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Multi-Agent Social and Organizational Modeling of Electric Power and Natural Gas Markets

Author

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  • Michael J. North

    (Argonne National Laboratory)

Abstract

Complex Adaptive Systems (CAS) can be applied to investigate large-scale socio-cognitive-technical systems. Viewing such systems from a multi-agent social and organizational perspective allows innovative computational policy analysis. Argonne National Laboratory (ANL) has taken such a perspective to produce an integrated model of the electric power and natural gas markets. This model focuses on the organizational interdependencies between these markets. These organizational interdependencies are being strained by fundamental market transformations.

Suggested Citation

  • Michael J. North, 2001. "Multi-Agent Social and Organizational Modeling of Electric Power and Natural Gas Markets," Computational and Mathematical Organization Theory, Springer, vol. 7(4), pages 331-337, December.
    • Handle: RePEc:spr:comaot:v:7:y:2001:i:4:d:10.1023_a:1013406317362
    DOI: 10.1023/A:1013406317362
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    Citations

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    Cited by:

    1. Sensfuß, Frank & Ragwitz, Mario & Genoese, Massimo & Möst, Dominik, 2007. "Agent-based simulation of electricity markets: a literature review," Working Papers "Sustainability and Innovation" S5/2007, Fraunhofer Institute for Systems and Innovation Research (ISI).
    2. Lam, C.Y. & Tai, K., 2018. "Modeling infrastructure interdependencies by integrating network and fuzzy set theory," International Journal of Critical Infrastructure Protection, Elsevier, vol. 22(C), pages 51-61.
    3. Zhang, Pengcheng & Peeta, Srinivas, 2011. "A generalized modeling framework to analyze interdependencies among infrastructure systems," Transportation Research Part B: Methodological, Elsevier, vol. 45(3), pages 553-579, March.
    4. Dong, Shangjia & Wang, Haizhong & Mostafizi, Alireza & Song, Xuan, 2020. "A network-of-networks percolation analysis of cascading failures in spatially co-located road-sewer infrastructure networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 538(C).
    5. Gabriel Kuper & Fabio Massacci & Woohyun Shim & Julian Williams, 2020. "Who Should Pay for Interdependent Risk? Policy Implications for Security Interdependence Among Airports," Risk Analysis, John Wiley & Sons, vol. 40(5), pages 1001-1019, May.
    6. Ouyang, Min & Pan, ZheZhe & Hong, Liu & He, Yue, 2015. "Vulnerability analysis of complementary transportation systems with applications to railway and airline systems in China," Reliability Engineering and System Safety, Elsevier, vol. 142(C), pages 248-257.
    7. Moglen, Rachel L. & Barth, Julius & Gupta, Shagun & Kawai, Eiji & Klise, Katherine & Leibowicz, Benjamin D., 2023. "A nexus approach to infrastructure resilience planning under uncertainty," Reliability Engineering and System Safety, Elsevier, vol. 230(C).
    8. Daniel Then & Patrick Hein & Tanja M. Kneiske & Martin Braun, 2020. "Analysis of Dependencies between Gas and Electricity Distribution Grid Planning and Building Energy Retrofit Decisions," Sustainability, MDPI, vol. 12(13), pages 1-42, July.
    9. Thomas J. Lampoltshammer & Heidrun Maurer & Nike Pulda & Peter Klimek & Jan Hurt & Ursula Rosenbichler, 2023. "Challenges toward Evidence-Based Policymaking Using Agent-Based Modeling for Federal Sports Grants: A Self-Reflection from a Transdisciplinary Project," Sustainability, MDPI, vol. 15(4), pages 1-34, February.
    10. 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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