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Institute for Machine Learning
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AI4GreenHeatingGrids

Term: 06/2023 – 05/2026 (36 months)

Partner: Arteria Technologies GmbH, Universität Graz Institut für Mathematik und Wissenschaftliches Rechnen

Topic:
Climate neutrality and energy supply challenges necessitate a reduction in energy consumption (optimally, while maintaining or improving living standards). Here,energy efficiency emerges as the primary mitigation strategy. While energy is commonly associated with electricity, thermal energy or heat plays a significant role in end-user energy consumption. Heating systems, including conventional and renewable options, are crucial for warming houses and tap water. However, integrating renewable heat into district heating systems in a sustainable, and efficient way is non-trivial. Today's challenges require advanced control systems that are able to optimize heating plant parameters based on consumption and production forecasts. The proposed project thus aims to explore algorithms for forecasting demand, production profiles, and control parameters in complex district heating networks. As such, the condcuted research will form the basis to facilitate the large-scale integration of renewable heat and contribute to significant decarbonization and emission reductions in Austria and globally.