When a blackout occurs, it is important to reduce the time for power system restoration to minimize damage. For fast restoration, it is important to reduce taking time for the selection of generators, transmission lines and transformers. In addition, it is essential that a determination of a generator start-up sequence (GSS) be made to restore the power system. In this paper, we propose the optimal selection of black start units through the generator start-up sequence (GSS) to minimize the restoration time using generator characteristic data and the enhanced Dijkstra algorithm. For each restoration step, the sequence selected for the next start unit is recalculated to reflect the system conditions. The proposed method is verified by the empirical Korean power systems.

Abstract:The uncertainty of complex power systems increases the possibility of large blackouts due to the expectations of physical events, such as equipment failures, protection failures, control actions failure, operator error, and cyber-attacks. Cascading outage is a sequence of dependent failures of individual components that successively weaken the power system. A procedure to identify and evaluate the initiating events and perform sequential cascading analysis is needed. In this paper, we propose a new screening methodology based on sequential contingency simulation of cascading outages, including probabilistic analysis and visualization model. Performance of a detail cascading analysis using practical power systems is suggested and discussed. The proposed screening methodology will play a key role in identifying the uncontrolled successive loss of system elements.