Conclusion
We have presented a modelling framework for estimating domestic energy end-use demand baseline in sub-city areas and we believe that it could be replicated by other LAs and could be used to make local energy planning recommendations. However, our validation results show a poor alignment with existing observed data as published by DECC. Our analysis seems to suggest that local area characteristics are important when systematically establishing energy baseline consumption for specific sub-city geographical areas. Subsequently, we believe that current UK Government regional and sub-city methods and data for domestic properties in its current most disaggregated form may not accurately represent energy consumption of geographically specific and homogenous urban areas in the UK and therefore be insufficient for providing evidence for meeting future challenges in planning local energy services and infrastructure. Our analysis also shows that there is a significant number of uncertainties which are not usually communicated and understood by LAs, policy development of national datasets, and other stakeholders such as planners, architects and engineers. To better understand, communicate and describe uncertainties, it is necessary to obtain a detailed local knowledge of the stock and non-filtered building or post code level consumption data. Further model validation to ascertain uncertainties in the CHM model, imputation algorithms, and DECC data is certainly needed. In our paper, we go even further to suggest that a re-think of underlying energy models to enable the integration of building and urban modelling challenges is necessary.