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:: Volume 10, Issue 2 (7-2021) ::
ieijqp 2021, 10(2): 28-39 Back to browse issues page
Building a Comprehensive Conceptual Framework for Power Systems Resilience Metrics
Habibollah Raoufi1 , Vahid Vahidinasab * 1, Kamyar Mehran2
1- Faculty of Electrical Engineering, Shahid Beheshti University, Tehran, Iran
2- School of Electronic Engineering and Computer Science, Queen Mary University of London
Abstract:   (925 Views)
Recently, the frequency and severity of natural and man-made disasters (extreme events), which have a high-impact low-frequency (HILF) property, are increased. These disasters can lead to extensive outages, damages, and costs in electric power systems. A power system must be built with “resilience” against disasters, which means its ability to withstand disasters efficiently while ensuring the least possible interruption in the supply of electricity, sustaining critical social services, and enabling a quick recovery and restoration to the normal operation state. Quantifying the power system resilience is a complicated and controversial problem. However, this is necessary for the evaluation and comparison of different resilience enhancement strategies. The resilience metrics are mathematical tools to measure the resilience level of a power system, which are normally employed for resilience cost-benefit in the planning and operation domains. Numerous resilience metrics have been presented in the power system literature. However, there is a lack of a comprehensive conceptual framework regarding the different types of resilience metrics in electric power systems, and existing frameworks have essential shortcomings. In this paper, after introducing and criticizing the existing frameworks, a conceptual framework is suggested to classify different types of resilience metrics in the power system literature. In this conceptual framework, power system resilience metrics are divided into “non-performance-based” and “performance-based” groups. The “performance-based” resilience metrics are also divided into “performance” and “consequence (outcome)” groups. The “performance” resilience metrics consist of five groups including “power”, “duration”, “frequency”, “probability” and “curve”. The “consequence (outcome)” resilience metrics consist of four groups including “economic”, “social”, “geographic” and “safety and health”. In addition, both of the “performance” and “consequence (outcome)” groups have a distinct group naming “general”. In order to verify and validate the comprehensiveness and inclusivity of the proposed conceptual framework, two actions are accomplished. Firstly, the existing power system resilience metrics are allocated to the framework’s groups. Secondly, the proposed conceptual framework is compared with the existing frameworks. These actions show that the proposed conceptual framework can cover and classify different types of power system resilience metrics in the literature, is more comprehensive comparing the existing frameworks, and lacks the essential shortcoming of those frameworks. Thus, the proposed conceptual framework is comprehensive and useful. The proposed conceptual framework can be used by academic and industrial researchers. Academic researchers can concentrate on groups that need further research to propose new resilience metrics, whereas industrial researchers can choose the appropriate resilience metric according to their needs.        
Keywords: Resilience, Resiliency, Metric, Index, Measurement, Quantification, Disaster, Extreme event, Power system, Conceptual framework
Full-Text [PDF 924 kb]   (149 Downloads)    
Type of Study: Research |
Received: 2020/09/5 | Accepted: 2021/04/25 | Published: 2021/07/1
References
1. Abbey, C., Cornforth, D., Hatziargyriou, N., Hirose, K., Kwasinski, A., Kyriakides, E., . . . Suryanarayanan, S. (2014). Powering through the storm: Microgrids operation for more efficient disaster recovery. IEEE Power and Energy Magazine, 12(3), 67-76. [DOI:10.1109/MPE.2014.2301514]
