AI Market Simulation for Hydrogen Network Planning at Open Grid Europe (OGE)

To prepare for Germany's energy transition, Open Grid Europe (OGE) is investing in hydrogen infrastructure and developing a digital twin to analyze future scenarios and market setups. This proactive approach, including an AI-powered market simulation developed by ML6, will help OGE optimize network development and ensure the effective management of their future hydrogen infrastructure, solidifying their position as a leader in the evolving energy landscape.

As one of Europe's leading gas transmission system operators, and the largest in Germany, Open Grid Europe (OGE) is actively preparing for the 'Energiewende.' Their strategy involves investing in the future capacity to transport hydrogen by strategically repurposing existing gas infrastructure and constructing new hydrogen pipelines.

The transportation of hydrogen brings with it a new set of challenges and uncertainties.

• Market development: The hydrogen market is in its early stages, with individual clusters being put into operation and only gradually connecting to form a nationwide market. This makes it challenging to implement a fully-fledged entry-exit system from the outset, and requires a coordinated development of both network infrastructure and market.
• Network Balancing: Balancing the hydrogen network requires a different approach compared to the natural gas market. This is due to the intermittent nature of hydrogen production, particularly green hydrogen generated from renewable energy sources, and its integration with electricity markets.

To address these challenges, OGE is developing a digital twin to analyze potential future scenarios, market setups, and their corresponding impact on the network.

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ML6 has created an AI-powered market simulation that models the buying behavior of various industries across multiple markets. The buying strategies of market participants can be configured using either predefined rules or reinforcement learning with an industry-specific optimization function.

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This simulated buying behavior is then integrated into a model of the future hydrogen network providing OGE the ability to easily assess the impact on the network and the adequacy of planned investments to manage the scenario effectively.