Regional-Level Disaggregation of EV Uptake Energy Consumption Using Bottom-Up Approach

Using the top-down approach, EV uptake energy consumption projections (EVECP) do not consider local demographic and socio-economic factors that hinder accurate load prediction on the electric grids, demanding a bottom-up approach. However, existing bottom-up approaches, whether they consider disaggregation or not, are mainly based on assumed demographic and socio-economic factor values. Therefore, these approaches have limited efficacy and generalization capability. To bridge this gap, this paper introduces a novel evidence-based disaggregation of EVECP produced by a top-down approach to local area levels. The proposed approach leverages their independent impact (II) and joint impact (JI) with a new modelling approach that considers both their positive and negative influence over EV uptake through Bayes’ theorem. The II and JI capture insights into how one factor impacts others, leading to selection factors for more reliable projections. The validation with actual EV energy consumption exhibits that II and JI produce more accurate projections for Victorian LGAs than CSIRO. The yearly EVECP projections reveal that EVECP increases over time, and urban areas have faster energy consumption growth. Results show EVECP increases in 2026 and 2041 from 2025 are 111.09%, 104.65% and 7888.86%, 5458.45% for II/JI and CSIRO projections, respectively, in urban.