2. Afgan, N. (2010). Sustainable resilience of energy systems. USA: Nova Science Publishers.
3. Amirioun, M., Aminifar, F., Lesani, H., & Shahidehpour, M. (2019). Metrics and quantitative framework for assessing microgrid resilience against windstorms. International Journal of Electrical Power & Energy Systems, 104, 716-723. [DOI:10.1016/j.ijepes.2018.07.025]
4. Amirioun, M. H., Aminifar, F., & Lesani, H. (2018a). Resilience-oriented proactive management of microgrids against windstorms. IEEE Transactions on Power Systems, 33(4), 4275 - 4284. [DOI:10.1109/TPWRS.2017.2765600]
5. Amirioun, M. H., Aminifar, F., & Lesani, H. (2018b). Towards proactive scheduling of microgrids against extreme floods. IEEE Transactions on Smart Grid, 9(4), 3900 - 3902. [DOI:10.1109/TSG.2017.2762906]
6. Ansari, B., & Mohagheghi, S. (2015). Optimal energy dispatch of the power distribution network during the course of a progressing wildfire. International Transactions on Electrical Energy Systems, 25(12), 3422-3438. [DOI:10.1002/etep.2043]
7. Arab, A., Khodaei, A., Han, Z., & Khator, S. K. (2015). Proactive recovery of electric power assets for resiliency enhancement. IEEE Access, 3, 99-109. [DOI:10.1109/ACCESS.2015.2404215]
8. Arab, A., Khodaei, A., Khator, S. K., Ding, K., Emesih, V. A., & Han, Z. (2015). Stochastic pre-hurricane restoration planning for electric power systems infrastructure. IEEE Transactions on Smart Grid, 6(2), 1046-1054. [DOI:10.1109/TSG.2015.2388736]
9. Arghandeh, R., Brown, M., Del Rosso, A., Ghatikar, G., Stewart, E., Vojdani, A., & von Meier, A. (2014). The local team: Leveraging distributed resources to improve resilience. IEEE Power and Energy Magazine, 12(5), 76-83. [DOI:10.1109/MPE.2014.2331902]
10. Arghandeh, R., von Meier, A., Mehrmanesh, L., & Mili, L. (2016). On the definition of cyber-physical resilience in power systems. Renewable and Sustainable Energy Reviews, 58, 1060-1069. [DOI:10.1016/j.rser.2015.12.193]
11. Attoh-Okine, N. O., Cooper, A. T., & Mensah, S. A. (2009). Formulation of resilience index of urban infrastructure using belief functions. IEEE Systems Journal, 3(2), 147-153. [DOI:10.1109/JSYST.2009.2019148]
12. Balasubramaniam, K., Saraf, P., Hadidi, R., & Makram, E. B. (2016). Energy management system for enhanced resiliency of microgrids during islanded operation. Electric Power Systems Research, 137, 133-141. [DOI:10.1016/j.epsr.2016.04.006]
13. Bhusal, N., Abdelmalak, M., Kamruzzaman, M., & Benidris, M. (2020). Power system resilience: Current practices, challenges, and future directions. IEEE Access, 8, 18064-18086. [DOI:10.1109/ACCESS.2020.2968586]
14. Bie, Z., Lin, Y., Li, G., & Li, F. (2017). Battling the extreme: A study on the power system resilience. Proceedings of the IEEE, 105(7), 1253 - 1266. [DOI:10.1109/JPROC.2017.2679040]
15. Carlson, L., Bassett, G., Buehring, W., Collins, M., Folga, S., Haffenden, B., . . . Whitfield, R. (2012). Resilience: Theory and application. Retrieved from USA: [DOI:10.2172/1044521]
16. Chaudry, M., Ekins, P., Ramachandran, K., Shakoor, A., Skea, J., Strbac, G., . . . Whitaker, J. (2011). Building a resilient UK energy system. Retrieved from UK:
17. 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]
18. Chen, C., Wang, J., & Ton, D. (2017). Modernizing distribution system restoration to achieve grid resiliency against extreme weather events: An integrated solution. Proceedings of the IEEE, 105(7), 1267-1288. [DOI:10.1109/JPROC.2017.2684780]
19. Ciapessoni, E., Cirio, D., Kjølle, G., Massucco, S., Pitto, A., & Sforna, M. (2016). Probabilistic risk-based security assessment of power systems considering incumbent threats and uncertainties. IEEE Transactions on Smart Grid, 7(6), 2890-2903. [DOI:10.1109/TSG.2016.2519239]
20. Dehghani, N. L., Darestani, Y. M., & Shafieezadeh, A. (2020). Optimal life-cycle resilience enhancement of aging power distribution systems: A MINLP-based preventive maintenance planning. IEEE Access, 8, 22324-22334. [DOI:10.1109/ACCESS.2020.2969997]
21. Ding, T., Lin, Y., Li, G., & Bie, Z. (2017). A new model for resilient distribution systems by microgrids formation. IEEE Transactions on Power Systems, 32(5), 4145 - 4147. [DOI:10.1109/TPWRS.2017.2650779]
22. Espinoza, S., Panteli, M., Mancarella, P., & Rudnick, H. (2016). Multi-phase assessment and adaptation of power systems resilience to natural hazards. Electric Power Systems Research, 136, 352-361. [DOI:10.1016/j.epsr.2016.03.019]
