Quantifying and Demonstrating Power System Operational Resilience From Outage Data

The impact, frequency, and duration of extreme weather events have been increasing alarmingly in recent times due to the development of bipolarized weather conditions as a consequence of increased greenhouse gas emissions caused by the rapidly swelling consumption of fossil fuels, leading to climate change. Thus, fossil fuels are being replaced by the increased injection of renewable energy sources and smart metering and communication devices in the power system. However, due to the intermittency, low inertia, and less reliability of renewable sources and cybersecurity threats of the digitalized power system, its overall resilience is being challenged. Moreover, the lack of a widely accepted resilience metric has only contributed to worsening the tradeoff between renewable penetration and system resilience. In this work, these issues have been addressed by defining the resilience of a system and clearly distinguishing the resilience of the power system and the electric grid. Two novel terminologies, resilience capacity (RC) and resilience kinetics ratio (RKR) are proposed to expedite operational resilience quantification. Four resilience tiers are explained for different scenarios and corroborated by simulating an IEEE 5-bus model. Also, necessary formulae are devised involving the areas of the outage curve to propose a novel method of operational resilience quantification. The significance of the first and second derivatives of the resilience curve in measuring operational resilience is also demonstrated. Furthermore, multiple recovery scenarios are demonstrated in this work, which reflect RKR’s relevance in complementing existing metrics and area-based resilience calculations. For all these, an IEEE 39-bus model was deployed to develop the outage dataset because of the scarcity of such datasets due to the inclusion of sensitive information about critical infrastructures in them.