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Interdependent Critical Infrastructure Model (ICIM): An agent-based model of power and water infrastructure

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  • Thompson, James R.
  • Frezza, Damon
  • Necioglu, Burhan
  • Cohen, Michael L.
  • Hoffman, Kenneth
  • Rosfjord, Kristine

Abstract

The comfort, mobility, and economic well-being of a population depends on reliable and affordable electric power services, which in turn requires a sustainable water supply. It is therefore increasingly important to analyze the sustainability and resilience of mid- and long-term electric utility and water system capacity expansion plans. Due to the inherent interdependency between power and water critical infrastructure, these expansion plans should be analyzed with respect to potential challenges posed by climate change and other risks. Decision-makers therefore require tools that facilitate an integrated analysis that captures the interdependency of power and water to better inform future expansion plans. Here we develop an agent-based model of a typical regional power system that incorporates the features of specific plant types and their cooling systems that are dependent on adequate water supplies at appropriate temperatures to support full power operation. The effects of capacity expansion plans, power demand growth, climate change, and extreme events are analyzed through different scenarios designed to illustrate the utility of such a model and show where it can aid in mid- and long-term planning.

Suggested Citation

  • Thompson, James R. & Frezza, Damon & Necioglu, Burhan & Cohen, Michael L. & Hoffman, Kenneth & Rosfjord, Kristine, 2019. "Interdependent Critical Infrastructure Model (ICIM): An agent-based model of power and water infrastructure," International Journal of Critical Infrastructure Protection, Elsevier, vol. 24(C), pages 144-165.
    • Handle: RePEc:eee:ijocip:v:24:y:2019:i:c:p:144-165
    DOI: 10.1016/j.ijcip.2018.12.002
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    1. Junjie Sun & Leigh Tesfatsion, 2007. "Dynamic Testing of Wholesale Power Market Designs: An Open-Source Agent-Based Framework," Computational Economics, Springer;Society for Computational Economics, vol. 30(3), pages 291-327, October.
    2. Varun Rai & Adam Douglas Henry, 2016. "Agent-based modelling of consumer energy choices," Nature Climate Change, Nature, vol. 6(6), pages 556-562, June.
    3. Joshua M. Epstein & Robert L. Axtell, 1996. "Growing Artificial Societies: Social Science from the Bottom Up," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262550253, December.
    4. Olsina, Fernando & Garces, Francisco & Haubrich, H.-J., 2006. "Modeling long-term dynamics of electricity markets," Energy Policy, Elsevier, vol. 34(12), pages 1411-1433, August.
    5. Steven A. Gabriel & Andy S. Kydes & Peter Whitman, 2001. "The National Energy Modeling System: A Large-Scale Energy-Economic Equilibrium Model," Operations Research, INFORMS, vol. 49(1), pages 14-25, February.
    6. Ouyang, Min, 2014. "Review on modeling and simulation of interdependent critical infrastructure systems," Reliability Engineering and System Safety, Elsevier, vol. 121(C), pages 43-60.
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    3. Zhou, Shenghua & Yang, Yifan & Ng, S. Thomas & Xu, J. Frank & Li, Dezhi, 2020. "Integrating data-driven and physics-based approaches to characterize failures of interdependent infrastructures," International Journal of Critical Infrastructure Protection, Elsevier, vol. 31(C).
    4. González, Santiago G. & Dormido Canto, S. & Sánchez Moreno, José, 2020. "Obtaining high preventive and resilience capacities in critical infrastructure by industrial automation cells," International Journal of Critical Infrastructure Protection, Elsevier, vol. 29(C).
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    6. Linas Martišauskas & Juozas Augutis & Ričardas Krikštolaitis & Rolandas Urbonas & Inga Šarūnienė & Vytis Kopustinskas, 2022. "A Framework to Assess the Resilience of Energy Systems Based on Quantitative Indicators," Energies, MDPI, vol. 15(11), pages 1-25, May.
    7. Reilly, Allison C. & Baroud, Hiba & Flage, Roger & Gerst, Michael D., 2021. "Sources of uncertainty in interdependent infrastructure and their implications," Reliability Engineering and System Safety, Elsevier, vol. 213(C).
    8. Lo, Huai-Wei & Liou, James J.H. & Huang, Chun-Nen & Chuang, Yen-Ching & Tzeng, Gwo-Hshiung, 2020. "A new soft computing approach for analyzing the influential relationships of critical infrastructures," International Journal of Critical Infrastructure Protection, Elsevier, vol. 28(C).
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