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- W4384696130 abstract "Existing buildings have a high potential to improve their energy performance and occupant satisfaction through retrofit projects. This thesis brings together a rapid energy modelling approach, with occupant feedback data in the form of unsolicited maintenance requests, to inform retrofit decisions that can improve overall building performance. The methodology is presented as three components, first generating an archetype-based rapid energy model of an existing building. Then, applying data analytics on maintenance request data to determine insights on the building performance and identify retrofit opportunities. Finally, evaluating the data-informed retrofit opportunities in the calibrated energy model to help stakeholders pursue building performance improvements. A case study has been conducted on the workflow, with results demonstrating the numerous benefits. This research introduces a novel methodology that leads to future work opportunities which are presented in the conclusion." @default.
- W4384696130 created "2023-07-20" @default.
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- W4384696130 date "2023-07-18" @default.
- W4384696130 modified "2023-09-25" @default.
- W4384696130 title "A Methodology for Rapid Energy Modelling and Maintenance Request Data Informed Building Retrofit Opportunity Analysis" @default.
- W4384696130 doi "https://doi.org/10.22215/etd/2023-15635" @default.
- W4384696130 hasPublicationYear "2023" @default.
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