ASSUME: An agent-based simulation framework for exploring electricity market dynamics with reinforcement learning

ASSUME: An agent-based simulation framework for exploring electricity market dynamics with reinforcement learning

Electricity markets are undergoing transformative changes driven by integrating renewable energy and emerging technologies, and evolving market conditions such as shifting demand patterns, regulatory reforms, and increased price volatility. To address the complexity of electricity markets and their...

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Bibliographic Details
Main Authors: Nick Harder, Kim K. Miskiw, Manish Khanra, Florian Maurer, Parag Patil, Ramiz Qussous, Christof Weinhardt, Marian Klobasa, Mario Ragwitz, Anke Weidlich
Format: Article
Language:English
Published: Elsevier 2025-05-01
Series:SoftwareX
Subjects:
Agent-based modeling
Electricity markets
Reinforcement learning
Python
Online Access:http://www.sciencedirect.com/science/article/pii/S2352711025001438
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