# Valuing Resilience Benefits of Microgrids for an Interconnected Island Distribution System
## 5 Conclusions  
This research work presented the economic resilience performance of a multi-island electric utility during Hurricanes Irma and Maria, calculated for the islands of Vieques and Culebra, through resilience curves and a probabilistic risk-based resilience valuation methodology. The resilience curves suggest it took more than three months to completely restore Vieques. When using IEEE suggested resilience metrics [4], this would result in a storm event X near 100%, which is a total failure. Given how devastating Hurricane Maria was, it is difficult to assert the fragility of the system pre-disaster. To enhance resilience, a microgrid solution is proposed, the cost of which was measured against the societal impact of the two hurricanes. The proposed microgrids will rely on 10 MWh BESS and 15 MW PV generation and will provide up to a 42% reduction in diesel consumption during loss of the subtransmission supply and up to a 56% reduction in the annual energy consumption of the minigrid of Vieques and Culebra from the main island during blue sky operation. The economic analysis suggests the the proposed microgrid projects can add between $1.9 and $20 million of expected annual avoided loss by improving the reliability and resilience of the discussed locations, and by supporting the community in future major weather events. The scalable layered architecture under consideration allows scaling to larger systems, or as in the case of the proposed approach, build out resilient sublayers of the diesel microgrid as renewables are integrated through VPP or other energy procurement exercises. As the team plans implementation of the proposed microgrid, it is expected the proposed innovations will benefit underrepresented and vulnerable communities and the industry at large. Furthermore, as the parameters of the resilience valuation methodology are validated, it can serve as a basis for future cost-benefit analysis requirements from policies that encourage electrical system resilience investment. As shown by the direct comparison within a single case study of four different economic resilience valuation methods, the consideration of non-linear effects due to the compounding economic conditions over the dynamic evolution of especially long-duration power outages leads to a potentially different valuation of resilience benefits for a resilience investment that reduces outage risk. However, this case study did not validate the parameters for the time-varying customer damage function approach, and instead presents three illustrative parameterizations. While theoretically the time-varying customer damage function method is more precise than the three other methods presented, this study shows that obtaining valid parameters setting the shape of these damage functions is critical, since different parameterizations lead to valuations of resilience investments that span a wide range. Future work is necessary to achieve this validation, as outlined by [PERSON] et al. [11]. Furthermore, while a deterministic approach was illustrated to determining the probability of occurrence at different outage durations, in reality these values are highly uncertain. Future work should perform more rigorous uncertainty quantification and sensitivity analysis to describe the range of likely valuations for grid resilience investments. Conceptualization, A.B.N. ; methodology, A.B.N., S.E. and C.A. ; software, A.B.N. and S.E. ; validation, R.J., E.H. and S.B. ; formal analysis, A.B.N. and S.E. ; investigation, A.B.N. and S.E. ; resources, R.J. and S.B. ; data curation, C.A. and E.H.; writing--original draft preparation, A.B.N. and S.E. ; writing--review and editing, A.B.N., S.E., C.A. and R.J.; visualization, E.H.; supervision, S.B. ; funding acquisition, R.J. All authors have read and agreed to the published version of the manuscript. This work was authored (in part) by the National Renewable Energy Laboratory (NREL), operated by Alliance for Sustainable Energy, LLC, for the U.S. Department of Energy (DOE) under Contract No. DE-AC36-08 GO28308.