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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 [https://en.wikipedia.org/wiki/District_heating 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.
==Background Readings==
==Community==
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