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Energy Resilience Impact of Supply Chain Network Disruption to Military Microgrids. INFRASTRUCTURES 2021. [DOI: 10.3390/infrastructures7010004] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
The ability to provide uninterrupted power to military installations is paramount in executing a country’s national defense strategy. Microgrid architectures increase installation energy resilience through redundant local generation sources and the capability for grid independence. However, deliberate attacks from near-peer competitors can disrupt the associated supply chain network, thereby affecting mission critical loads. Utilizing an integrated discrete-time Markov chain and dynamic Bayesian network approach, we investigate disruption propagation throughout a supply chain network and quantify its mission impact on an islanded microgrid. We propose a novel methodology and an associated metric we term “energy resilience impact” to identify and address supply chain disruption risks to energy security. The proposed methodology addresses a gap in the literature and practice where it is assumed supply chains will not be disrupted during incidents involving microgrids. A case study of a fictional military installation is presented to demonstrate how installation energy managers can adopt this methodology for the design and improvement of military microgrids. The fictional case study shows how supply chain disruptions can impact the ability of a microgrid to successfully supply electricity to critical loads throughout an islanding event.
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Maximization of availability of 1-out-of-2:G repairable dependent system. ADV APPL PROBAB 2016. [DOI: 10.1017/s0001867800018930] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Abstract
The IFR property of the stochastic process governing a one-component system supported by an inactive standby and a repair facility when the lifetime of one component and the repair time of the other component are dependent, is established. We solve the problem of selecting repair rates to maximize the steady-state availability for given component failure rates when a lower bound for the MTBF and upper bounds for the steady-state expected number of repairs of the components per unit time and expected number of failures of the system per unit time are given.
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Joshi BH, Dharmadhikari AD. Maximization of availability of 1-out-of-2: G repairable dependent system. ADV APPL PROBAB 2016. [DOI: 10.2307/1427648] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022]
Abstract
The IFR property of the stochastic process governing a one-component system supported by an inactive standby and a repair facility when the lifetime of one component and the repair time of the other component are dependent, is established. We solve the problem of selecting repair rates to maximize the steady-state availability for given component failure rates when a lower bound for the MTBF and upper bounds for the steady-state expected number of repairs of the components per unit time and expected number of failures of the system per unit time are given.
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Luo J, Li Y, Pershing J, Xie L, Chen Y. A methodology for analyzing availability weak points in SOA deployment frameworks. IEEE TRANSACTIONS ON NETWORK AND SERVICE MANAGEMENT 2009. [DOI: 10.1109/tnsm.2009.090303] [Citation(s) in RCA: 10] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
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Rishel TD, Canel C. A perspective on job assignments under varying scheduled maintenance scenarios. JOURNAL OF STATISTICS & MANAGEMENT SYSTEMS 2007. [DOI: 10.1080/09720510.2007.10701235] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/26/2022]
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Vineyard M, Amoako‐Gyampah K, Meredith JR. An evaluation of maintenance policies for flexible manufacturing systems. INTERNATIONAL JOURNAL OF OPERATIONS & PRODUCTION MANAGEMENT 2000. [DOI: 10.1108/01443570010319156] [Citation(s) in RCA: 26] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
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Park CG. Likelihood ratio test for homogeneity of steady-state availabilities against order restrictions. J Stat Plan Inference 2000. [DOI: 10.1016/s0378-3758(99)00146-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/16/2022]
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Estimation and testing of availability of a parallel system with exponential failure and repair times. J Stat Plan Inference 1999. [DOI: 10.1016/s0378-3758(98)00184-0] [Citation(s) in RCA: 11] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2022]
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Koulamas CP. Single-Stage and Serial Production Line Systems with Unreliable Machines and General Probability Distributions. DECISION SCIENCES 1993. [DOI: 10.1111/j.1540-5915.1993.tb00478.x] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
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