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Abstract

One of the most common causes of failures in complex systems in nature or engineering is an abrupt transition from a stable to an alternate stable state. Such transitions cause failures in the dynamic power systems. We focus on this transition from a stable to an unstable manifold for a rate-dependent mechanical power input via a numerical investigation in a theoretical power system model. Our studies uncover early transitions that depend on the rate of variation of mechanical input. Furthermore, we determine the dependency of a critical rate on initial conditions of the system. Accordingly, this knowledge of the critical rate can be used in devising an effective control strategy based on artificial intelligence (AI). Blackout is the short-term loss of the ability of a power grid to deliver reliable electric power supply. The global trend toward urbanization leads to an increase in demand for electric power that magnifies the challenge of controlling blackout. There are many causes for the power system failures, which can lead to a blackout. Often, our electric power system operates close to the stability margin, which significantly magnifies the chance of cascading failures in the presence of disturbances. The stability analysis conducted hitherto in the power system confined to either linear or nonlinear stability analysis by considering the power system as an autonomous system. However, the power system is a non-autonomous system in which parameters are time-dependent. In this paper, we study the rate-dependent variation of the control parameter and rate-induced transition in a mathematical model of the power system. As the transition will result in power system instability, leading to interruption of the supply and a massive loss of revenue, studying factors leading to transition is highly essential