Exploring cascading outages and weather via processing historic data
Exploring cascading outages and weather via processing historic data
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通过处理历史数据探索级联停电和天气
DOI：
10.24251/hicss.2018.345
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发表时间：
2017
期刊：
影响因子：
--
通讯作者：
J. Reynolds
中科院分区：
文献类型：
--
作者：
I. Dobson;NichelleLe Carrington;Kai Zhou;Zhaoyu Wang;B. Carreras;J. Reynolds
我们描述了一些批量的历史初始线路停电的统计数据，并形成应急列表和了解哪些初始停电可能会导致进一步级联的影响。我们使用历史停电数据，通过原因代码和NOAA风暴数据来估计天气对级联的影响。恶劣天气会显著增加停电率，并与级联效应相互作用，应在级联模型和模拟中考虑。我们建议如何天气影响可以纳入OPA级联模拟和验证。有很好的前景，以改善数据处理和模型的批量统计的历史停电数据，使级联可以更好地理解和量化。
We describe some bulk statistics of historical initial line outages and the implications for forming contingency lists and understanding which initial outages are likely to lead to further cascading. We use historical outage data to estimate the effect of weather on cascading via cause codes and via NOAA storm data. Bad weather significantly increases outage rates and interacts with cascading effects, and should be accounted for in cascading models and simulations. We suggest how weather effects can be incorporated into the OPA cascading simulation and validated. There are very good prospects for improving data processing and models for the bulk statistics of historical outage data so that cascading can be better understood and quantified.
影响因子：
6.6
作者：
J. Bialek;E. Ciapessoni;D. Cirio;E. Cotilla-Sánchez;C. Dent;I. Dobson;P. Henneaux;P. Hines;J. Jardim;Stephen S. Miller;M. Panteli;M. Papic;A. Pitto;J. Quirós-Tortós;Dee Wu
通讯作者：
J. Bialek;E. Ciapessoni;D. Cirio;E. Cotilla-Sánchez;C. Dent;I. Dobson;P. Henneaux;P. Hines;J. Jardim;Stephen S. Miller;M. Panteli;M. Papic;A. Pitto;J. Quirós-Tortós;Dee Wu