## 5 Conclusions  
This paper presents a comprehensive resilience evaluation framework that can be used by distribution system operators to plan and evaluate resilience-driven investments, particularly in the presence of critical loads in the system. The framework incorporates the priority of the critical loads in the islanded microgrid operation with DER as the system succumbs to extreme weather events. It also develops a practical model to estimate post-event load restoration time by considering the priority of the loads, the dependency of the outage components, and the availability of the repair crew. The paper evaluates the impact of various investment strategies on the performance of critical and non-critical loads by utilizing the novel metrics proposed in this paper, such as DLH and NDLH, as well as other traditional metrics, such as EOD and EENS.  
A series of case studies within each investment strategy--infrastructure hardening, DER deployment, and repair process management--performed on a modified IEEE-69 bus test system reveals several key findings. Firstly, the strategic hardening of the main feeder provides better system-level resilience improvement compared to that of the targeted hardening of critical sections. However, the hardening of critical sections significantly reduces the outage duration and unserved energy for critical loads, which is a preferred investment model due to the high outage costs associated with the critical loads. Nevertheless, utilities must use care with this approach, as when increasing the resilience of critical loads, the performance gap between priority loads and the rest of the system tends to increase, which can be limited through strategic hardening alternatives. Second, DER management strategies provide a resilient solution at lower costs; however, their improvement is restricted by the vulnerability of the infrastructure needed to serve the loads. A hybrid strategy of combining DER deployment, along with hardening of strategically selected sections, provides substantial improvements, especially for the critical loads. Likewise, while the investment in repair crew has a uniform impact on the performance of both critical and non-critical loads, critical loads can be promptly restored through proactively deploying the crew near the site of priority loads as soon as the event warning is received.  
The framework developed in this paper and the analysis of the results provide a valuable decision-making tool for system planners to design resilience-driven investments more effectively in an era of increasing climate-induced prolonged outages. The framework can be utilized to develop cost-optimization models for detailed economic analysis by integrating the investment costs of various resilience enhancement scenarios and the outage cost estimation using the value of the lost-load for the expected outage duration. A detailed sensitivity analysis can be carried out using the optimal DER siting and sizing, coupled with strategic and targeted hardening alternatives, to determine an optimal investment model.  
Conceptualization, R.K.; Methodology, A.S.; Software, A.S.; Validation, A.S.; Formal analysis, A.S.; Investigation, A.S.; Resources, R.K.; Data curation, A.S.; Writing--original draft, A.S.; Writing--review & editing, R.K.; Supervision, R.K.; Project administration, R.K.; Funding acquisition, R.K. All authors have read and agreed to the published version of the manuscript.  
Natural Science and Engineering Research Council: RGPIN-2020-04477.  
Not applicable.  
The data presented in this study are openly available in the Appendix A and Reference [33] of the paper.  
The authors declare no conflict of interest.