A GIS-based bottom-up space heating demand model of the London domestic stock

This paper demonstrates a systematic approach towards exploring the impact of urban built form and the heat island effect on the levels of domestic energy consumption in London. The study combines GIS databases and a modified version of the Standard Assessment Procedure (SAP) algorithm in order to estimate the space heating demand of urban domestic energy users. The output data is aggregated to the Middle Layer Super Output Area (MLSOA) level. External air temperatures in various locations across London were predicted as part of the London Site Specific Air Temperature (LSSAT) model development. This data was used as input to the energy use calculation model. Comparison of the model output for 95 case study areas with top-down energy statistics at MLSOA level demonstrated that the model ranks areas based on their domestic energy demand with relative success.

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