23. Farzin, H., Fotuhi-Firuzabad, M., & Moeini-Aghtaie, M. (2016). Enhancing power system resilience through hierarchical outage management in multi-microgrids. IEEE Transactions on Smart Grid, 7(6), 2869-2879. [DOI:10.1109/TSG.2016.2558628]
24. Fisher, R. E., Bassett, G. W., Buehring, W. A., Collins, M. J., Dickinson, D. C., Eaton, L. K., . . . Peerenboom, J. P. (2010). Constructing a resilience index for the enhanced critical infrastructure protection program. Retrieved from USA: [DOI:10.2172/991101]
25. Fu, G., Wilkinson, S., Dawson, R. J., Fowler, H. J., Kilsby, C., Panteli, M., & Mancarella, P. (2018). Integrated approach to assess the resilience of future electricity infrastructure networks to climate hazards. IEEE Systems Journal, 12(4), 3169 - 3180. [DOI:10.1109/JSYST.2017.2700791]
26. Gao, H., Chen, Y., Mei, S., Huang, S., & Xu, Y. (2017). Resilience-oriented pre-hurricane resource allocation in distribution systems considering electric buses. Proceedings of the IEEE, 105(7), 1214 - 1233. [DOI:10.1109/JPROC.2017.2666548]
27. Gao, H., Chen, Y., Xu, Y., & Liu, C.-C. (2016). Resilience-oriented critical load restoration using microgrids in distribution systems. IEEE Transactions on Smart Grid, 7(6), 2837-2848. [DOI:10.1109/TSG.2016.2550625]
28. Gholami, A., Shekari, T., Aminifar, F., & Shahidehpour, M. (2016). Microgrid scheduling with uncertainty: The quest for resilience. IEEE Transactions on Smart Grid, 7(6), 2849-2858. [DOI:10.1109/TSG.2016.2598802]
29. Hosseini, S., Barker, K., & Ramirez-Marquez, J. E. (2016). A review of definitions and measures of system resilience. Reliability Engineering & System Safety, 145, 47-61. [DOI:10.1016/j.ress.2015.08.006]
30. Huang, G., Wang, J., Chen, C., Qi, J., & Guo, C. (2017). Integration of preventive and emergency responses for power grid resilience enhancement. IEEE Transactions on Power Systems, 32(6), 4451 - 4463. [DOI:10.1109/TPWRS.2017.2685640]
31. Hussain, A., Bui, V.-H., & Kim, H.-M. (2017). Optimal operation of hybrid microgrids for enhancing resiliency considering feasible islanding and survivability. IET Renewable Power Generation, 11(6), 846-857. [DOI:10.1049/iet-rpg.2016.0820]
32. IEC. (2014). Microgrids for disaster preparedness and recovery-With electricity continuity plans and systems. Retrieved from Switzerland:
33. Ji, C., Wei, Y., & Poor, H. V. (2017). Resilience of energy infrastructure and services: Modeling, data analytics, and metrics. Proceedings of the IEEE, 105(7), 1354-1366. [DOI:10.1109/JPROC.2017.2698262]
34. Johnson, B., Chalishazar, V., Cotilla-Sanchez, E., & Brekken, T. K. (2020). A monte carlo methodology for earthquake impact analysis on the electrical grid. Electric Power Systems Research, 184, 106332. [DOI:10.1016/j.epsr.2020.106332]
35. Keogh, M., & Cody, C. (2013). Resilience in regulated utilities. Retrieved from USA:
36. Khodaei, A. (2014a). Microgrid optimal scheduling with multi-period islanding constraints. IEEE Transactions on Power Systems, 29(3), 1383-1392. [DOI:10.1109/TPWRS.2013.2290006]
37. Khodaei, A. (2014b). Resiliency-oriented microgrid optimal scheduling. IEEE Transactions on Smart Grid, 5(4), 1584-1591. [DOI:10.1109/TSG.2014.2311465]
38. Khodaei, A. (2015). Provisional microgrids. IEEE Transactions on Smart Grid, 6(3), 1107-1115. [DOI:10.1109/TSG.2014.2358885]
39. Krishnamurthy, V., & Kwasinski, A. (2016). Effects of power electronics, energy storage, power distribution architecture, and lifeline dependencies on microgrid resiliency during extreme events. IEEE Journal of Emerging and Selected Topics in Power Electronics, 4(4), 1310-1323. [DOI:10.1109/JESTPE.2016.2598648]
40. Kwasinski, A. (2010). Technology planning for electric power supply in critical events considering a bulk grid, backup power plants, and micro-grids. IEEE Systems Journal, 4(2), 167-178. [DOI:10.1109/JSYST.2010.2047034]
41. Landegren, F. E., Johansson, J., & Samuelsson, O. (2016). A method for assessing margin and sensitivity of electricity networks with respect to repair system resources. IEEE Transactions on Smart Grid, 7(6), 2880-2889. [DOI:10.1109/TSG.2016.2582080]
42. Lei, S., Wang, J., Chen, C., & Hou, Y. (2018). Mobile emergency generator pre-positioning and real-time allocation for resilient response to natural disasters. IEEE Transactions on Smart Grid, 9(3), 2030 - 2041.
