Assessment of coupled PV-EV penetration in a grid-connected district energy system with scheduled charging: A case study of a mixed-use district in Northern Italy

The anticipated widespread adoption of Electric Vehicles (EVs) presents significant challenges for electricity infrastructure integration. In parallel, the rapid expansion of Photovoltaic (PV) systems in urban areas introduces additional operational challenges. In this context, this work presents a PV-EV penetration assessment framework with a scheduled charging scheme to reduce peak electricity demand from the grid through temporal load shifting. A stochastic agent-based modelling framework is adopted to represent user behaviour and EV charging demand. Then, a scheduled charging scheme is presented based on the simulated charging profiles, while different combinations of PV and EV penetration are assessed through a parametric scenario analysis. The performance of different combinations is evaluated by the grid electricity saving ratio, self-consumption ratio, self-sufficiency ratio, and self-consumption-sufficiency ratio. A case study of a mixed-use district in Milan, Italy, with a gross floor area of 0.73 km2 is analysed at hourly resolution over a one-year period. The proposed scheduled charging scheme reduces peak electricity demand by 10.26% and 40.06%. Within the simulated scenario set, the best-performing PV-EV penetration scenarios are found at high PV penetration levels (80% to 100%) combined with moderate EV penetration levels (30% to 50%). The results identify best-performing PV-EV penetration combinations for the selected case study and show that the proposed framework can provide practical planning guidance for mixed-use urban districts. Subject to the availability of comparable input data, the proposed district-scale framework can also be adapted to other geographical contexts.