Winter Storm Scenario Generation for Power Grids Based on Historical Generator Outages

2022 IEEE/PES Transmission and Distribution Conference and Exposition (T&D)(2022)

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摘要
We present a procedure for randomly generating realistic steady-state contingency scenarios based on the historical outage data from a particular event. First, we divide generation into classes and fit a probability distribution of outage magnitude for each class. Second, we provide a method for randomly synthesizing generator resilience levels in a way that preserves the data-driven probability distributions of outage magnitude. Finally, we devise a simple method of scaling the storm effects based on a single global parameter. We apply our methods using data from historical Winter Storm Uri to simulate contingency events for the ACTIVSg2000 synthetic grid on the footprint of Texas.
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关键词
contingency,inverse transform sampling,maximum likelihood estimation,Monte Carlo method,power generation,power system planning,scenario generation,winter storms,Winter Storm Uri
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