43. Li, Y., Xie, K., Wang, L., & Xiang, Y. (2019). Exploiting network topology optimization and demand side management to improve bulk power system resilience under windstorms. Electric Power Systems Research, 171, 127-140. [DOI:10.1016/j.epsr.2019.02.014]
44. Li, Z., Shahidehpour, M., Aminifar, F., Alabdulwahab, A., & Al-Turki, Y. (2017). Networked microgrids for enhancing the power system resilience. Proceedings of the IEEE, 105(7), 1289 - 1310. [DOI:10.1109/JPROC.2017.2685558]
45. Liu, J., Qin, C., & Yu, Y. (2019). Enhancing distribution system resilience with proactive islanding and RCS-based fast fault isolation and service restoration. IEEE Transactions on Smart Grid, 11(3), 2381-2395. [DOI:10.1109/TSG.2019.2953716]
46. Liu, X., Shahidehpour, M., Li, Z., Liu, X., Cao, Y., & Bie, Z. (2017). Microgrids for enhancing the power grid resilience in extreme conditions. IEEE Transactions on Smart Grid, 8(2), 589-597.
47. Ma, S., Chen, B., & Wang, Z. (2018). Resilience enhancement strategy for distribution systems under extreme weather events. IEEE Transactions on Smart Grid, 9(2), 1442 - 1451. [DOI:10.1109/TSG.2016.2591885]
48. Manshadi, S. D., & Khodayar, M. E. (2015). Resilient operation of multiple energy carrier microgrids. IEEE Transactions on Smart Grid, 6(5), 2283-2292. [DOI:10.1109/TSG.2015.2397318]
49. MEA. (2014). Maryland resiliency through microgrids: Task force report. Retrieved from USA:
50. NERC. (2010). High-impact, low-frequency event risk to the north american bulk power system. Retrieved from USA:
51. Nezamoddini, N., Mousavian, S., & Erol-Kantarci, M. (2017). A risk optimization model for enhanced power grid resilience against physical attacks. Electric Power Systems Research, 143, 329-338. [DOI:10.1016/j.epsr.2016.08.046]
52. Panteli, M., & Mancarella, P. (2015a). The grid: Stronger, bigger, smarter?: Presenting a conceptual framework of power system resilience. IEEE Power and Energy Magazine, 13(3), 58-66. [DOI:10.1109/MPE.2015.2397334]
53. Panteli, M., & Mancarella, P. (2015b). Influence of extreme weather and climate change on the resilience of power systems: Impacts and possible mitigation strategies. Electric Power Systems Research, 127, 259-270. [DOI:10.1016/j.epsr.2015.06.012]
54. Panteli, M., & Mancarella, P. (2017). Modeling and evaluating the resilience of critical electrical power infrastructure to extreme weather events. IEEE Systems Journal, 11(3), 1733 - 1742. [DOI:10.1109/JSYST.2015.2389272]
55. Panteli, M., Mancarella, P., Trakas, D., Kyriakides, E., & Hatziargyriou, N. (2017). Metrics and quantification of operational and infrastructure resilience in power systems. IEEE Transactions on Power Systems, 32(6), 4732 - 4742. [DOI:10.1109/TPWRS.2017.2664141]
56. Panteli, M., Pickering, C., Wilkinson, S., Dawson, R., & Mancarella, P. (2017). Power system resilience to extreme weather: Fragility modeling, probabilistic impact assessment, and adaptation measures. IEEE Transactions on Power Systems, 32(5), 3747-3757. [DOI:10.1109/TPWRS.2016.2641463]
