养网(GSPN)的建模工具,旨在确定维护团队数量对燃煤电厂冷却塔的可用性和性能的影响。通过该模型获得的结果面临着对冷却塔的热力学分析,其显示该系统对电厂效率的影响。因此,可以确定维修团队的最佳尺寸,以使工厂的性能最大化,在维护人员中最少的投资。

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