Resilience-Based Optimal Recovery Strategy for Cyber–Physical Power Systems Considering Component Multistate Failures

Abstract

This article investigates optimal recovery strategy of components for maximizing the resilience of the cyber–physical power system (CPPS), where a component represents a unique node or branch, such as generating stations and communication transmission lines. The proposed optimization model is built as a multimode resource-constrained project scheduling problem to incorporate system resilience, cascading failures of the CPPS, the diversity of recovery resources, execution modes of recovery activities, precedence of damaged components, as well as the availability, cost, and time of recovery resources. The failure propagation mechanisms are characterized by a cascading failure model, which is further embedded in the optimization model to quantify the system real-time performance during the recovery process, and determine whether repaired components can be reconnected to the system. The system resilience is quantified using a proposed time-dependent annual composite resilience metric based on a compound Poisson process. The proposed optimization model is solved using a modified simulated annealing algorithm. The system that couples the IEEE 30-bus model and a small-world communication network is used as a testbed to demonstrate the feasibility and effectiveness of the proposed modeling approach. Comparisons with existing optimization models in the literature show the superiority of the proposed model.