Comparison of prediction models for determining energy demand in the residential sector of a country

The increasing need for energy conservation has led to the development of a range of energy models for assessing energy demand in the residential sector of a country. Even though such models deliver a principal solution for forecasting energy demand and assessing the impact of future energy saving measures, collecting the required baseline data is fraught with difficulties such as a complete lack of data, missing data within a dataset and a lack in coherence between different datasets in terms of detail, data collection method, baseline assumptions and sample size. This paper analyses the transferability and accuracy of twelve energy models (MAED-2, FfE-Gebäudemodell, CDEM, REM, CREEM, ECCABS, REEPS, BREHOMES, LEAP, DECM, CHM, BSM), taking Germany as case study example. Furthermore, a sensitivity analysis is conducted for each model to analyze the significance of the input variables for the overall modelling outcome, highlighting the most influential variables. It is shown that models with a high level of disaggregation do not necessarily guarantee more accurate results. Adjustments are proposed to improve the transferability of the models to the case study country Germany.