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IEEE Transactions on Energy Markets Policy and Regulation
Article . 2025 . Peer-reviewed
License: IEEE Copyright
Data sources: Crossref
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Strategic and Fair Aggregator Interactions in Energy Markets: Multi-Agent Dynamics and Quasiconcave Games

Authors: Jiayi Li; Matt Motoki; Baosen Zhang;

Strategic and Fair Aggregator Interactions in Energy Markets: Multi-Agent Dynamics and Quasiconcave Games

Abstract

The introduction of aggregator structures has proven effective in bringing fairness to energy resource allocation by negotiating for more resources and economic surplus on behalf of users. This paper extends the fair energy resource allocation problem to a multi-agent setting, focusing on interactions among multiple aggregators in an electricity market. We prove that the strategic optimization problems faced by the aggregators form a quasiconcave game, ensuring the existence of a Nash equilibrium. This resolves complexities related to market price dependencies on total purchases and balancing fairness and efficiency in energy allocation. In addition, we design simulations to characterize the equilibrium points of the induced game, demonstrating how aggregators stabilize market outcomes, ensure fair resource distribution, and optimize user surplus. Our findings offer a robust framework for understanding strategic interactions among aggregators, contributing to more efficient and equitable energy markets.

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Keywords

Computer Science - Computer Science and Game Theory, Electrical Engineering and Systems Science - Systems and Control

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
Green