A statistical model for risk management of electric outage forecasts
A statistical model for risk management of electric outage forecasts
复制标题
停电预测风险管理统计模型
DOI：
10.1147/jrd.2010.2044836
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发表时间：
2010
期刊：
影响因子：
--
通讯作者：
J. Hosking
中科院分区：
文献类型：
--
作者：
Hongfei Li;L. Treinish;J. Hosking
飓风、龙卷风、雷暴等恶劣天气事件造成的停电风险管理在电力配电运营中发挥着重要作用。基于适当空间尺度上的天气预报的损害预测可以通过降低与恢复工作相关的经济和社会成本来提高风险管理的效率。我们开发了一种方法，通过在贝叶斯分层框架中使用空间数据的泊松回归模型，以适合电力公司使用的方式预测停电次数。特别关注从停电数据的多个空间分辨率和空间相关性的角度构建包含停电数据不确定性的模型。停电预测模型是利用美国东北部一家电力公司的历史停电数据开发的。该公司正在其架空配电系统和应急管理操作中使用该模型。我们讨论迄今为止的结果以及如何应用该模型。除了损害预测之外，我们还开发了风险可视化工具，通过在地理地图上显示损害预测的不确定性。
Risk management of power outages caused by severe weather events, such as hurricanes, tornadoes, and thunderstorms, plays an important role in electric utility distribution operations. Damage prediction based on weather forecasts on an appropriate spatial scale can improve the efficiency of risk management by reducing the economic and societal costs associated with restoration efforts. We have developed a method of predicting the number of outages in a fashion that is suitable for use by electric utilities by using a Poisson regression model for spatial data in a Bayesian hierarchical framework. Particular attention is given to building models that incorporate uncertainty in the outage data from the perspective of multiple spatial resolutions and spatial correlation in the outage data. The outage-prediction model was developed using historical outage data from an electric utility company in the northeastern part of the United States. The model is being used by that company in the operations of its overhead electrical distribution system and emergency management operations. We discuss results to date and how the model is being applied. In addition to the damage forecasts, we have developed tools for risk visualization by displaying the uncertainty of the damage forecasts on geographic maps.