## 6 Conclusions  
This study presents an FBN for the risk assessment of power grids based on historical failure incident data and expert elicitation. RTO data are utilized for calculating CPr, and experts from the power industry and academia are consulted for calculating FPr. The main contributions of this research are summarized below. * This study identifies twenty-six external and internal critical risk variables responsible for power grid shutdowns by presenting a comprehensive risk level spectrum. To offset the vagueness and uncertainty in historical data, the FST using expert elicitation is integrated with a BN to present a more nuanced risk assessment approach. * The initial risk assessment with sixteen BEs using CPr and ten BEs using FPr shows that the probability of TE (power grid shutdown) is 3%. Environmental factors account for 11% of TE failure rates, followed by equipment conditions, which account for 36%. A higher failure probability from equipment conditions confirmed that the root causes are the tripping of transmission lines and circuit breakers. A failure probability of 11% from environmental factors endorsed the increased risk of the likelihood of TEs because of storms and weather conditions. * Expert elicitation is endorsed as a nuanced approach to integrating a BN and FST. For instance, based on RTO historical data, SCADA is less likely to disrupt the power grid's functionality, with a failure probability of only 1%. However, results from expert opinion confirmed it as a serious threat with a 12% probability of failure. * Diagnosis inference with 100% confirmation of TE highlights the most critical IEs as environmental factors and equipment conditions, with 59% and 22% failure probabilities, respectively. Environmental factors remain the most significant IE, with the root cause of fire risk as the most influential BE, with a failure rate of 35%, followed by storms  
Figure 11: Diagnosis inference using 100% failure probability as TE. (13%). Equipment conditions are also a critical IE with root causes of transmission lines (24%), generators (20%), and circuit breakers (19%). Diagnosis inference confirmed the authenticity of the FBN for cybersecurity and operational parameters, with leading root causes for the likelihood of TEs being unauthorized access (10%) and frequency changes (9%). * A comparison of an FBN constructed through CPr plus FPr versus FBN (FPr only) yields similar results for the likelihood of TEs (3%). Still, significant variations exist in the failure probabilities of BEs and IEs. Expert elicitation confirmed that the equipment condition is the most critical IE (13%), followed by weather conditions and operational parameters with a failure probability of 9%, and cybersecurity and environmental factors with 8%. * The expert's opinions yielded different results than historical failure data since the latest safety and maintenance strategies altered the threat levels, which can be captured through expert elicitation, as historical data remained constant over time. Moreover, due to improved mitigation strategies, there are fewer chances of failure incidents of the same type in the future, making CPr less relevant than expert opinions. Integrating FBNs using expert elicitation is an effective risk assessment technique for evaluating these viable assets. However, certain limitations when using an expert's opinion, such as long distances and unpredictable environmental conditions, may lead to the under- or overestimation of risk levels. To counter these challenges, robotic inspection and intelligent perception may be incorporated to complement the proposed approach for future studies. Y.M. : Methodology, Investigation, Writing--Original Draft, Visualization, Validation, Software, Resources, Formal Analysis, Data Curation, Conceptualization. N.Y. ([PERSON]): Validation, Software, Resources, Formal Analysis, Data Curation. N.Y. ([PERSON]): Writing--Review and Editing, Visualization, Methodology, Investigation, Formal Analysis. Y.H.