Resilience-Oriented Distribution Network Investment Planning Framework Under Windstorm Uncertainties With Explicit Economic Valuation

Power system resilience against high-impact lowprobability (HILP) events such as windstorms has become increasingly critical due to the threat of climate change. However, traditional investment planning frameworks typically fail to economically justify resilience enhancements due to the very low probability of HILP events (i.e., their expected value tends to be zero). This study proposes a framework that assigns economic value to specific resilience levels using constraints. A two-stage stochastic mixed-integer linear programming model is formulated with a resilience metric threshold constraint that incentivises resilience enhancement investments regardless of HILP event probabilities, explicitly linking investment costs to resilience levels. Uncertainties from windstorm events are captured using scenarios generated through Monte Carlo simulation based on a spatiotemporal model. Resilience enhancement options including overhead line hardening and distributed generator installation are considered. The framework is validated on a real network, using a cost-resilience Pareto front to provide decision-makers with explicit economic trade-off information.