A Stochastic Multi-agent Optimization Model for Energy Infrastructure Planning under Uncertainty in An Oligopolistic Market

Zhaomiao Guo and Yueyue Fan ()
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Zhaomiao Guo: University of California
Yueyue Fan: University of California

Networks and Spatial Economics, 2017, vol. 17, issue 2, No 9, 609 pages

Abstract: Abstract This paper presents a mathematical model for analyzing long-term infrastructure investment decisions in a deregulated electricity market, such as the case in the United States. The interdependence between different decision entities in the system is captured in a network-based stochastic multi-agent optimization model, where new entrants of investors compete among themselves and with existing generators for natural resources, transmission capacities, and demand markets. To overcome computational challenges involved in stochastic multi-agent optimization problems, we have developed a solution method by combining stochastic decomposition and variational inequalities, which converts the original problem to many smaller problems that can be solved more easily.

Keywords: Energy infrastructure planning; Oligopolistic market; Equilibrium; Stochastic multi-agent optimization; Decomposition (search for similar items in EconPapers)
Date: 2017
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Citations: View citations in EconPapers (5)

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DOI: 10.1007/s11067-016-9336-8

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