Abstract

Climate change leads to extreme climate events that result in frequent wildfires that cause numerous adverse societal impacts. Public Safety Power Shutoffs, adopted by utilities to minimize the risk of wildfires, pose many challenges to electricity consumers. Microgrids, have been proposed to improve the resilience of energy infrastructure during wildfire events for vulnerable communities. However, a comprehensive techno-economic and environmental assessment of the potential of such energy systems have not been performed. To address this research gap, the present study introduces a modeling framework, consisting of (1) clustering algorithms that identify the communities based on building footprint data, fire hazard severity, and renewable energy potential; (2) a building simulation model to quantify the energy demand; and (3) an energy system optimization model to assist the Microgrid design. A novel optimization tool was introduced to model Microgrids in wildland-urban interface, and subsequently, a comprehensive assessment was performed, focusing on seven localities from California, United States, with different climatic conditions. The study reveals that Microgrids can keep the average levelized energy cost and annual Public Safety Power Shutoffs below $0.3/kilowatt-hour (kWh) and 2%–3% (of the annual energy demand), respectively. Furthermore, renewable energy penetration levels can be maintained above 60% of the annual energy demand. Therefore, Microgrid may become an attractive solution to reduce the adverse impacts of wildfires and enhance the resilience of energy infrastructure. However, the study reveals that Microgrid cannot completely eliminate the Public Safety Power Shutoffs. The levelized cost and renewable energy generation curtailments (waste of renewable energy) become notably high when attempting to eliminate Public Safety Power Shutoffs completely. A notable reduction in energy storage cost is essential to achieve zero Public Safety Power Shutoffs, and this is expected with the evolution of energy storage technologies. The present study recommends Microgrids for communities affected by wildfires to enhance the resilience of energy infrastructure and protect the health and safety of residents. The modeling framework and optimization tool developed in this study can be used by stakeholders and their consultants to inform design and optimization of Microgrids for investment decision making.

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