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This page is about the applications of machine learning (ML) in the context of district heating with sector coupling. For an overview of district heating more generally, please see the Wikipedia page on this topic.
To achieve decarbonization across the heating and power supply and the mobility sector, they are increasingly coupled within districts in a joint spatial and organizational context. ML by providing surrogate models of thermal processes and quantify uncertainties of loads, supply and mobility behavior.