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Decentralized Integration of Grid Edge Resources into Wholesale Electricity Markets via Mean-field Games

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arxiv 2503.07984 v1 pith:OO64NPRM submitted 2025-03-11 eess.SY cs.SY

classification eess.SYcs.SY
keywords energyprosumersgridmarketresourceswholesaledersmarkets
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Grid edge resources refer to distributed energy resources (DERs) located on the consumer side of the electrical grid, controlled by consumers rather than utility companies. Integrating DERs with real-time electricity pricing can better align distributed supply with system demand, improving grid efficiency and reliability. However, DER owners, known as prosumers, often lack the expertise and resources to directly participate in wholesale energy markets, limiting their ability to fully realize the economic potential of their assets. Meanwhile, as DER adoption grows, the number of prosumers participating in the energy system is expected to increase significantly, creating additional challenges in coordination and market participation. To address these challenges, we propose a mean-field game framework that enables prosumers to autonomously learn optimal decision policies based on dynamic market prices and their variable solar generation. Our framework is designed to accommodate heterogeneous agents and demonstrates the existence of a mean-field equilibrium (MFE) in a wholesale energy market with many prosumers. Additionally, we introduce an algorithm that automates prosumers' resource control, facilitating real-time decision-making for energy storage management. Numerical experiments suggest that our approach converges towards an MFE and effectively reduces peak loads and price volatility, especially during periods of external demand or supply shocks. This study highlights the potential of a fully decentralized approach to integrating DERs into wholesale markets while improving market efficiency.

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  1. A Hybrid Mean Field Framework for Aggregators Participating in Wholesale Electricity Markets

    eess.SY 2025-07 conditional novelty 5.0 of 10

    A hybrid mean-field control/game plus reinforcement learning algorithm lets DER aggregators learn storage policies under endogenous wholesale prices, with a conditional equilibrium proof and an Oahu case study.

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