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Original Articles

Post-disruption performance recovery to enhance resilience of interconnected network systems

& ORCID Icon
Pages 107-123 | Received 24 Jun 2019, Accepted 23 Dec 2019, Published online: 16 Jan 2020

References

  • Arif, A., Wang, Z., Wang, J., & Chen, C. (2018). Power distribution system outage management with co-optimization of repairs, reconfiguration, and DG dispatch. IEEE Transactions on Smart Grid, 9(5), 4109–4118. doi:10.1109/Tsg.2017.2650917
  • Bai, G., Wang, P., & Hu, C. (2015). A self-cognizant dynamic system approach for prognostics and health management. Journal of Power Sources, 278, 163–174. doi:10.1016/j.jpowsour.2014.12.050
  • Baran, M. E., & Wu, F. F. (1989). Network reconfiguration in distribution-systems for loss reduction and load balancing. IEEE Transactions on Power Delivery, 4(2), 1401–1407. doi:10.1109/61.25627
  • Carvalho, P. M. S., Ferreira, L. A. F. M., & da Silva, A. J. C. (2005). A decomposition approach to optimal remote controlled switch allocation in distribution systems. IEEE Transactions on Power Delivery, 20(2), 1031–1036. doi:10.1109/Tpwrd.2004.838470
  • Chen, C., Wang, J., Qiu, F., & Zhao, D. (2016). Resilient distribution system by microgrids formation after natural disasters. IEEE Transactions on Smart Grid, 7(2), 958–966. doi:10.1109/Tsg.2015.2429653
  • Chen, X., Xi, Z., & Jing, P. (2017). A unified framework for evaluating supply chain reliability and resilience. IEEE Transactions on Reliability, 66(4), 1144–1156. doi:10.1109/Tr.2017.2737822
  • Compare, M., & Zio, E. (2014). Predictive maintenance by risk sensitive particle filtering. IEEE Transactions on Reliability, 63(1), 134–143. doi:10.1109/Tr.2014.2299651
  • Ellingwood, B. R., Cutler, H., Gardoni, P., Peacock, W. G., van de Lindt, J. W., & Wang, N. (2016). The centerville virtual community: A fully integrated decision model of interacting physical and social infrastructure systems. Sustainable and Resilient Infrastructure, 1(3–4), 95–107. doi:10.1080/23789689.2016.1255000
  • Gardoni, P., & Murphy, C. (2018). Society-based design: Promoting societal well-being by designing sustainable and resilient infrastructure. Sustainable and Resilient Infrastructure, 1–16. doi:10.1080/23789689.2018.1448667
  • Guidotti, R., Chmielewski, H., Unnikrishnan, V., Gardoni, P., McAllister, T., & van de Lindt, J. (2016). Modeling the resilience of critical infrastructure: The role of network dependencies. Sustainable and Resilient Infrastructure, 1(3–4), 153–168. doi:10.1080/23789689.2016.1254999
  • Hamdan, B., & Diabat, A. (2019). A two-stage multi-echelon stochastic blood supply chain problem. Computers & Operations Research, 101, 130–143. doi:10.1016/j.cor.2018.09.001
  • IEEE 37 Node Test Feeder. (2016). Retrieved from http://sites.ieee.org/pes-testfeeders/files/2017/08/feeder37.zip
  • Ju, C., Yao, S., & Wang, P. (2017). Resilient post-disaster system reconfiguration for multiple energy service restoration. 2017 IEEE Conference on Energy Internet and Energy System Integration (EI2). Beijing, China. doi:10.1109/EI2.2017.8245559
  • Kim, J., & Dvorkin, Y. (2018). Enhancing distribution system resilience with mobile energy storage and microgrids. IEEE Transactions on Smart Grid, 10(5), 4996–5006. doi:10.1109/Tsg.2018.2872521
  • Lavorato, M., Franco, J. F., Rider, M. J., & Romero, R. (2012). Imposing radiality constraints in distribution system optimization problems. IEEE Transactions on Power Systems, 27(1), 172–180. doi:10.1109/Tpwrs.2011.2161349
  • Lei, S., Chen, C., Li, Y., & Hou, Y. (2018). Resilient disaster recovery logistics of distribution systems: Co-optimize service restoration with repair crew and mobile power source dispatch. arXiv Preprint arXiv:1806.07581.
  • Lei, S., Chen, C., Zhou, H., & Hou, Y. (2018). Routing and scheduling of mobile power sources for distribution system resilience enhancement. IEEE Transactions on Smart Grid, 10(5), 5650–5662. doi:10.1109/Tsg.2018.2889347
  • Li, Z., & Shahidehpour, M. (2017). Role of microgrids in enhancing power system resilience. 2017 IEEE Power & Energy Society General Meeting, Chicago, IL, 2017. doi:10.1109/PESGM.2017.8274054.
  • Maya Duque, P. A., Dolinskaya, I. S., & Sörensen, K. (2016). Network repair crew scheduling and routing for emergency relief distribution problem. European Journal of Operational Research, 248(1), 272–285. Retrieved from http://www.sciencedirect.com/science/article/pii/S0377221715005408
  • MEng, S. H., MEng, D. C., Edward Tufton, M., & Inglis, S. (2012). Engineering resilient infrastructure. Proceedings of the Institution of Civil Engineers, 165(6), 5.
