RAPID: A Cross-Infrastructure Data-driven Approach to Modeling and Simulation of the 2021 Texas Power Outage

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This Grants for Rapid Response Research (RAPID) project will collect cross-domain data and develop an open-source synthetic grid model with a ready-to-use dataset for event simulation and quantitative assessment of the February 2021 Texas power outages. The extreme winter storm and associated electricity outages in February 2021 are estimated to have caused more than 70 deaths and $150 billion economic loss in Texas. Given the complexity and confidentiality of the actual electric grid model and relevant information, it becomes very challenging for the broader research community to develop quantitative assessments and credible insights on what, why, and how this event occurred, and more importantly, what could be done in the future to prevent it from happening again. This grant will develop an open-source cross-domain approach to build a realistic synthetic model with a ready-to-use dataset for the power outage simulation and quantitative assessments of corrective measures for the broader infrastructure research community. The intellectual merit of this project is as follows. First, this team will collect timely data and develop an open-source large-scale synthetic grid model tailored for the event assessment via rigorous calibration. Second, we will integrate cross-infrastructure outage data along the timeline that enable scientific simulation for the broader research community. This ready-to-use cross-domain blackout dataset will cover the details of the event along the timeline, including both the electric power system and the natural gas system. Last but not least, this team will perform consistent simulation methods and metrics for the quantitative studies on the effectiveness of potential corrective measures and their combined effects. This team plans to actively engage under-represented groups in this project. We will actively disseminate this through a wide range of venues, including a Texas A&M Smart Grid Center and Texas A&M Energy Institute webinar and workshop series. The finding of this project will be incorporated in the PI's newly developed course on Data Sciences and Application for Modern Power Systems. The team has a track record of industry-oriented short courses on data sciences and reliability assessment for the power industry.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.