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A Stochastic Multi-Agent Optimization Model for Energy Infrastructure Planning Under Uncertainty and Competition

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  • Guo, Zhaomiao
  • Fan, Yueyue

Abstract

This paper presents a stochastic multi-agent optimization model that supports energy infrastructure planning under uncertainty. The interdependence between different decision entities in the system is captured in an energy supply chain network, where new entrants of investors compete among themselves and with existing generators for natural resources, transmission capacities, and demand markets. Directly solving the stochastic energy supply chain planning problem is challenging. Through decomposition and reformulation, we convert the original problem to many traffic network equilibrium problems, which enables efficient solution algorithm design. View the NCST Project Webpage

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  • Guo, Zhaomiao & Fan, Yueyue, 2017. "A Stochastic Multi-Agent Optimization Model for Energy Infrastructure Planning Under Uncertainty and Competition," Institute of Transportation Studies, Working Paper Series qt89s5s8hn, Institute of Transportation Studies, UC Davis.
    • Handle: RePEc:cdl:itsdav:qt89s5s8hn
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    1. R. T. Rockafellar, 1976. "Augmented Lagrangians and Applications of the Proximal Point Algorithm in Convex Programming," Mathematics of Operations Research, INFORMS, vol. 1(2), pages 97-116, May.
    2. Zugang Liu & Anna Nagurney, 2007. "Financial Networks with Intermediation and Transportation Network Equilibria: A Supernetwork Equivalence and Reinterpretation of the Equilibrium Conditions with Computations," Computational Management Science, Springer, vol. 4(3), pages 243-281, July.
    3. Bar-Gera, Hillel, 2010. "Traffic assignment by paired alternative segments," Transportation Research Part B: Methodological, Elsevier, vol. 44(8-9), pages 1022-1046, September.
    4. Genc, Talat S. & Reynolds, Stanley S. & Sen, Suvrajeet, 2007. "Dynamic oligopolistic games under uncertainty: A stochastic programming approach," Journal of Economic Dynamics and Control, Elsevier, vol. 31(1), pages 55-80, January.
    5. James B. Bushnell & Erin T. Mansur & Celeste Saravia, 2008. "Vertical Arrangements, Market Structure, and Competition: An Analysis of Restructured US Electricity Markets," American Economic Review, American Economic Association, vol. 98(1), pages 237-266, March.
    6. Liu, Zugang & Nagurney, Anna, 2011. "Supply chain outsourcing under exchange rate risk and competition," Omega, Elsevier, vol. 39(5), pages 539-549, October.
    7. Zugang Liu & Anna Nagurney, 2009. "An integrated electric power supply chain and fuel market network framework: Theoretical modeling with empirical analysis for New England," Naval Research Logistics (NRL), John Wiley & Sons, vol. 56(7), pages 600-624, October.
    8. Nagurney, Anna, 2006. "On the relationship between supply chain and transportation network equilibria: A supernetwork equivalence with computations," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 42(4), pages 293-316, July.
    9. Hu, X. & Ralph, D. & Ralph, E.K. & Bardsley, P. & Ferris, M.C., 2004. "Electricity Generation with Looped Transmission Networks: Bidding to an ISO," Cambridge Working Papers in Economics 0470, Faculty of Economics, University of Cambridge.
    10. Nagurney, Anna & Liu, Zugang & Cojocaru, Monica-Gabriela & Daniele, Patrizia, 2007. "Dynamic electric power supply chains and transportation networks: An evolutionary variational inequality formulation," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 43(5), pages 624-646, September.
    11. Pierre-Olivier Pineau & Pauli Murto, 2003. "An Oligopolistic Investment Model of the Finnish Electricity Market," Annals of Operations Research, Springer, vol. 121(1), pages 123-148, July.
    12. R. T. Rockafellar & Roger J.-B. Wets, 1991. "Scenarios and Policy Aggregation in Optimization Under Uncertainty," Mathematics of Operations Research, INFORMS, vol. 16(1), pages 119-147, February.
    13. Zugang Liu & Anna Nagurney, 2013. "Supply chain networks with global outsourcing and quick-response production under demand and cost uncertainty," Annals of Operations Research, Springer, vol. 208(1), pages 251-289, September.
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    Cited by:

    1. Dávid Csercsik & László Á. Kóczy, 2017. "Efficiency and Stability in Electrical Power Transmission Networks: a Partition Function Form Approach," Networks and Spatial Economics, Springer, vol. 17(4), pages 1161-1184, December.
    2. Fan, Yueyue & Zhang, Yunteng, 2019. "Next-Generation Transit System Design During a Revolution of Shared Mobility," Institute of Transportation Studies, Working Paper Series qt77t6g3w4, Institute of Transportation Studies, UC Davis.
    3. Kerstin Dächert & Sauleh Siddiqui & Javier Saez-Gallego & Steven A. Gabriel & Juan Miguel Morales, 2019. "A Bicriteria Perspective on L-Penalty Approaches – a Corrigendum to Siddiqui and Gabriel’s L-Penalty Approach for Solving MPECs," Networks and Spatial Economics, Springer, vol. 19(4), pages 1199-1214, December.
    4. Yekini Shehu & Lulu Liu & Xiaolong Qin & Qiao-Li Dong, 2022. "Reflected Iterative Method for Non-Monotone Equilibrium Problems with Applications to Nash-Cournot Equilibrium Models," Networks and Spatial Economics, Springer, vol. 22(1), pages 153-180, March.
    5. Xie, Fei & Huang, Yongxi, 2018. "A multistage stochastic programming model for a multi-period strategic expansion of biofuel supply chain under evolving uncertainties," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 111(C), pages 130-148.

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