Risk analysis of critical infrastructures emphasizing electricity supply and interdependencies

Factors underlying organizational resilience: The case of electric power restoration in New York City after 11 September 2001

“…A rich vein of research on interdependent critical infrastructure systems-in part motivated by the attacks of 11 September-has sought to conceptualize (Kröger 2008, Little 2002, Rinaldi et al 2001, measure (Francis & Bekera 2014, Johansson et al 2013, Pant et al 2014, model (Pendall et al 2010) and support (Gay & Sinha 2013, Kjølle et al 2012 the management of the links between systems such as electric power, water, wastewater, telecommunications and transportation, among others (for recent reviews, see (Ouyang 2014, Satumtira & Dueñas-Osorio 2010). Critical infrastructures (CIs) are here viewed as mixed human-machine systems composed of a large number of interacting components exhibiting nonlinear relationships, thus limiting their ability to be described, controlled or predicted at a systems level.…”

Definition of a Data Model to support Risk Analysis in the frame of Critical Infrastructures protection

“…The elements of the Risk Dimension are those typical of any Risk Analysis [4], and are defined as follows:…”

Vulnerability analysis of complementary transportation systems with applications to railway and airline systems in China

“…A detailed review of these approaches is provided by one of the authors in reference [18]. The empirical approaches utilize the post-event incident reports and data to analyze interdependent system vulnerability, which enable to identify frequent and significant failure patterns, quantify interdependency strength metrics to inform decision making, make empirically-based risk analysis and provide alternatives to minimize the risk [19][20][21][22][23]. The agent based approaches use agents to computationally represent components in an infrastructure (such as electric transformers or generators) or some important players (such as government or weather) related to system operation, and take a set of rules to describe agents' behaviors and their interactions with environment so that it can model all types of interdependencies among interdependent systems by discrete-event simulations, and provide scenario-based what-if analysis and the effectiveness assessment of different control strategies [24][25][26][27][28].…”