57. Panteli, M., Trakas, D. N., Mancarella, P., & Hatziargyriou, N. D. (2016). Boosting the power grid resilience to extreme weather events using defensive islanding. IEEE Transactions on Smart Grid, 7(6), 2913-2922. [DOI:10.1109/TSG.2016.2535228]
58. Panteli, M., Trakas, D. N., Mancarella, P., & Hatziargyriou, N. D. (2017). Power systems resilience assessment: Hardening and smart operational enhancement strategies. Proceedings of the IEEE, 105(7), 1202 - 1213. [DOI:10.1109/JPROC.2017.2691357]
59. Petit, F. D., Bassett, G. W., Black, R., Buehring, W. A., Collins, M. J., Dickinson, D. C., . . . Peerenboom, J. P. (2013). Resilience measurement index: An indicator of critical infrastructure resilience. Retrieved from USA: [DOI:10.2172/1087819]
60. Reed, D. A., Kapur, K. C., & Christie, R. D. (2009). Methodology for assessing the resilience of networked infrastructure. IEEE Systems Journal, 3(2), 174-180. [DOI:10.1109/JSYST.2009.2017396]
61. Shao, C., Shahidehpour, M., Wang, X., Wang, X., & Wang, B. (2017). Integrated planning of electricity and natural gas transportation systems for enhancing the power grid resilience. IEEE Transactions on Power Systems, 32(6), 4418 - 4429. [DOI:10.1109/TPWRS.2017.2672728]
62. Shinozuka, M., & Chang, S. E. (2004). Evaluating the disaster resilience of power networks and grids. In Y. Okuyama & S. E. Chang (Eds.), Modeling spatial and economic impacts of disasters (pp. 289-310). Germany: Springer. [DOI:10.1007/978-3-540-24787-6_14]
63. The_National_Academies. (2012a). Disaster resilience: A national imperative. USA: The National Academies Press.
64. The_National_Academies. (2012b). Terrorism and the electric power delivery system. USA: The National Academies Press.
65. Ton, D. T., & Wang, W.-T. P. (2015). A more resilient grid: The US Department of Energy joins with stakeholders in an R&D plan. IEEE Power and Energy Magazine, 13(3), 26-34. [DOI:10.1109/MPE.2015.2397337]
66. Trakas, D. N., Panteli, M., Hatziargyriou, N. D., & Mancarella, P. (2019). Spatial risk analysis of power systems resilience during extreme events. Risk Analysis, 39(1), 195-211. [DOI:10.1111/risa.13220]
67. Wang, C., Hou, Y., Qiu, F., Lei, S., & Liu, K. (2017). Resilience enhancement with sequentially proactive operation strategies. IEEE Transactions on Power Systems, 32(4), 2847-2857. [DOI:10.1109/TPWRS.2016.2622858]
68. Wang, C., Wei, W., Wang, J., Liu, F., Qiu, F., Correa-Posada, C. M., & Mei, S. (2017). Robust defense strategy for gas-electric systems against malicious attacks. IEEE Transactions on Power Systems, 32(4), 2953-2965. [DOI:10.1109/TPWRS.2016.2628877]
69. Wang, Y., Chen, C., Wang, J., & Baldick, R. (2016). Research on resilience of power systems under natural disasters-A review. IEEE Transactions on Power Systems, 31(2), 1604-1613. [DOI:10.1109/TPWRS.2015.2429656]
70. Watson, J.-P., Guttromson, R., Silva-Monroy, C., Jeffers, R., Jones, K., Ellison, J., . . . Walker, L. T. (2014). Conceptual framework for developing resilience metrics for the electricity, oil, and gas sectors in the United States. Retrieved from USA: [DOI:10.2172/1177743]
