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, spatial, and infrastructural constraints. The work aims to identify feasible operating patterns for electricity and heating systems at the district and urban scale, and to study how spatial characteristics
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, storage, and local electricity grids. A key goal is to translate methodological innovations in deep learning into practical tools for sustainable urban energy systems, supporting applications in forecasting
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