Dynamic probabilistic risk analysis of the fast cascade phase of large disturbances in power system

Abstract

Power systems have experienced wide-area disturbances in the last decades, including large blackouts in the U.S. and Europe that impacted millions of customers. According to previous blackout analysis, the development of a cascading event leading to a blackout can be split in two phases. In an initial "slow cascade" phase, an initiating contingency (e.g. a line trip), though not supposed to challenge the electrical stability of the grid because of the N-1 security criterion, triggers a thermal transient developing on characteristic times much longer than the electrical time constants. This transient increases significantly the likelihood of additional contingencies. The loss of additional elements can then trigger an electrical instability. This is at the origin of the subsequent "fast cascade" phase, where a rapid succession of events can possibly lead the system to blackout. This paper is devoted to the study of the fast cascade phase of power system large disturbances. Dynamic Probabilistic risk assessment (PRA) has been developed, mostly in nuclear engineering, for identifying dangerous accident scenarios, while capturing the interaction between the dynamic evolution of a system in transient conditions and the occurrence of events along an accident sequence. Discrete dynamic event trees (DDET) is the core of the scheme used in this research. Misoperation of distance protection systems, involved in the propagation of disturbances, is integrated into the approach to provide more trustworthy results. The objective of this paper is the identification of dangerous scenarios leading to blackout in the fast cascade phase and the estimation of their frequency, using dynamic PRA. The methodology is applied to a test grid and results are analyzed.info:eu-repo/semantics/publishe