This study examines the implications of replacing the Italian vehicle fleet with electric vehicles powered exclusively through fast and slow charging. The purpose is to quantify the additional electrical energy and peak charging power required, and to assess their compatibility with the present characteristics of major European electricity systems. The methodology combines national mobility statistics, estimated charging demand profiles, and empirical scaling factors derived from refuelling infrastructure to determine both annual energy requirements and instantaneous power needs. The analysis indicates that full fleet electrification for night-only charging would increase national electricity consumption by approximately 40–50%, a substantial yet potentially manageable rise in annual energy consumption. By contrast, the charging power needed to support large-scale fast charging reaches values close to 280 gigawatts, far exceeding the peak loads currently managed by existing transmission networks. This peak requirement is nearly five times higher than the present Italian maximum demand and surpasses, by large margins, the peak values recorded in comparable European systems. The results indicate that the principal challenge of transport electrification lies in accommodating extremely concentrated power demand within limited temporal windows. The conclusions emphasize the need for substantial upgrades to transmission and distribution networks, complemented by the widespread adoption of controlled slow charging and demand-shifting strategies that can help reduce peak loads. These findings suggest that the feasibility of large-scale vehicle electrification hinges critically on managing instantaneous power rather than total energy, underscoring the importance of coordinating infrastructure planning, regulatory frameworks, and charging behavior to ensure that electric mobility can be integrated into existing power systems without compromising stability or reliability.

The goal of the present work is to evaluate and select the optimum chitosan-based biodegradable biopolymer composite for energy storage devices for sustainable planning. In this study, “sustainable planning” is specifically addressed at the material selection stage, focusing on the identification of biodegradable and environmentally benign polymer composites that reduce long-term ecological impact and electronic waste generation. The proposed model therefore supports early-stage sustainable design decisions without requiring a full life-cycle assessment. To assess the options—pure chitosan and chitosan modified with different weight percent (10%, 20% and 30%) of 2,6-pyridinedicarboxylic acid; the study offers an integrated multi-criteria decision-making (MCDM) approach called TOPSIS. The entropy approach is used to overcome the impreciseness of eliciting judgments in the preferences of criteria since information pertaining to material attributes is always imprecise. The best sources are then chosen using the TOPSIS approach. According to the results, alternating current (AC) conductivity (40 Hz) is the most important criterion, and chitosan–2,6-pyridinedicarboxylic acid (CPCA) 20 is the best option with the greatest score value. The robustness of the proposed methodology is further demonstrated by sensitivity analysis.