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

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.

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.

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.

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.