The Feasibility of Energy Communities for Hurricane Resilience
DOI:
https://doi.org/10.31224/3899Keywords:
hurricane, energy, risk analysisAbstract
Climate extremes like hurricanes can devastate vulnerable power lines, resulting in large-scale power outages, e.g., Hurricane Beryl (2024) with 2.6 million customers in Texas, US. In response, peer-to-peer (P2P) energy sharing has emerged as a promising strategy to create energy communities (ECs) that become resilient by adopting distributed energy resources (DERs) to generate and share electricity locally, especially after disasters. We developed a validated high-fidelity model of power systems for 2,640 households, integrating geographical multi-sourced data with probabilistic risk analysis to assess the feasibility of ECs for hurricane resilience. Our study finds that ECs would have experienced shorter outages by 65.8% for Hurricane Isaias (2020) in Absecon City, New Jersey. We then utilized our power risk model to study the financial feasibility of ECs versus other measures (e.g., undergrounding lines) for resilience to future hurricanes in Absecon and compare it to Miami communities, in Florida, exposed to larger hurricanes. We show that benefits are larger in Miami, where ECs can shorten outages by 64.4%, 33%, and 50.54% than no grid upgrade, DERs without P2P sharing (non-ECs), and undergrounding. Battery backups and resilient solar panels enhanced ECs ability to operate in island mode, which would have reduced the percentage of households experiencing outages longer than a day by 74% during Hurricane Isaias (2020). Furthermore, we show that undergrounding results in a negative net present value (NPV) for communities, with households facing a 155% higher cash outflow compared to ECs, where the addition of solar panels reduces energy bills and increases savings. Our study demonstrates the importance of integrating resilience into energy policies, particularly as infrastructure evolves to meet the challenges of a changing climate.
Downloads
Downloads
Posted
License
Copyright (c) 2024 Prateek Arora, Luis Ceferino
This work is licensed under a Creative Commons Attribution 4.0 International License.