The electric power grid is a critical societal resource connecting multiple infrastructural domains such as agriculture, transportation, and manufacturing. The electrical grid as an infrastructure is shaped by human activity and public policy in terms of demand and supply requirements. Further, the grid is subject to changes and stresses due to solar weather, climate, hydrology, and ecology. The emerging interconnected and complex network dependencies make such interactions increasingly dynamic causing potentially large swings, thus presenting new challenges to manage the coupled human-natural system. This paper provides a survey of models and methods that seek to explore the significant interconnected impact of the electric power grid and interdependent domains. We also provide relevant critical risk indicators (CRIs) across diverse domains that may influence electric power grid risks, including climate, ecology, hydrology, finance, space weather, and agriculture. We discuss the convergence of indicators from individual domains to explore possible systemic risk, i.e., holistic risk arising from cross-domains interconnections. Our study provides an important first step towards data-driven analysis and predictive modeling of risks in the coupled interconnected systems. Further, we propose a compositional approach to risk assessment that incorporates diverse domain expertise and information, data science, and computer science to identify domain-specific CRIs and their union in systemic risk indicators.
翻译:电网是连接农业、交通和制造业等多个基础设施领域的重要社会资源。电网是连接农业、交通和制造业等多个基础设施领域的关键社会资源。电网是人类活动和公共政策在供需需求方面形成的。此外,电网还受到太阳天气、气候、水文学和生态等变化和压力的影响。新出现的相互关联和复杂的网络依赖性使这种相互作用日益活跃,造成潜在的大规模波动,从而对管理结合的人类-自然系统提出了新的挑战。本文件对各种模型和方法进行了调查,以探索电网和相互依存领域的重大相互关联影响。我们还提供了可能影响电网风险的不同领域,包括气候、生态、水文学、金融、空间气象和农业的相关关键风险指标。我们讨论了各个领域指标的趋同,以探索可能的系统风险,即跨界互联互通所产生的整体风险。我们的研究为数据驱动分析和预测相互关联的系统风险模型提供了重要的第一步。我们提出了一种组合方法,用以进行风险评估,将不同领域的专门知识和信息、数据科学和计算机科学纳入其系统风险联盟。