A Multi-stage Quantitative Resilience Optimization Model of Power Systems Subjected to Hurricane Hazards

Abstract

Power systems are essential to national security, economic prosperity, public health, and safety. However, as the frequency of extreme events and man-made attacks has increased dramatically in recent years, making resilience theory has become a new direction for responding to low-probability high-impact events. In power systems, resilience is essential in maintaining functionality, reducing losses, and speeding up recovery when encountering a disruptive event. This study develops a resource optimization allocation framework based on multiple resilience objectives by understanding the relationship between resilience performance and dynamic decisions. A multi-resilience-objective mixed-integer linear programming (MROMILP) model is formulated to optimize the resource allocation scheme for each resilience stage under limited internal resources of power systems under hurricane hazards. The IEEE 30-bus test system is used to validate the usability of the model.