Extreme temperature events affecting the electricity distribution system of the metropolitan area of Buenos Aires (1971–2013)
Extreme temperature events affecting the electricity distribution system of the metropolitan area of Buenos Aires (1971–2013)
复制标题
影响布宜诺斯艾利斯大都市区配电系统的极端温度事件（1971-2013）
DOI：
10.1016/j.enpol.2017.04.006
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发表时间：
2017
期刊：
影响因子：
9
通讯作者：
D. Gomez
中科院分区：
文献类型：
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作者：
D. Santágata;Paula S. Castesana;Cristina Rössler;D. Gomez
我们研究了寒潮和热浪对布宜诺斯艾利斯市区主要停电的影响。对分布尾部发生的事件的影响进行了评估，根据统计得出的阈值估计了最低温度、最高温度和每小时用电量的偏差，并使用了三组数据：温度观测（1911-2013）；灾难数据库（1971-2013）和每小时用电量（2006-2013）中报告的主要停电情况。事实证明，这些偏差（超出）足以表明极端温度事件对配电系统造成的压力，从而导致大规模停电。基于这些指标，我们发现，在寒潮和热浪期间，配电系统承受着类似的压力，但它更容易受到热浪的影响（2006年至2013年期间，寒潮期间停电3次，热浪期间停电20次）。对于热浪，二项回归逻辑模型的结果提供了在极端温度和电力消耗压力超出方面灾难性供应中断的概率的充分描述。该方法可用于其他希望评估极端温度事件对配电基础设施影响的城市。
We studied the role of cold waves and heat waves on major power outages in the metropolitan area of Buenos Aires. Impacts of events occurring in the tails of distributions were assessed estimating deviations of minimum temperature, maximum temperature and hourly electricity consumption with respect to statistically derived thresholds and using three sets of data: temperature observations (1911–2013); major power outages reported in a disaster database (1971–2013) and hourly electricity consumption (2006–2013). These deviations (exceedances) proved to be adequate indicators of the stress posed by extreme temperature events to the electricity distribution system leading to major blackouts. Based on these indicators, we found that the electricity distribution system was under similar stress during cold waves or heat waves, but it was much more vulnerable to heat waves (three blackouts under cold waves against 20 under heat waves between 2006 and 2013). For heat waves, the results of a binomial regression logistic model provided an adequate description of the probability of disastrous supply interruptions in terms of exceedances in extreme temperatures and electricity consumption stress. This approach may be of use for other cities wishing to evaluate the effects of extreme temperature events on the electricity distribution infrastructure.