## 4 Conclusions  
Substantial investments in transmission resources will be required to address the growing challenges of maintaining the reliability of power grids, stemming from the rising penetration of intermittent renewable energy sources and the growth in electric vehicles causing increased uncertainty in load profiles across the load centers. Ongoing research and development in smart technologies, such as energy storage, power electronics, and digital communication devices, provide opportunities for enhancing the capabilities of the transmission system. The appropriate investment in the selected emerging technologies should, however, enhance the grid network reliability and mitigate the cost of power outages. The methodology proposed and illustrated in this paper can be used by grid reliability planners to estimate the cost of outages originating from transmission facilities. The outage costs obtained from the proposed method can also be used to decide investment in grid resiliency enhancement against extreme weather that mainly impacts the grid network facilities.  
This paper presents and illustrates the methodology to estimate the outage costs originating from transmission component failures using data obtained from an outage cost survey conducted in the year 2017 in the Canadian province of Saskatchewan. Since past outage cost surveys were all focused on outages due to a lack of generation supply, this paper illustrates approximations required due to the lack of data needed to calculate outage costs originating from transmission failures. This paper shows that the amount of customer data required increases with the number of periods in the SPD model for the customer sector. The industrial sector SPD model has only one period, and therefore, the data from other existing surveys can be adequately utilized. The industrial and residential sectors account for over 80% of the total system load in most power systems, and therefore, concentrated efforts are required to plan appropriate survey questionnaires for the residential sector in order to obtain useful data to assess the transmission-originated outage costs. New  
Figure 8: CCDF at two different load points of the IEEE-RTS system.  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline \multirow{2}{*}{**Sector**} & \multicolumn{2}{c}{**Peak Demand \%**} & \multicolumn{2}{c}{**Energy Consumption \%**} \\ \cline{2-5}  & **Load Point 4** & **Load Point 14** & **Load Point 4** & **Load Point 14** \\ \hline Residential & 40\% & 19\% & 45\% & 14\% \\ \hline Farm & 15\% & 10\% & 10\% & 6\% \\ \hline Commercial & 30\% & 25\% & 35\% & 24\% \\ \hline Industrial & 15\% & 46\% & 10\% & 56\% \\ \hline \hline \end{tabular}
\end{table}
Table 13: Assumed sector load composition at two load points in IEEE-RTS 24-bus system.  
surveys that incorporate these recommendations will yield realistic outage costs that can then be used in value-based reliability or resiliency investments in emerging technologies and transmission facilities.  
Conceptualization, R.K.; methodology, R.K.; software, S.B.; validation, S.B.; formal analysis, S.B. and R.K.; investigation, S.B.; resources, R.K.; data curation, S.B.; writing--original draft preparation, S.B.; writing--review and editing, R.K.; visualization, R.K.; project administration, R.K.; funding acquisition, R.K. All authors have read and agreed to the published version of the manuscript.  
This research was funded by Natural Sciences and Engineering Research Council, Grant number 585294-2023.  
Not applicable.  
The data presented in this study are available on request from the corresponding author.  
The authors declare no conflict of interest.