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The Use of Simulation to Reduce the Domain of 'Black Swans' with Application to Hurricane Impacts to Power Systems

机译：利用模拟减少“黑天鹅”的范围及其在飓风对电力系统的影响中的应用

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摘要

Recently, the concept of black swans has gained increased attention in the fields of risk assessment and risk management. Different types of black swans have been suggested, distinguishing between unknown unknowns (nothing in the past can convincingly point to its occurrence), unknown knowns (known to some, but not to relevant analysts), or known knowns where the probability of occurrence is judged as negligible. Traditional risk assessments have been questioned, as their standard probabilistic methods may not be capable of predicting or even identifying these rare and extreme events, thus creating a source of possible black swans. In this article, we show how a simulation model can be used to identify previously unknown potentially extreme events that if not identified and treated could occur as black swans. We show that by manipulating a verified and validated model used to predict the impacts of hazards on a system of interest, we can identify hazard conditions not previously experienced that could lead to impacts much larger than any previous level of impact. This makes these potential black swan events known and allows risk managers to more fully consider them. We demonstrate this method using a model developed to evaluate the effect of hurricanes on energy systems in the United States; we identify hurricanes with potentially extreme impacts, storms well beyond what the historic record suggests is possible in terms of impacts.
机译：近年来，黑天鹅的概念在风险评估和风险管理领域得到了越来越多的关注。已经提出了不同类型的黑天鹅，以区分未知的未知数（过去没有什么可以令人信服地指出其发生），未知的已知数（某些人知道，但不相关的分析家知道）或判断发生概率的已知已知数。可以忽略不计。传统的风险评估受到质疑，因为它们的标准概率方法可能无法预测甚至识别这些罕见和极端事件，因此可能成为黑天鹅的源头。在本文中，我们展示了如何使用仿真模型来识别以前未知的潜在极端事件，如果不进行识别和处理，则可能会以黑天鹅的身份出现。我们表明，通过操纵经过验证的模型来预测危害对目标系统的影响，我们可以识别以前未经历过的危害条件，这些危害条件可能导致比任何以前的影响水平大得多的影响。这使这些潜在的黑天鹅事件广为人知，并使风险管理者可以更充分地考虑它们。我们使用开发用于评估飓风对美国能源系统的影响的模型来演示此方法；我们确定飓风具有潜在的极端影响，就影响而言，风暴远远超过了历史记录所表明的可能性。

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