This study develops a unified optimization framework to evaluate and compare the performance of electric, conventional, and hybrid vehicle routing strategies under consistent operational conditions. The proposed model integrates routing decisions, energy consumption, infrastructure constraints, and emission considerations within a single mathematical formulation, enabling a comprehensive assessment of both economic and environmental performance. Using a benchmark urban transportation network, the study analyzes route configurations, operational costs, financial feasibility, and carbon emissions across the three vehicle technologies. The results indicate that electric vehicles offer lower and more stable operational costs, with zero direct emissions. In contrast, conventional vehicles offer greater operational flexibility, albeit at the expense of higher costs and a greater environmental impact. The hybrid model, which allows endogenous technology selection at the route level, achieves the most balanced performance by assigning vehicle types based on route-specific characteristics. This leads to significant reductions in both operational costs and emissions compared to single-technology approaches. The findings underscore the importance of integrated and flexible routing strategies in supporting sustainable transportation planning, offering practical insights for policymakers and transport operators in designing efficient and environmentally responsible systems.

The transition toward low-carbon cities increasingly relies on community-based energy systems that integrate distributed renewable generation and shared storage infrastructure. This study examines how strategic prosumer grouping within community energy storage (CES) and shared energy storage (SES) systems can enhance the sustainability, efficiency, and resilience of urban energy networks. An optimization framework is developed to determine grouping configurations that balance heterogeneous energy production and demand under renewable uncertainty, particularly solar variability. Two community structures are compared: an individual model that clusters prosumers with similar generation characteristics, and a cooperative model that encourages resource sharing among prosumers with diverse production capacities and consumption patterns. Results indicate that cooperative grouping substantially improves system-level performance, reducing reliance on external energy supply and lowering overall procurement costs while enhancing resilience against seasonal and hourly fluctuations. By leveraging diversity within communities, the cooperative structure achieves more stable storage utilization and mitigates imbalance risks associated with renewable intermittency. Sensitivity analysis further shows that poorly designed grouping configurations can generate instability and inefficiencies, highlighting the importance of community structure in sustainable energy planning. The findings position prosumer grouping as a critical design decision in urban CES/SES deployment and offer practical insights for policymakers and planners seeking to strengthen renewable integration and support resilient, sustainable city development.