71. Willis, H. H., & Loa, K. (2015). Measuring the resilience of energy distribution systems. Retrieved from USA:
72. Xiang, Y., Wang, L., & Liu, N. (2018). A Robustness-oriented power grid operation strategy considering attacks. IEEE Transactions on Smart Grid, 9(5), 4248 - 4261. [DOI:10.1109/TSG.2017.2653219]
73. Xu, X., Mitra, J., Cai, N., & Mou, L. (2014). Planning of reliable microgrids in the presence of random and catastrophic events. International Transactions on Electrical Energy Systems, 24(8), 1151-1167. [DOI:10.1002/etep.1768]
74. Yang, L.-J., Zhao, Y., Wang, C., Gao, P., & Hao, J.-H. (2019). Resilience-oriented hierarchical service restoration in distribution system considering microgrids. IEEE Access, 7, 152729-152743. [DOI:10.1109/ACCESS.2019.2948372]
75. Yuan, C., Illindala, M. S., & Khalsa, A. S. (2017). Modified Viterbi algorithm based distribution system restoration strategy for grid resiliency. IEEE Transactions on Power Delivery, 32(1), 310-319. [DOI:10.1109/TPWRD.2016.2613935]
76. Yuan, W., Wang, J., Qiu, F., Chen, C., Kang, C., & Zeng, B. (2016). Robust optimization-based resilient distribution network planning against natural disasters. IEEE Transactions on Smart Grid, 7(6), 2817-2826. [DOI:10.1109/TSG.2015.2513048]
77. Zhu, Y., Yan, J., Tang, Y., Sun, Y. L., & He, H. (2014). Resilience analysis of power grids under the sequential attack. IEEE Transactions on Information Forensics and Security, 9(12), 2340-2354. [DOI:10.1109/TIFS.2014.2363786]
78. امینی‌فر، ف؛ فرهومندی، م، (1397). مفاهیم و مبانی ارزیابی تاب‌آوری در شبکه‌های برق، مجله انجمن مهندسي برق و الكترونيك ايران، 15 (3)، صص 91-83.
79. صابری، ر؛ فلقی، ح؛ اسماعیلی، م، (a1399). شاخصی جدید برای ارزیابی کمی تاب‌آوری شبکه توزیع در حضور منابع تولید پراکنده، نشریه مهندسی و مدیریت انرژی، 10 (3)، صص 43-30.
80. صابری، ر؛ فلقی، ح؛ اسماعیلی، م، (b1399). طراحی منابع تولید پراکنده در شبکه‌های توزیع با هدف بهبود تاب‌آوری، نشریه كيفيت و بهره‌وري صنعت برق ايران، 9 (4)، صص 49-35.
81. صادقی خمامی، م؛ سپاسیان، م، (1398). برنامه‌ریزی بازیابی پیش از وقوع تندباد شبکه‌های توزیع فشار متوسط با هدف بهبود مدیریت بحران پیش‌اقدامانه، نشریه مدیریت بحران، 15، صص 89-77.
82. علیزاده، م؛ غفارپور، ر؛ رنجبر، ع، (1399). بهینه‌سازی سه‌سطحی مقاوم مشارکت واحدها مقید به امنیت با هدف تاب‌آوری در سیستم‌های قدرت با نفوذ بالای منابع اتکاناپذیر، مجله انجمن مهندسي برق و الكترونيك ايران، 17 (2)، صص 121-113.
83. منعمی، م؛ حسن‌پور دربان، س، (1396). مدل تاب‌آور برنامه‌ریزی ورود و خروج واحدهای نیروگاهی با هدف کنترل سریع فرکانسی شبکه در حضور واحدهای مجهز به چرخ لنگر، مجله عصر برق، 4 (6)، صص 30-16.
84. منعمی، م؛ حسن‌پور دربان، س، (1397). مسأله در مدار قرار گرفتن واحدهای نیروگاهی با هدف افزایش تاب‌آوری شبکه، مجله مهندسی برق دانشگاه تبریز، 48 (4)، صص 1794-1785.


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Raoufi H, Vahidinasab V, Mehran K. Building a Comprehensive Conceptual Framework for Power Systems Resilience Metrics. ieijqp. 2021; 10 (2) :28-39
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نشریه علمی- پژوهشی کیفیت و بهره وری صنعت برق ایران Iranian Electric Industry Journal of Quality and Productivity
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