Resilience-based importance assessment and hardening measures of power systems components

Increasingly frequent natural disasters and man-made attack threaten the critical infrastructure. The power systems which play the crucial role in daily life are vulnerable to those extreme events. Improving the resilience has become an inevitable requirement for the modern power system. It is significant to assess the importance of each component, since it can help identify critical component, strengthen grid structure, design restoration strategy, and improving resource allocation efficiency for disaster prevention and mitigation, and it can also provide us an effective hardening measure. This paper proposes a component importance assessment approach of power systems for improving resilience under wind storms and an effective hardening measures can be obtained base on it. First, the component failure rate model under wind storms is established, according to the model, system states under wind storms can be sampled by the non-sequential Monte Carlo simulation method. For each system state, an optimal restoration scheme is then figured out by solving a component repair sequence optimization model considering crew dispatching. After solving the MILP problem iteratively, the component importance ranking result can be obtained by Copeland ranking method. Finally, the ranking result can provide us effective hardening measures. IEEE RTS 24-bus system is adapted to illustrate the efficiency of the method.