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

SoftwareX, vol. 30, pp. 102176

Abstract

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 interactions, we present ASSUME, an open-source agent-based simulation framework that incorporates multi-agent deep reinforcement learning for modeling adaptive market participants. ASSUME offers a modular architecture for representing generator and demand-side agents, bidding strategies, and diverse market configurations. ASSUME has been proven effective in multiple research studies, demonstrating its ability to analyze complex bids, demand-side flexibility, and other market scenarios. By incorporating adaptive strategies through deep reinforcement learning, ASSUME supports dynamic strategy exploration, enabling a deeper understanding of electricity market behaviors. With its flexible architecture, documentation, tutorials, and broad accessibility, ASSUME ensures usability across different user groups, minimizing technical overhead and freeing up human resources for deeper insights into operational, economic, and policy-related challenges in this critical sector.

Authors 9

1. Nick Harder corresponding

   University of Freiburg

   Affiliation as printed

   Institute for Sustainable Systems Engineering, University of Freiburg, Freiburg, Germany

2. Kim K. Miskiw

   Karlsruhe Institute of Technology

   Affiliation as printed

   Institute of Information Systems and Marketing, Karlsruhe Institute of Technology, Karlsruhe, Germany

3. Manish Khanra

   Fraunhofer Institute for Systems and Innovation Research

   Affiliation as printed

   Fraunhofer Institute for Systems and Innovation Research, Karlsruhe, Germany

4. Florian Maurer Aachen

   FH Aachen

   Affiliation as printed

   FH Aachen - University of Applied Sciences, Aachen, Germany

5. Ramiz Qussous

   University of Freiburg

   Affiliation as printed

   Institute for Sustainable Systems Engineering, University of Freiburg, Freiburg, Germany

6. Christof Weinhardt

   Karlsruhe Institute of Technology

   Affiliation as printed

   Institute of Information Systems and Marketing, Karlsruhe Institute of Technology, Karlsruhe, Germany

7. Marian Klobasa

   Fraunhofer Institute for Systems and Innovation Research

   Affiliation as printed

   Fraunhofer Institute for Systems and Innovation Research, Karlsruhe, Germany

8. Mario Ragwitz

   Fraunhofer Research Institution for Energy Infrastructures and Geotechnologies IEG · Fraunhofer-Gesellschaft

   Affiliation as printed

   Fraunhofer Institute for Energy Infrastructures and Geothermal Systems, Cottbus, Germany

9. Anke Weidlich

   University of Freiburg

   Affiliation as printed

   Institute for Sustainable Systems Engineering, University of Freiburg, Freiburg, Germany