Metrics and Quantification of Operational and Infrastructure Resilience in Power Systems

Resilience to high impact low probability events is becoming of growing concern, for instance to address the impacts of extreme weather on critical infrastructures worldwide. However, there is, as yet, no clear methodology or set of metrics to quantify resilience in the context of power systems and in terms of both operational and infrastructure integrity. In this paper, the resilience “trapezoid” is therefore introduced which extends the resilience “triangle” that is traditionally used in existing studies, in order to consider the different phases that a power system may experience during an extreme event. The resilience trapezoid is then quantified using time-dependent resilience metrics that are specifically introduced to help capture the critical system degradation and recovery features associated to the trapezoid for different temporal phases of an event. Further, we introduce the concepts of operational resilience and infrastructure resilience to gain additional insights in the system response. Different structural and operational resilience enhancement strategies are then analyzed using the proposed assessment framework, considering single and multiple severe windstorm events that hit the 29-bus Great Britain transmission network test case. The results clearly highlight the capability of the proposed framework and metrics to quantify power system resilience and relevant enhancement strategies.

[1]  W. Adger Social and ecological resilience: are they related? , 2000 .

[2]  Min Ouyang,et al.  A three-stage resilience analysis framework for urban infrastructure systems , 2012 .

[3]  Ross Baldick,et al.  Research on Resilience of Power Systems Under Natural Disasters—A Review , 2016, IEEE Transactions on Power Systems.

[4]  Pierluigi Mancarella,et al.  Influence of extreme weather and climate change on the resilience of power systems: Impacts and possible mitigation strategies , 2015 .

[5]  K. A T H L E E N T I E R N E Y A N D M I C H E L B R Conceptualizing and Measuring Resilience a Key to Disaster Loss Reduction , 2022 .

[6]  Pierluigi Mancarella,et al.  The Grid: Stronger, Bigger, Smarter?: Presenting a Conceptual Framework of Power System Resilience , 2015, IEEE Power and Energy Magazine.

[7]  A. Rose Economic resilience to natural and man-made disasters: Multidisciplinary origins and contextual dimensions , 2007 .

[8]  Pierluigi Mancarella,et al.  Multi-phase assessment and adaptation of power systems resilience to natural hazards , 2016 .

[9]  K. Bell,et al.  Wind related faults on the GB transmission network , 2014, 2014 International Conference on Probabilistic Methods Applied to Power Systems (PMAPS).

[10]  Pierluigi Mancarella,et al.  Boosting the Power Grid Resilience to Extreme Weather Events Using Defensive Islanding , 2016, IEEE Transactions on Smart Grid.

[11]  Michel Bruneau,et al.  Framework for analytical quantification of disaster resilience , 2010 .

[12]  Pierluigi Mancarella,et al.  Power System Resilience to Extreme Weather: Fragility Modeling, Probabilistic Impact Assessment, and Adaptation Measures , 2017, IEEE Transactions on Power Systems.

[13]  Devanandham Henry,et al.  Generic metrics and quantitative approaches for system resilience as a function of time , 2012, Reliab. Eng. Syst. Saf..

[14]  C. S. Holling Resilience and Stability of Ecological Systems , 1973 .

[15]  K. C. Kapur,et al.  Methodology for Assessing the Resilience of Networked Infrastructure , 2009, IEEE Systems Journal.

[16]  Min Ouyang,et al.  Multi-dimensional hurricane resilience assessment of electric power systems , 2014 .

[17]  Min Ouyang,et al.  Time-dependent resilience assessment and improvement of urban infrastructure systems. , 2012, Chaos.