LAUSR

Abstract Optimal restoration of a real-time power system following a disruption is a complex process. In view of that and with increase in frequency and severity of power system outages across the US and their impact on consumers and utilities, North American Electric Reliability Corporation elevated the standard of compliance for power system restoration. While several utilities have proposed solutions addressing the elevated standards based on dynamic programming, they could not address the issues for large-scale power systems and real-time operations including those using steady-state and transient analysis due to the curses of dimensionality. In this paper, we introduce a restoration process based on approximate dynamic programming integrated with solution space reduction methodology. The main theoretical foundations of the methodology and key algorithms used in this restoration process include the knowledge of power system engineering, complex network science, concepts of graph theory, and dynamic programming in operation research. We first use the proposed method to demonstrate an optimal restoration process on the IEEE 118-bus test system and then on a 2000-bus synthetic test system. This method addresses the concerns related to the curses of dimensionality and simplifies the solution space and thus can be applied to various complex real-time operation settings.