Application of FAHP-TOPSIS Method for Weighting and Prioritizing Resilience Indicators in a Combined Cycle Power Plant

S. Mousavi, Mahsa Jahadi Naeini, Farzad Behzadinejad
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Abstract

Background & Aims of the Study: Resilience means the ability of a system to predict, tolerate, and adapt to various disturbances and recover quickly to its original state. This study aims to weigh and prioritize the indicators affecting the resilience in a combined cycle power plant using the combined method of FAHP-TOPSIS. Materials and Methods: This is a descriptive-analytical and cross-sectional study conducted at the beginning of 2021 in the Kashan Combined Cycle Power Plant. In the first step, a literature review and semi-structured interviews with 25 experts were conducted to identify the indicators affecting resilience. A total of 20 affecting indicators were identified and divided into three groups: situational awareness, vulnerability, and adaptability. In the next step, we used the Fuzzy Analytical Hierarchy Process (FAHP) to determine the indicators’ weights of each group. In the end, we used the TOPSIS method to perform the final prioritization of the indicators. Results: The final results of prioritizing the indicators that affect resilience based on the outcomes of the TOPSIS method showed that the three indicators of structural stability (final weight=1), senior management awareness of the roles and responsibilities (final weight=0.075), and understanding and risk acceptance (final weight=0.067) play the most important roles, while logistics support index (final weight=0.029) is the least important indicator in determining the level of resilience. Conclusion: By recognizing and prioritizing the indicators affecting the level of resilience, corrective and preventive measures can be defined and implemented to improve safety and increase the resilience in combined cycle power plants based on the importance of each indicator. Also, the method introduced in this paper can be used as a scientific technique to identify and prioritize resilience indicators in other process industries such as oil and gas and petrochemical industries.
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FAHP-TOPSIS法在联合循环电厂弹性指标加权排序中的应用
研究背景和目的:弹性是指系统预测、容忍和适应各种干扰并迅速恢复到原始状态的能力。本研究旨在使用FAHP-TOPSIS的组合方法,对影响联合循环发电厂恢复力的指标进行权衡和排序。材料和方法:这是一项2021年初在卡山联合循环发电厂进行的描述性分析和横断面研究。在第一步中,对25名专家进行了文献综述和半结构化访谈,以确定影响复原力的指标。共确定了20个影响指标,并将其分为三组:态势感知、脆弱性和适应性。在下一步中,我们使用模糊层次分析法(FAHP)来确定每组指标的权重。最后,我们使用TOPSIS方法对指标进行了最终排序。结果:基于TOPSIS方法的结果对影响弹性的指标进行优先级排序的最终结果表明,结构稳定性(最终权重=1)、高级管理层对角色和责任的认识(最终权重=0.075)以及理解和风险接受(最终权重0.067)三个指标发挥着最重要的作用,而后勤保障指数(最终权重=0.029)是决定恢复力水平的最不重要的指标。结论:通过识别和优先考虑影响恢复力水平的指标,可以根据每个指标的重要性来确定和实施纠正和预防措施,以提高联合循环发电厂的安全性和恢复力。此外,本文介绍的方法可以作为一种科学技术,用于识别和优先考虑石油天然气和石化等其他加工行业的弹性指标。
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审稿时长
2 weeks
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