Multi-Agent Receding Horizon Games Framework for Autonomous Market Participation
Abstract
Electrochemical distributed energy resources (DERs), such as electrolyzers and battery energy storage systems, consume large amounts of electricity. Buying that power directly from wholesale markets can sharply reduce operating costs. Accessing these markets, however, requires a minimum bid size that individual small or medium-scale units struggle to meet. Grouping several units to bid as a single participant clears this barrier while letting each unit use its own low-cost renewable generation. The common remedy is to hire a third-party aggregator, but aggregators charge commissions and solve a centralized optimization that often favors certain units over others. A fairer alternative is peer-to-peer (P2P) participation, where units form a self-governing group and bid jointly with no central authority. Because each self-interested unit is unwilling to share private data, coordination is best posed as a game-theoretic distributed optimization problem. Existing P2P methods, however, address only single-round spot markets and ignore the two-stage structure of real wholesale markets, where participants commit a day ahead and continuously adjust in real time. We close this gap with a two-stage receding-horizon generalized Nash equilibrium (GNE) game. Each unit re-optimizes its strategy every five minutes over a rolling one-hour horizon, while the group satisfies both market stages collectively. Units exchange only publicly visible aggregate power, never private cost or production data. We apply the approach to a six-unit fleet on the PJM market. It delivers 37% higher profit, 29% lower electricity cost, and 92% less renewable curtailment than individual participation, with every unit better off.
Related
- Receding Horizon Control and Dissipativity - Optimal Control, Games and Uncertainty
- Stability Filters for Receding-Horizon Games
- Characterizing Identifiability and Generalization for Inverse Receding-Horizon Linear-Quadratic Regulator Problems
- Supply Chain Information Sharing among Competitors: Profit-Based Participation under Market Shocks
- Hankel-Koopman Finite-Horizon Energy Decomposition of Coupled Experimental Data: A Three-Phase Data-Driven Twin Forecasting Framework
BibTeX
@misc{brahmbhatt2026multiagent,
title = {{Multi-Agent Receding Horizon Games Framework for Autonomous Market Participation}},
author = {Parth Brahmbhatt and Styliani Avraamidou},
howpublished = {arXiv},
year = {2026},
month = aug,
doi = {10.48550/arxiv.2608.30136},
eprint = {2608.30136},
archivePrefix = {arXiv},
url = {https://arxiv.org/abs/2608.30136},
note = {CC BY 4.0},
}
RIS
TY - UNPB
TI - Multi-Agent Receding Horizon Games Framework for Autonomous Market Participation
AU - Parth Brahmbhatt
AU - Styliani Avraamidou
PY - 2026
DA - 2026/08/31
PB - arXiv
DO - 10.48550/arxiv.2608.30136
UR - https://arxiv.org/abs/2608.30136
AB - Electrochemical distributed energy resources (DERs), such as electrolyzers and battery energy storage systems, consume large amounts of electricity. Buying that power directly from wholesale markets can sharply reduce operating costs. Accessing these markets, however, requires a minimum bid size that individual small or medium-scale units struggle to meet. Grouping several units to bid as a single participant clears this barrier while letting each unit use its own low-cost renewable generation. The common remedy is to hire a third-party aggregator, but aggregators charge commissions and solve a centralized optimization that often favors certain units over others. A fairer alternative is peer-to-peer (P2P) participation, where units form a self-governing group and bid jointly with no central authority. Because each self-interested unit is unwilling to share private data, coordination is best posed as a game-theoretic distributed optimization problem. Existing P2P methods, however, address only single-round spot markets and ignore the two-stage structure of real wholesale markets, where participants commit a day ahead and continuously adjust in real time. We close this gap with a two-stage receding-horizon generalized Nash equilibrium (GNE) game. Each unit re-optimizes its strategy every five minutes over a rolling one-hour horizon, while the group satisfies both market stages collectively. Units exchange only publicly visible aggregate power, never private cost or production data. We apply the approach to a six-unit fleet on the PJM market. It delivers 37% higher profit, 29% lower electricity cost, and 92% less renewable curtailment than individual participation, with every unit better off.
ER -