Increasing the realism of electricity market modeling through market interrelations. - Ramiz Qussous; Nick Harder; Mirko Schäfer; Anke Weidlich (OSMSES, 2022)

Modeling Participation of Storage Units in Electricity Markets using Multi-Agent Deep Reinforcement Learning. - Nick Harder; Anke Weidlich; Philipp Staudt (e-Energy, 2023)

Market Abstraction of Energy Markets and Policies - Application in an Agent-Based Modeling Toolbox. - Florian Maurer 007; Kim K. Miskiw; Rebeca P. Ramírez Acosta; Nick Harder; Volker Sander; Sebastian Lehnhoff (EI.A (2), 2023)

Finding individual strategies for storage units in electricity market models using deep reinforcement learning. - Nick Harder; Anke Weidlich; Philipp Staudt (Energy Inform., 2023)

Multi Power-Market Bidding: Stochastic Optimization and Reinforcement Learning. - Kim K. Miskiw; Nick Harder; Philipp Staudt (HICSS, 2024)

ASSUME: An agent-based simulation framework for exploring electricity market dynamics with reinforcement learning. - Nick Harder; Kim K. Miskiw; Manish Khanra; Florian Maurer 007; Parag Patil; Ramiz Qussous; Christof Weinhardt; Marian Klobasa; Mario Ragwitz; Anke Weidlich (SoftwareX, 2025)