Research and Development Priorities for Energy Islanding of Military and Industrial Installations

. Identification of protective actions to reduce the vulnerability of safety-critical systems to malevolent acts: a sensitivity-based decision-making approach. Reliability Engineering and System Safety, Elsevier, 2016, 147, pp.9-18. Milan, Italy, Fax: 39-02-2399.6309, Phone: 39-02-2399 ABSTRACTA classification model based on the Majority Rule Sorting method has been previously proposed by the authors to evaluate the vulnerability of safety-critical systems (e.g., nuclear power plants) with respect to malevolent intentional acts.In this paper, we consider a classification model previously proposed by the authors based on the Majority Rule Sorting method to evaluate the vulnerability of safety-critical systems (e.g., nuclear power plants) with respect to malevolent intentional acts. The model is here used as the basis for solving an inverse classification problem aimed at determining a set of protective actions to reduce the level of vulnerability of the safety-critical system under consideration.To guide the choice of the set of protective actions, sensitivity indicators are originally introduced as measures of the variation in the vulnerability class that a safety-critical system is expected to undergo after the application of a given set of protective actions. These indicators form the basis of an algorithm to rank different combinations of actions according to their effectiveness in reducing the safety-critical systems vulnerability. Results obtained using these indicators are presented with regard to the application of: (i) one identified action 2 at a time, (ii) all identified actions at the same time or (iii) a random combination of identified actions. The results are presented with reference to a fictitious example considering nuclear power plants as the safety-critical systems object of the analysis.

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“…As presented in [25], an influential set of weights can suggest R&D priorities in protection of energy systems.…”

Section: Discussionmentioning

confidence: 99%

Identification of protective actions to reduce the vulnerability of safety-critical systems to malevolent acts: A sensitivity-based decision-making approach

Wang

Pedroni

Zio

2016

Reliability Engineering & System Safety

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“…The rankings of initiatives under the impact of the stressors for all criteria sets are used to identify the resilience of initiatives and assess the influence of stressors on priorities. To measure the influence of stressors, various methods have been used, including sum of square ranking changes, mean absolute rank change, and Kendall Tau‐b distance . In the following, the Spearman rank correlation coefficient, which is defined as follows, is used:

ρ = 1 - \frac{6 \sum_{i = 1}^{n} d_{i}^{2}}{n (n^{2} - 1)},

where

d_{i}

is the difference in ranking between the two samples under consideration for element i and n is the sample size, which in this case is the number of initiatives.…”

Section: Methodsmentioning

confidence: 99%

Resilience Analytics with Application to Power Grid of a Developing Region

et al. 2016

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Infrastructure development of volatile regions is a significant investment by international government and nongovernment organizations, with attendant requirements for risk management. Global development banks may be tasked to manage these investments and provide a channel between donors and borrowers. Moreover, various stakeholders from the private sector, local and international agencies, and the military can be engaged in conception, planning, and implementation of constituent projects. Emergent and future conditions of military conflict, politics, economics, technology, environment, behaviors, institutions, and society that stress infrastructure development are prevalent, and funding mechanisms are vulnerable to fraud, waste, and abuse. This article will apply resilience analytics with scenario-based preferences to identify the stressors that most influence a prioritization of initiatives in the electric power sector of Afghanistan. The resilience in this article is conceived in terms of the degree of disruption of priorities when stressors influence the preferences of stakeholders, and ultimately a prioritization of initiatives. The ancillary results include an understanding of which initiatives contribute most and least across strategic criteria and which criteria have the most impact for the analysis. The article concludes with recommendations for risk monitoring and risk management of the portfolio of stressors through the life cycle and horizon of grid capacity expansion.

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“…In the energy sector, the sections could be compliance and regulation, climate policy and carbon pricing, commodity price volatility, managing planning and public acceptance of risks, talent, renewable subsidies, low-carbon technologies, economic shocks, political intervention, and accessibility of capital. Another crucial application could be to guide the research and development for energy systems (e.g., smart and secure microgrids for industrial and military installations and solar cogeneration technologies) where deep uncertainties and emergent conditions are said to exist (Hamilton et al 2012). The applicability potential thus of the ToRS, the RSAF, and the LUOMEAR within high-risk and volatile environments can be vast if implemented with accountable governance structures and procedures.…”

Section: Potential Applications Of the Rsaf Frameworkmentioning

confidence: 99%

Development and Introduction of the Risk-Sentience Auxiliary Framework (RSAF) as an Enabler to the ISO 31000 and ISO 31010 for High-Risk Environments

Selvaseelan¹

2018

Administrative Sciences

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Abstract:The aim of this study was to develop, implement, and evaluate a new auxiliary enterprise risk management framework and process to serve as an enabler to the global ISO 31000 risk framework and ISO 31010 processes. This framework has been designed particularly for use within high-risk environments and those characterized by volatility, uncertainty, complexity, and ambiguity (VUCA). This paper proposes a methodology for optimization of structured sharing and grass-roots management of all available risk-sentience information with the assessed potential to develop into an identifiable risk in the future. The author introduces new risk terminology including risk-sentience, risk-sentience information, and risk-sentience management. The process involved the development of the Theory of Risk-Sentience (ToRS), Risk-Sentience Auxiliary Framework (RSAF) and a risk-sentience management process referred to as LUOMEAR (Learning from Uncertainties, Others Mistakes, Experiences and Anecdotal Reporting). Manchester Patient Safety Framework (MaPSaF), SWOT (Strengths, Weaknesses, Opportunities, and Threats) analysis, and a newly developed Risk-Sentience Fertility Checklist were used to conduct pre and post-trial evaluations. The findings include positive adjustments in safety culture, components of commitment to quality, communication and team-working around safety issues, access to evolving risk-information, and efficient sharing and management of recorded risk-information. Recommendations are made for more extensive application of both the proposed auxiliary risk framework and process within high-risk sectors to further explore its effectiveness and scope.

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Research and Development Priorities for Energy Islanding of Military and Industrial Installations

Cited by 34 publications

References 26 publications

Identification of protective actions to reduce the vulnerability of safety-critical systems to malevolent acts: A sensitivity-based decision-making approach

Identification of protective actions to reduce the vulnerability of safety-critical systems to malevolent acts: A sensitivity-based decision-making approach

Resilience Analytics with Application to Power Grid of a Developing Region

Development and Introduction of the Risk-Sentience Auxiliary Framework (RSAF) as an Enabler to the ISO 31000 and ISO 31010 for High-Risk Environments

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