Abstract
Understanding the mechanism of large scale outages is the precondition for designing of an effective prevention scheme. Complex system study shows that sudden transitions of the system from one regime to another may happen due to the nonlinear interaction among consisting components. Power systems are good examples of complex systems, and previous research shows that their critical transitions can be observed and predicted by statistical measures. These critical transitions include voltage collapse and system's entering a higher stress level from a long-term evolutional perspective. This paper continues the analysis of critical transitions in self-organized power system by Oak-PSERC-Alaska (OPA) model, a well-accepted model for the study of cascading blackouts from long-term perspective. Based on the self-organization mechanism designed in OPA, the mechanism of critical transition of power system entering a critical state is explained. The effects of local reliability on the transition is analyzed by comparing different cases. Time series of fractional load-shedding and fractional line loading are constructed and the performance of early warning of these two time series are discussed. The proposed research provide more insights on the mechanism of large blackouts, and easily available early warning signals, which are possible to implement as early warning of large catastrophic power system outage. Moreover, the fact that our research is conducted from a long-term point of view enables it to serve as a planning-assistant tool for a future power system with higher resilience.
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