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Auteurs principaux: Hubert, Emma, Lolas, Dimitrios, Sircar, Ronnie
Format: Preprint
Publié: 2025
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Accès en ligne:https://arxiv.org/abs/2507.10604
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author Hubert, Emma
Lolas, Dimitrios
Sircar, Ronnie
author_facet Hubert, Emma
Lolas, Dimitrios
Sircar, Ronnie
contents This paper studies the optimal investment behavior of renewable electricity producers in a competitive market, where both prices and installation costs are influenced by aggregate industry activity. We model the resulting crowding effects using a mean field game framework, capturing the strategic interactions among a continuum of heterogeneous producers. The equilibrium dynamics are characterized via a coupled system of Hamilton-Jacobi-Bellman and Fokker-Planck equations, which describe the value function of a representative producer and the evolution of the distribution of installed capacities over time. We analyze both deterministic and stochastic versions of the model, providing analytical insights in tractable cases and developing numerical methods to approximate the general solution. Simulation results illustrate how aggregate investment responds to changing market conditions, cost structures, and exogenous productivity shocks.
format Preprint
id arxiv_https___arxiv_org_abs_2507_10604
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle A Mean Field Game for Capacity Expansion Modeling
Hubert, Emma
Lolas, Dimitrios
Sircar, Ronnie
Optimization and Control
Probability
This paper studies the optimal investment behavior of renewable electricity producers in a competitive market, where both prices and installation costs are influenced by aggregate industry activity. We model the resulting crowding effects using a mean field game framework, capturing the strategic interactions among a continuum of heterogeneous producers. The equilibrium dynamics are characterized via a coupled system of Hamilton-Jacobi-Bellman and Fokker-Planck equations, which describe the value function of a representative producer and the evolution of the distribution of installed capacities over time. We analyze both deterministic and stochastic versions of the model, providing analytical insights in tractable cases and developing numerical methods to approximate the general solution. Simulation results illustrate how aggregate investment responds to changing market conditions, cost structures, and exogenous productivity shocks.
title A Mean Field Game for Capacity Expansion Modeling
topic Optimization and Control
Probability
url https://arxiv.org/abs/2507.10604