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- W4294531220 abstract "To meet carbon reduction goals, municipalities, universities, and other large organizations need reliable and adaptable models that provide detailed building performance metrics to efficiently manage future energy demand. At the urban scale, models are often restricted by access to usage and geometry data and can only accurately predict aggregate energy demand based on historic data or statistical models. This paper seeks to present a novel workflow that uses institutional GIS datasets to produce calibrated multi-zone energy models for future scenario assessment and to inform building retrofitting options. The authors hope that the introduced workflow leads to a wider adoption of the involved tools to support the environmental strategies of others." @default.
- W4294531220 created "2022-09-03" @default.
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- W4294531220 date "2017-08-07" @default.
- W4294531220 modified "2023-09-23" @default.
- W4294531220 title "Campus Energy Model: Using a Semi-Automated Workflow to Build Spatially Resolved Campus Building Energy Models for Climate Change and Net-Zero Scenario Evaluation" @default.
- W4294531220 doi "https://doi.org/10.26868/25222708.2017.361" @default.
- W4294531220 hasPublicationYear "2017" @default.
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