Finding individual strategies for storage units in electricity market models using deep reinforcement learning

Finding individual strategies for storage units in electricity market models using deep reinforcement learning

Abstract Modeling energy storage units realistically is challenging as their decision-making is not governed by a marginal cost pricing strategy but relies on expected electricity prices. Existing electricity market models often use centralized rule-based bidding or global optimization approaches, w...

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Bibliographic Details
Main Authors:	Nick Harder, Anke Weidlich, Philipp Staudt
Format:	Article
Language:	English
Published:	SpringerOpen 2023-10-01
Series:	Energy Informatics
Subjects:	Agent-based modeling Electricity markets Energy storage Multi-agent reinforcement learnin Reinforcement learning
Online Access:	https://doi.org/10.1186/s42162-023-00293-0

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