AI-Based Transparency and Governance Tools for Regional Energy Systems
Potential Applications for Brandenburg
DOI:
https://doi.org/10.52825/th-wildau-ensp.v3i.3529Keywords:
Regional Energy Systems, Energy Governance, Transparency Tools, Multi-Level Governance, Decentralised Energy Transition, Explainable AI, Agent-Based AIAbstract
The transition to decentralised renewable energy systems creates a threefold transparency deficit at regional level: energy data is available, but is scarcely accessible for local governance processes (data transparency); decision-making processes are difficult to trace (process transparency); and AI-supported analyses often remain incomprehensible to decision-makers (explainability transparency). This paper conceptualises AI not as an optimisation tool, but as a mediating infrastructure between the data landscape and human decision-making processes. Methodologically, it follows the Design Science Research approach. The eight-phase process model developed anchors explicit MLG stakeholder roles and AI levers institutionally; a modular platform architecture with a dedicated governance logic layer ensures embedding within decision-making processes. Using Brandenburg as an example, three potential applications are demonstrated: a regional energy report, a forecasting model for wind energy generation at the individual turbine level, and a planned approach to AI-supported stakeholder analysis. As all tools are based on open data available nationwide, the concept is transferable to other regions with a comparable MLG structure.
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Copyright (c) 2026 Benjamin lemhényi Hankó, Benjamin Hagedorn, Christian Matthaei, Carolin Bachert, Bastian Halecker
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