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Projecting building energy demand using probabilistic weather conditions
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Projecting building energy demand using probabilistic weather conditions

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CIBSE Technical Symposium, DeMontfort University, Leicester UK
6th and 7th September 2011


During a building’s lifespan, it is widely accepted that weather conditions may alter considerably due to climate change, thereby influencing heating and cooling demands. To make a design robust against these changes, a method of analysing the influences of climate change is required. The UK Climate Impact Programme (UKCIP) has developed an hourly Weather Generator that presents engineers with thousands of freely-available synthetic projections of future weather conditions for any UK site. However, traditional energy demand modelling using these raw projections would be impractically time consuming. A method has been developed whereby thousands of hourly weather years can be quickly assessed. The process first calibrates an energy “fingerprint” via dynamic simulation using a few selected years of data. The fingerprint is then applied to the synthetic years to estimate a range of building energy demand for a given future time frame, thus reducing the time required for computation to practical level. Excellent correlation between the fingerprint outputs and dynamic simulation have been shown (r² = 0.9889 and 0.9915). The method has been applied to an example building where net emissions resulting from heating and cooling were found to marginally increase from 2020 to
2080 regardless of the degree of climate change experienced. The situation would be improved by reducing demand for cooling and improving system efficiency.

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