Resilient energy transition in wildfire-prone regions: A multi-stage investment optimization

Abstract

The increasing frequency and severity of wildfires and heatwaves in California pose significant threats to energy infrastructure, necessitating a resilient and sustainable energy transition. This paper proposes a multi-stage investment optimization framework that integrates wildfire-induced disruptions, heatwave-driven demand surges, and carbon-neutral transition pathways into long-term power system planning. The framework employs a Distributionally Robust Optimization (DRO) approach to account for uncertainties in wildfire spread, transmission failures, and climate variability, ensuring robustness against worst-case scenarios. A GIS-driven wildfire risk assessment is incorporated to prioritize infrastructure reinforcements, microgrid deployment, and renewable integration in high-risk regions. The model balances three key objectives: (i) minimizing infrastructure investment costs, (ii) maximizing grid resilience through fire-adaptive expansion planning, and (iii) ensuring a carbon-neutral transition in alignment with climate policies. A case study of Los Angeles County during the 2025 Eaton Fire demonstrates the model’s effectiveness in enhancing power grid resilience and optimizing energy investment strategies under extreme climate conditions. The results highlight significant reductions in carbon emissions, improved microgrid reliability, and accelerated post-wildfire grid recovery, showcasing the model’s applicability for future wildfire-prone energy systems.