Quantifying the Economic Value of Space Weather Forecasting for Power Grids: An Exploratory Study
Quantifying the Economic Value of Space Weather Forecasting for Power Grids: An Exploratory Study
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DOI：
10.1029/2018sw002003
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发表时间：
2018-12-01
影响因子：
3.7
通讯作者：
Burnett, C.
中科院分区：
文献类型：
--
作者：
Eastwood, J. P.;Hapgood, M. A.;Burnett, C.
准确了解空间气象的社会经济影响对于发展适当的业务服务、预报能力和减缓战略至关重要。解决这一问题的一种方法是开发基于物理的模型和框架，从而对风险和可能的影响进行自下而上的估计。在此，我们将介绍一个新框架的开发情况，以评估空间气象对配电网和电力供应的经济影响。特别是，我们专注于地磁亚暴的现象，这是相对本地化的时间和空间，并发生多次不同程度的地磁风暴。该框架使用AE指数来表征亚暴的严重程度，亚暴的影响由电网的弹性和可用预报的性质来调制。根据2003年、1989年和1859年的地磁暴资料，给出了10年一遇、30年一遇和100年一遇地磁暴事件中亚暴序列的可能情景。然后，可以使用标准技术，根据停电的持续时间和地理足迹，计算经济影响，包括国际溢出。说明性的计算是为欧洲部门，为各种预测和弹性的情况。然而，现有的数据在各区域之间差异很大，使目前界定全球总体经济影响的努力受挫。
An accurate understanding of space weather socioeconomic impact is fundamental to the development of appropriate operational services, forecasting capabilities, and mitigation strategies. One way to approach this problem is by developing physics-based models and frameworks that can lead to a bottom-up estimate of risk and likely impact. Here we describe the development of a new framework to assess the economic impact of space weather on power distribution networks and the supply of electricity. In particular, we focus on the phenomenon of the geomagnetic substorm, which is relatively localized in time and space, and occurs multiple times with varying severity during a geomagnetic storm. The framework uses the AE index to characterize substorm severity, and the impact of the substorm is modulated by the resilience of the power grid and the nature of available forecast. Possible scenarios for substorm sequences during a 1-in-10-, a 1-in-30-, and a 1-in-100-year geomagnetic storm events are generated based on the 2003, 1989, and 1859 geomagnetic storms. Economic impact, including international spill over, can then be calculated using standard techniques, based on the duration and the geographical footprint of the power outage. Illustrative calculations are made for the European sector, for a variety of forecast and resilience scenarios. However, currently available data are highly regionally inhomogeneous, frustrating attempts to define an overall global economic impact at the present time.