  • Moradi, A., & Fotuhi-Firuzabad, M. (2008). Optimal switch placement in distribution systems using trinary particle swarm optimization algorithm. IEEE Transactions on Power Delivery, 23(1), 271–279. doi:10.1109/Tpwrd.2007.905428
  • Murty, V. V. S. N., & Kumar, A. (2015). Optimal placement of DG in radial distribution systems based on new voltage stability index under load growth. International Journal of Electrical Power & Energy Systems, 69, 246–256. doi:10.1016/j.ijepes.2014.12.080
  • Nagarajan, H., Lu, M., Yamangil, E., & Bent, R. (2016). Tightening Mccormick relaxations for nonlinear programs via dynamic multivariate partitioning. Principles and Practice of Constraint Programming, Cp 2016, 9892, 369–387. doi:10.1007/978-3-319-44953-1_24.
  • Patterson, M. D., & Wears, R. L. (2015). Resilience and precarious success. Reliability Engineering & System Safety, 141, 45–53. doi:10.1016/j.ress.2015.03.014
  • Peng, Q., & Low, S. H. (2018). Distributed optimal power flow algorithm for radial networks, I: Balanced single phase case. IEEE Transactions on Smart Grid, 9(1), 111–121. doi:10.1109/Tsg.2016.2546305
  • Rey Horn, J., Nafpliotis, N., & Goldberg, D. E. (1994). A niched Pareto genetic algorithm for multiobjective optimization. Proceedings of the first IEEE conference on evolutionary computation, IEEE world congress on computational intelligence, Proceedings of the First IEEE Conference on Evolutionary Computation, IEEE World Congress on Computational Intelligence, Orlando, FL, 1994. doi:10.1109/ICEC.1994.350037.
  • Rosenheim, N., Guidotti, R., Gardoni, P., & Peacock, W. G. (2019). Integration of detailed household and housing unit characteristic data with critical infrastructure for post-hazard resilience modeling. Sustainable and Resilient Infrastructure, 1–17. doi:10.1080/23789689.2019.1681821
  • Salem, S., Campidelli, M., El-Dakhakhni, W. W., & Tait, M. J. (2018). Resilience-based design of urban centres: Application to blast risk assessment. Sustainable and Resilient Infrastructure, 3(2), 68–85. doi:10.1080/23789689.2017.1345256
  • Sharma, N., Tabandeh, A., & Gardoni, P. (2018). Resilience analysis: A mathematical formulation to model resilience of engineering systems. Sustainable and Resilient Infrastructure, 3(2), 49–67. doi:10.1080/23789689.2017.1345257
  • Shin, H., & Baldick, R. (2017). Plug-in electric vehicle to home (V2H) operation under a grid outage. IEEE Transactions on Smart Grid, 8(4), 2032–2041. doi:10.1109/Tsg.2016.2603502
  • Srinivas, N., & Deb, K. (1994). Muiltiobjective optimization using nondominated sorting in genetic algorithms. Evolutionary Computation, 2(3), 221–248.
  • Wang, P., Hu, C., & Youn, B. D. (2011). A generalized complementary intersection method (GCIM) for system reliability analysis. Journal of Mechanical Design, 133(7), 071003. doi:10.1115/1.4004198
  • Wang, P., Youn, B. D., & Hu, C. (2010). A probabilistic detectability-based sensor network design method for system health monitoring and prognostics. Journal of Intelligent Material Systems and Structures, 26(9), 1079–1090. doi:10.1177/1045389X14541496
  • Wang, Z., & Wang, P. (2014). A maximum confidence enhancement based sequential sampling scheme for simulation-based design. Journal of Mechanical Design, 136(2), 021006.
  • Wu, J., & Wang, P. (2019). A comparison of control strategies for disruption management in engineering design for resilience. Asce-Asme Journal of Risk and Uncertainty in Engineering Systems Part B-Mechanical Engineering, 5(2). doi:10.1115/1.4042829
  • Yodo, N., & Wang, P. (2016a). Engineering resilience quantification and system design implications: A literature survey. Journal of Mechanical Design, 138(11). doi:10.1115/1.4034223
  • Yodo, N., & Wang, P. (2016b). Resilience allocation for early stage design of complex engineered systems. Journal of Mechanical Design, 138(9), 091402. doi:10.1115/1.4033990
  • Yodo, N., & Wang, P. (2016c). Resilience modeling and quantification for engineered systems using Bayesian networks. Journal of Mechanical Design, 138(3), 031404-031404-031412. doi:10.1115/1.4032399
  • Yodo, N., Wang, P., & Rafi, M. (2018). Enabling resilience of complex engineered systems using control theory. IEEE Transactions on Reliability, 67(1), 53–65. doi:10.1109/Tr.2017.2746754
  • Youn, B. D., & Wang, P. (2008). Bayesian reliability-based design optimization using eigenvector dimension reduction (EDR) method. Structural and Multidisciplinary Optimization, 36(2), 107–123.
  • Zio, E., & Sansavini, G. (2011). Modeling interdependent network systems for identifying cascade-safe operating margins. IEEE Transactions on Reliability, 60(1), 94–101. doi:10.1109/Tr.2010.2104211

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