Welcome to the ASSUME Toolbox

The transformation of electricity markets associated with the transition towards high shares of renewable power generation results in the constant development of market mechanisms, increasing sector coupling, and creating new market platforms. Introducing a new market or changing the current market design does, however, affect all other markets and their participants because of their strong interrelation in not necessarily foreseeable ways. This raised the need for tools and simulation models to investigate and understand such complex interplay of markets and predict possible adverse effects and misuse of market power.

Within the ASSUME project (2021 – 2025) a team of researchers developed a highly modular and easy-to-use energy market simulation toolbox with integrated reinforcement learning methods.

With ADAPT (2025 – 2028), the successor of the ASSUME project, we aim to expand on this. The ADAPT project – Adaptive AI‑supported Simulation Toolbox for Energy Markets Design – is developing a user‑friendly, adaptive simulation platform built on deep reinforcement learning (DRL). ASSUME already provides a comprehensive technical foundation that can be used for market‑design studies, and will be further developed in ADAPT in three major areas:

Adaptive market‑agent – The platform introduces an AI‑driven market‑agent that represents the regulator or market‑design authority. It can autonomously tweak market rules and parameters, observe how participants react, and continuously learn how to improve the design. This creates flexible, self‑optimising market‑designs that stay effective in a rapidly changing environment.

Low‑code, user‑friendly RL toolbox with explainable results – A low‑code reinforcement‑learning interface and an intuitive front‑end make the advanced DRL engine accessible to researchers without deep programming skills. Integrated AI assistants built on large‑language models guide users through configuration and operation, while built‑in explainability tools shed light on the multi‑agent simulation outcomes, fostering trust in the insights generated.

Inclusion of local grids and sector coupling – The tool is extended to model distribution networks, local energy systems and cross‑sector interactions. This enables distribution‑system operators and other downstream actors to simulate congestion‑management measures, test regulatory options (e.g., extensions of § 14a EnWG), and design incentive schemes for flexible loads such as electrolyzers, steel plants and other industrial consumers that can respond to dynamic price and grid signals, thereby supporting overall system optimisation and stability.

These developments will allow researchers, TSOs, DSOs, unit operators, regulators to assess the effects of market or regulatory changes in a model that captures intricate relationships between market designs and market participants. Use cases could include reforms to grid‑tariff structures, the creation of capacity markets and bidding zone configurations.