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Equilibria in Network Constrained Markets with System Ope...
[Submitted on 31 Dec 2024 (v1), last revised 29 Aug 2026 (this v · 2024-12-31 · via cs.SI updates on arXiv.org

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Abstract:We study a networked economic system composed of $n$ producers supplying a single homogeneous good to a number of geographically separated markets and of a centralized authority, called the market maker. Producers compete à la Cournot, by choosing the quantities of good to supply to each market they have access to in order to maximize their profit. Every market is characterized by its inverse demand functions returning the unit price of the considered good as a function of the total available quantity. Markets are interconnected by a dispatch network through which quantities of the considered good can flow within finite capacity constraints and possibly satisfying additional linear physical constraints. Such flows are determined by the action of a system operator, who aims at maximizing a designated welfare function. We model such competition as a strategic game with $n+1$ players: the producers and the system operator. For this game, we first establish the existence of pure-strategy Nash equilibria under standard concavity assumptions. We then identify sufficient conditions for the game to be exact potential with an essentially unique Nash equilibrium. Next, we present a general result that connects the optimal action of the system operator with the capacity constraints imposed on the network. For the commonly used Walrasian welfare, our finding proves a connection between capacity bottlenecks in the market network and the emergence of price differences between markets separated by saturated lines. This phenomenon is frequently observed in real-world scenarios, for instance in power networks. Finally, we validate the model with data from the Italian day-ahead electricity market.

Submission history

From: Martina Vanelli [view email]
[v1] Tue, 31 Dec 2024 00:02:52 UTC (1,996 KB)
[v2] Sun, 29 Mar 2026 22:03:49 UTC (1,585 KB)
[v3] Sat, 29 Aug 2026 16:24:48 UTC (1,658 KB)